19.03.2007:
[1]. Prepare Proposal. Examination will be held on May 2007 (before new semester or about end of Summer Semester)--> Send me your document as a progress for it!.
[2]. Help by Mr. B about MESH/ GRID problem:--> May be the S/W not ur program.
26.03.2007:
[1]. I send my progress reports: 2 file present in front of Ajarn, then his messages are:
[2]. Want to see velocity vectors from Velocity_Inlet[1] to Pressure_Outlet[1] by assume Boundary Condition look like Paper ELSEVIER...CFD Study Flow in Natural Rubber Smoking Room (2007)...
[3]. Then the simulate concentration PM in empty rooms: one by one I/O...
+
[4]. AjG: read Tutorial05 FLUENT 5/6
Assumptions:
not have radiation,
use Bousinessq,
temperature operation?,
heat flux=0[standard in fluent],
velocity inlet at the top of the chamber, only Vy...[AjPT:from Paper Mr. X===0.63m/s(already read it by 28.03.2007)],
simulate 1st: fluid AIR then PARTICLEs (use 0.1micron),
operationng=1,
temp.,
cp=constant or not,
...
[5]. Think: send doc. to AjPT text to correction by him, before 23April2007
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Wednesday, March 28, 2007
Thursday, March 15, 2007
[gambit2.2]What does "geometry not C1 or G1" meant?
[1]. http://www.caddigest.com/subjects/solidworks/select/cadcamnet_proe_vs_solidworks.htm
Curvature continuity
To appreciate what enables CAD software to produce graceful flowing curves, it’s important to understand some concepts of continuous curvature. The curvature of a curve or surface is the inverse of the radius of the curve at each point along its length. An arc, circle, or cylinder has a constant curvature as does a straight line or plane whose curvature is zero. When a circular fillet is tangent to a straight-line segment, the curvature falls abruptly from a constant value to zero.
The human eye can perceive abrupt changes in the curvature of surfaces. A round fillet meeting a plane surface appears to have a ridge at its edge, even though none physically exists. Artfully designed products thus avoid discontinuities in the derivative (rate of change) of the curvature of curves and surfaces except where ridges and sharp edges are used for accent. Entities whose curvature derivative is continuous are said to be C2 (or sometimes G2) continuous. Curves and surfaces that are tangent are said to be C1 (or G1) continuous, while continuous curves or surfaces with sharp edges are said to be C0 (or G0) continuous.
Most CAD systems can produce curves and surfaces that are continuous (C0) or tangent (C1). However, only the best systems can produce surfaces that can be joined with C2 continuity under a wide range of conditions. Pro/Engineer Wildfire maintains C2 continuity between adjacent surfaces under more conditions than SolidWorks 2004.
[2].http://www.cs.stevens.edu/~quynh/courses/cs537-notes/lesson6-CurvesAndSurfaces.ppt#257,2,Curves and Surfaces
Joining Curve Segments Together
G0 geometric continuity: Two curve segments join together
G1 geometric continuity: The direction of the two segments’ tangent vectors are equal at the join point
C1 (parametric) continuity: Tangent vectors of the two segments are equal in magnitude and direction
(C1 Þ G1 unless tangent vector = [0, 0, 0])
Cn (parametric) continuity: Direction and magnitude through the nth derivative are equal at the join point
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Curvature continuity
To appreciate what enables CAD software to produce graceful flowing curves, it’s important to understand some concepts of continuous curvature. The curvature of a curve or surface is the inverse of the radius of the curve at each point along its length. An arc, circle, or cylinder has a constant curvature as does a straight line or plane whose curvature is zero. When a circular fillet is tangent to a straight-line segment, the curvature falls abruptly from a constant value to zero.
The human eye can perceive abrupt changes in the curvature of surfaces. A round fillet meeting a plane surface appears to have a ridge at its edge, even though none physically exists. Artfully designed products thus avoid discontinuities in the derivative (rate of change) of the curvature of curves and surfaces except where ridges and sharp edges are used for accent. Entities whose curvature derivative is continuous are said to be C2 (or sometimes G2) continuous. Curves and surfaces that are tangent are said to be C1 (or G1) continuous, while continuous curves or surfaces with sharp edges are said to be C0 (or G0) continuous.
Most CAD systems can produce curves and surfaces that are continuous (C0) or tangent (C1). However, only the best systems can produce surfaces that can be joined with C2 continuity under a wide range of conditions. Pro/Engineer Wildfire maintains C2 continuity between adjacent surfaces under more conditions than SolidWorks 2004.
[2].http://www.cs.stevens.edu/~quynh/courses/cs537-notes/lesson6-CurvesAndSurfaces.ppt#257,2,Curves and Surfaces
Joining Curve Segments Together
G0 geometric continuity: Two curve segments join together
G1 geometric continuity: The direction of the two segments’ tangent vectors are equal at the join point
C1 (parametric) continuity: Tangent vectors of the two segments are equal in magnitude and direction
(C1 Þ G1 unless tangent vector = [0, 0, 0])
Cn (parametric) continuity: Direction and magnitude through the nth derivative are equal at the join point
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Wednesday, March 14, 2007
[CFDPackages] For CFD Code Learner in the World
Good for Learner about CFD Code Packages in the world:
http://nenes.eas.gatech.edu/CFD/
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http://nenes.eas.gatech.edu/CFD/
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Friday, March 02, 2007
[indoorairindonesia]BAQ2006.org
http://pciaonline.org/2007IndiaForum/index.cfm?/c=callForAbstracts
http://www.pciaonline.org/references.cfm
http://www.pciaonline.org/events_viewer.cfm?id=76
The following websites are particularly relevant to household energy, indoor air pollution and health, and contain (in most cases) annotated and searchable bibliographies.
Asian Regional Cookstove Program (ARECOP)http://www.arecop.org/The ARECOP network is made up of organizations and individuals involved in improved cookstove programs and household energy issues. The network includes 14 countries in the Asia Region. It also acts as a forum for discussions on Improved Cookstove Programs in the region. ARECOP organizes regular workshops on issues such as commercialization; kitchen improvements; and household energy and health. Key themes include improved stoves, household energy, indoor air pollution etc. The website also features: Proceedings of ARECOP regional workshops; household energy activity and contact information on member countries; issues of GLOW magazine and monthly Letters from the Secretariat; links to relevant organizations and publications for household energy and health. Contact Information:
ARECOP SecretariatPO. Box 19, BulaksumurYogyakarta55281 Indonesia.Phone: 62-274-885247,Fax: 62-21-885423E-mail: secretariat@arecop.org, arecop@yogya.wasantara.net.id
September 13-15, Yogyakarta, Indonesia
The 5th Better Air Quality (BAQ) workshop will be held 13-15 September 2006 in the historic city of Yogyakarta in Central Java, Indonesia. The theme of BAQ 2006 is called a "Celebration of Efforts" to highlight the success stories that Asian countries, cities and communities have achieved over the last years in addressing air pollution while at the same time highlighting the efforts that are still ahead in improving air quality in Asia. The submission deadline for abstracts is 30 March 2006. For more information, please visit http://www.baq2006.org.
http://continuousimprovement.blogsome.com
http://Life4aaK.blogspot.com
http://godoproduction.blogspot.com
http://www.pciaonline.org/references.cfm
http://www.pciaonline.org/events_viewer.cfm?id=76
The following websites are particularly relevant to household energy, indoor air pollution and health, and contain (in most cases) annotated and searchable bibliographies.
Asian Regional Cookstove Program (ARECOP)http://www.arecop.org/The ARECOP network is made up of organizations and individuals involved in improved cookstove programs and household energy issues. The network includes 14 countries in the Asia Region. It also acts as a forum for discussions on Improved Cookstove Programs in the region. ARECOP organizes regular workshops on issues such as commercialization; kitchen improvements; and household energy and health. Key themes include improved stoves, household energy, indoor air pollution etc. The website also features: Proceedings of ARECOP regional workshops; household energy activity and contact information on member countries; issues of GLOW magazine and monthly Letters from the Secretariat; links to relevant organizations and publications for household energy and health. Contact Information:
ARECOP SecretariatPO. Box 19, BulaksumurYogyakarta55281 Indonesia.Phone: 62-274-885247,Fax: 62-21-885423E-mail: secretariat@arecop.org, arecop@yogya.wasantara.net.id
September 13-15, Yogyakarta, Indonesia
The 5th Better Air Quality (BAQ) workshop will be held 13-15 September 2006 in the historic city of Yogyakarta in Central Java, Indonesia. The theme of BAQ 2006 is called a "Celebration of Efforts" to highlight the success stories that Asian countries, cities and communities have achieved over the last years in addressing air pollution while at the same time highlighting the efforts that are still ahead in improving air quality in Asia. The submission deadline for abstracts is 30 March 2006. For more information, please visit http://www.baq2006.org.
http://continuousimprovement.blogsome.com
http://Life4aaK.blogspot.com
http://godoproduction.blogspot.com
Thursday, March 01, 2007
risktech2007_fullpaper
Fundamental concept of risk
A typical dictionary defines risk as the possibility of loss or injury. It implies that risk has two main components: the probability of some event occurring and the negative consequence if it occurs. Thus, to analyze risk we should be able to estimate these two factors. Boehm [1] translated this defnition into the
fundamental concept of risk management: the risk exposure, sometimes called risk impact.
Fundamental concept of risk (Cairo., et al., 1999)
A typical dictionary defines risk as the possibility of loss or injury. It implies that risk has two main components: the probability of some event occurring and the negative consequence if it occurs. Thus, to analyze risk we should be able to estimate these two factors. Boehm (1989) translated this definition into the fundamental concept of risk management: the risk exposure, sometimes called risk impact.
Where RE means risk exposure, P(UO) expresses the probability of an unsatisfactory outcome, and L(UO) means the loss to the parties affected if the outcome is unsatisfactory.
Usually the perception of risk is higher for those items over which one have little or no control. However, the importance of the risk factors might be considered as some combination of risk frequency (that is, how likely it is that the risk will occur) and risk impact (such as, how serious a threat the risk represents if it does occur). In considering risks you must also consider their perceived level of control. This represents the degree to which the project manager perceived that their actions could prevent the risk from occurring. Most of the probable risks or threats to projects can be reduced or avoided using an appropriate methodology. It can also be complemented with approximative methods, which can provide enough information to support risk management decisions.
Risk-reduction is a fundamental part of project management in software and knowledge engineering. Software risk management is important because it helps people to avoid disasters, rework, and overkill, it also stimulates win-win situations on software projects (Boehm, 1989).
We should be aware that by avoiding or reducing the most significant risks, managers make more informed decisions, we obtain better outcomes, and hence the project will have a higher probability of success.
Boehm (1988) suggests to use a software risk management plan, which consists of five steps:
• Identify the project's top risk items.
• Present a plan for resolving each risk item.
• Update list of top risk items, plan, and results monthly.
• Highlight risk-item status in monthly project reviews.
• Initiate appropriate corrective actions.
Successful management of a project leads to control. Control leads to quality. Quality leads to satisfied customers. And we know customers are the final arbiters of a product or service.
The main factors affecting contaminants OK
Characteristics of indoor air flows:
Gant., et al.; 2006 state a number of parameters which can be used to characterize the dispersion of a contaminant inside a room, i. e.:
1. Fresh Air/ Contaminant Distribution:
Contaminant Concentration, Local Mean Age of Air, Purging Effectiveness of Inlets, Local Specific Contaminant-Accumulating Index, Air Change Efficiency, Ventilation Effectiveness Factor, Relative Ventilation Efficiency.
2. Stability and Bouyancy of the Room Air:
Reynold Number, Rayleigh Number, Grashof Number, Froude Number, Richardson Number, Flux Richardson Number, Bouyancy Flux.
3. Temperature Distribution:
Air Diffusion Performance Index, Effective Draft Temperature.
4. Supply Air Conditions:
Purging Effectiveness of Inlet, Reynold Number, Froude Number, Archimedes Number.
Due to overlap between these subjects, some parameters appear more than once. Some parameters characterize directly the observed pattern of contaminant distribution whilst others characterize flow features, such as stability. Flow parameters such as the ‘mean age of air’ are difficult but not impossible to calculate experimentally. They are used mainly as a tool to help interpret data from numerical simulations of contaminant dispersion. For discussions on how these parameters are used to assess compliance with standards on room air quality, see Peng & Davidson (1999) or the ASHRAE Guides (2003).
Clearly the simplest indicator of contaminant distribution in a room is the contaminant concentration, i.e. the mass of contaminant per unit volume of air (measured in kg/m3). Contaminant concentration is sometimes expressed in terms of parts per million (ppm), or parts per billion, trillion etc. This can be based on either the mass fraction or the volume fraction.
Local Mean Age of Air is commonly used to evaluate the performance of a ventilation system and indoor air quality. The precise meaning of the local mean age is defined in Di Tommaso et al.; (1999) as follows: “the average time it takes for air to travel from the inlet to any point P in the room”.
The purging effectiveness of an inlet is a quantity that can be used to identify the relative performance of each inlet in a room where there are multiple inlets.
Peng et al.; (1999) classify the various measures used to characterize ventilation performance into three groups: measures of ventilation air-diffusing efficiency which indicate the ability to provide fresh air to occupants, ventilation effectiveness which indicate the ability to remove contaminants from a ventilated space and specific ventilation effectiveness which deals with specific situations.
Air Change Efficiency is a measure of how effectively the air present in a room is replaced by fresh air from the ventilation system (Di Tommaso et al.; 1999). It is the ratio of the room mean age that would exist if the air in the room were completely mixed to the average time of replacement of the room.
The Ventilation Effectiveness Faction (VEF) appears to be ASHRAE’s preferred method for characterizing indoor air quality and is based on the work of Zhang et al. (2001).
The relative ventilation efficiency is the ratio of the local mean age that would exist if the air in the room were completely mixed to the local mean age that is actually measured at a point.
Air Diffusion Performance Index (ADPI) is primarily a measure of occupant comfort rather than an indicator of contaminant concentrations. It expresses the percentage of locations in an occupied zone that meet air movement and temperature specifications for comfort.
The temperature effectiveness is similar in concept to ventilation effectiveness and reflects the ability of a ventilation system to remove heat.
The effective draft temperature, θ, indicates the feeling of coolness due to air motion:
where Tx and Tc are the local air-stream and average room dry-bulb temperatures (in ºC or K), Vx is the local air-stream centre-line velocity (in m/s) and θ is measured in K.
The Reynolds number, Re, expresses the ratio of the inertial forces to viscous forces:
where U and L are characteristic velocity and length scales of the flow and ν is the kinematic
viscosity.
Natural convection flows are often characterized using the Rayleigh Number, Ra, given by:
where g is the acceleration due to gravity (g = 9.81 m/s2), β the coefficient of thermal expansion (where for an ideal gas, β = T 1 ), ∆T the temperature difference, L the length scale (e.g. the height of the heated surface), υ the kinematic viscosity and α the thermal diffusivity (α = k /ρCp).
The Grashof number, Gr, is equivalent to the Rayleigh number divided by the Prandtl number:
where g is the acceleration due to gravity, β the coefficient of thermal expansion ∆T temperature difference, L the length scale and υ the kinematic viscosity.
The following form of the Froude number is used by Linden [6] to characterize flow through corridors and doorways and in combined displacement and wind ventilation cases.
where U and L are characteristic velocity and length scales, respectively, and g the acceleration due to gravity.
The Richardson number, Ri, characterizes the importance of buoyancy. It is calculated from:
where ∆ ρ is the density difference that occurs over a typical (usually vertical) length scale, L, in a flow of velocity, U.
The flux Richardson number, Rif, is used to characterize the stabilizing effect of stratification on turbulence:
where Pkb and Pk are the turbulence production due to buoyancy and shear respectively
The buoyancy flux, B, is calculated from:
Linden (1999) uses this to characterize buoyancy driven flows, where W is the heat flux, β = 1/ T is the coefficient of expansion and cp is the specific heat capacity at constant pressure.
The conditions of the supplied air are often characterized by the discharge Archimedes number, Ar, which expresses the ratio of the buoyancy forces to momentum forces or the strength of natural convection to forced convection:
where T ∆ is the temperature difference between supply and exhaust, U is the initial velocity of the discharged air, g is the acceleration due to gravity and L is the length scale of the supply terminal (i.e. diffuser or grille).
Aerosol as one kind of Particulate Matter and contaminants,
From pre-proposal….
The respiratory system (http://www.sirinet.net/~jgjohnso/respiratory.html accesed 01st March 2007)
CHAPTER 46, SECTION 3
THE RESPIRATORY SYSTEM
You have read how the blood transports oxygen from the lungs to cells and carries carbon dioxide from the cells to the lungs. It is the function of the respiratory system to transport gases to and from the circulatory system. The respiratory system involves both External and Internal respiration.
External Respiration is the exchange of gases between the atmosphere and the blood. Internal Respiration is the exchange of gases between the blood and the cells of the body. Cellular Respiration or Aerobic Respiration involves the use of oxygen to break down glucose in the cell. We will examine the structures and mechanisms that carry oxygen to the cells for use in aerobic respiration and that eliminate the carbon dioxide that is produced by the same process.
OBJECTIVES:
1. Differentiate external respiration from internal respiration.
2. Trace the path of air from the atmosphere to the bloodstream.
3. Describe how gases are exchanged in the lungs and transported in the bloodstream.
4. Summarize the skeletal and muscular changes that occur during breathing.
5. Describe how the rate of breathing is controlled.
RESPIRATION
1. THE MAIN JOB OF THE RESPIRATORY SYSTEM IS TO GET OXYGEN INTO THE BODY AND WASTE GASES OUT OF THE BODY. IT IS THE FUNCTION OF THE RESPIRATORY SYSTEM TO TRANSPORT GASES TO AND FROM THE CIRCULATORY SYSTEM.
2. Respiration is a vital function of all living organisms.
3. Respiration occurs at TWO DIFFERENT LEVELS:
A. The level of the CELL. In the Mitochondria of Eukaryotic Cells, Aerobic Respiration requires OXYGEN to break down Glucose, releases CARBON DIOXIDE, and produces large amounts of ATP. THIS LEVEL OF RESPIRATION IS CALLED INTERNAL RESPIRATION OR CELLULAR RESPIRATION.
B. The level of the ORGANISM. An organism must get oxygen into its CELLS and CARBON DIOXIDE back out. THIS LEVEL OF RESPIRATION IS CALLED EXTERNAL RESPIRATION BECAUSE THE EXCHANGE OF GASES TAKES PLACE WITH THE EXTERNAL ENVIRONMENT. THE EXCHANGE OF GASES, OXYGEN (O2) AND CARBON DIOXIDE (CO2) BETWEEN AIR AND BLOOD.
4. EXTERNAL RESPIRATION INVOLVES THE RESPIRATORY SYSTEM.
5. A RESPIRATORY SYSTEM IS A GROUP OF ORGANS WORKING TOGETHER TO BRING ABOUT THE EXCHANGE OF OXYGEN AND CARBON DIOXIDE WITH THE ENVIRONMENT.
6. A single-celled organism living in water (DIFFUSION) gets its oxygen directly from its surroundings (the water). The oxygen easily diffuses across the Cell Membrane. Carbon dioxide also diffuses across the Cell Membrane; thus single-celled organisms do not need a Respiratory System.
7. In MULTICELLULAR ORGANISMS, Each Cell consumes Oxygen and produces Carbon dioxide. Large Multicellular organism must have a Respiratory System to ensure the effective exchange of gasses with the Atmosphere quickly and efficiently to survive.
8. THIS OCCURS EVERY TIME AN ORGANISM TAKES A BREATH.
9. The atmosphere of planet Earth is approximately 78% Nitrogen and 21% Oxygen. The remaining 1% is made up of Carbon Dioxide, Water Vapor, and other trace gases.
10. Humans are Air Breathers; our Respiratory System has adapted to these concentrations of gases in the Atmosphere. If the amount of Oxygen FALLS much below 15 %, our Respiratory System will be UNABLE to provide enough Oxygen to support cellular respiration.
THE PASSAGE OF AIR AND THE RESPIRATORY STRUCTURES (Figure 46-16)
1. THE HUMAN RESPIRATORY SYSTEM CONSIST OF THE NOSE, NASAL CAVITY, PHARYNX, LARYNX, TRACHEA, SMALLER CONDUCTING PASSAGEWAYS (BRONCHI AND BRONCHIOLES), AND LUNGS.
2. The Respiratory System may be divided into the UPPER RESPIRATORY TRACT AND THE LOWER RESPIRATORY TRACT.
3. THE UPPER RESPIRATORY TRACT CONSISTS OF THE PARTS OUTSIDE THE THORACIC (CHEST) CAVITY: THE AIR PASSAGES OF THE NOSE, NASAL CAVITIES, PHARYNX (WINDPIPE), LARYNX (VOICE BOX), AND UPPER TRACHEA.
4. THE LOWER RESPIRATORY TRACT CONSISTS OF THE PARTS FOUND IN THE THORACIC (CHEST) CAVITY: THE LOWER TRACHEA AND THE LUNGS THEMSELVES.
5. Air ENTERS the Respiratory System through the Mouth or Nose.
6. Air entering the Nose passes into the NASAL CAVITY. The Nasal Cavity is richly supplied with arteries, veins, and capillaries, which bring nutrients and water to its cells.
7. As air pushes back from the Nasal Cavity, it enters the PHARYNX. The Pharynx is located in the back of the mouth and serves as a passageway for BOTH AIR AND FOOD. When food is swallowed, a Flap of Cartilage, called the EPIGLOTTIS, presses down and covers the opening to the air passage (ever have food go "Down the Wrong Way"?).
8. From the Pharynx, the air moves through the LARYNX, the upper end of the Trachea, and into the TRACHEA (WINDPIPE), WHICH LEADS DIRECTLY TO THE LUNGS.
9. These passageways provide a direct connection between the outside air and some of the most Delicate Tissue in the body.
10. These passageways must filter out dust, dirt, smoke, bacteria, and a variety of other contaminants found in air.
11. THE FIRST FILTERING IS DONE IN THE NOSE. THE NOSE WILL DO THREE THINGS TO THE AIR WE BREATHE IN:
A. FILTER THE AIR
B. WARM THE AIR
C. PROVIDE MOISTURE (WATER VAPOR OR HUMIDITY) TO THE AIR.
12. As air passes through the nasal cavities it is warmed and humidified, so that air that reaches the lungs is warmed and moist.
13. The Nasal Airways are lined with Cilia and kept moist by Mucous secretions. The combination of Cilia and Mucous helps to filter out solid particles from the air an Warm and Moisten the air, which prevents damage to the delicate tissues that form the Respiratory System.
14. The moisture in the nose helps to heat and humidify the air, Increasing the amount of Water Vapor the air entering the Lungs contains.
15. This helps to keep the air entering the nose from Drying out the Lungs and other parts of our Respiratory System.
16. When air enters the Respiratory System through the Mouth, much less filtering is done. It is generally better to take in air through the Nose.
17. At the top of the Trachea is the LARYNX (Voice Box or Adam's Apple). Inside, and stretched across the Larynx are two highly elastic folds of tissue (Ligaments) called the VOCAL CORDS. Air rushing through the voice box causes the vocal cords to vibrate producing sound waves.
18. From the Larynx, the Warmed, Filtered, and Moistened air passes downward into the Thoracic Cavity through the Trachea.
19. The Walls of the Trachea are made up of C-Shaped rings of tough flexible Cartilage. These rings of cartilage Protect the Trachea, make it Flexible, and keep it from Collapsing or over expanding.
20. The Cells that line the trachea produce Mucus; the mucus helps to capture things still in the air (Dust and Microorganisms), and is swept out of the air passageway by tiny Cilia into the Digestion System.
21. Within the Thoracic Cavity, the Trachea divides into TWO Branches, the Right and Left BRONCHI. Each BRONCHUS enters the LUNG on its respective side. The Lungs are the Site of Gas Exchange Between the Atmosphere and the Blood. The Right Lung has Three Divisions or Lobes, and is slightly larger than the Two Lobed Left Lung. The Lungs are inside the Thoracic Cavity, bounded by the Rib Cage and Diaphragm. Lining the entire cavity and encasing the Lungs are PLEURA MEMBRANES that secrete a Mucus that decreases friction from the movement of the Lungs during Breathing. (Figure 47-16)
22. The further branching of the BRONCHIAL TUBES is often called the BRONCHIAL TREE.
23. Imagine the Trachea as the trunk of an upside down tree with extensive branches that become smaller and smaller; these smaller branches are the BRONCHIOLES.
24. Both Bronchi and Bronchioles contain Smooth Muscle Tissue in their walls. This muscle tissue controls the SIZE of the Air Passage.
25. The Bronchioles continue to subdivide until they finally end in Clusters of Tiny Hallow AIR SACS called ALVEOLI. Groups of Alveoli look like bunches of grapes. ALL EXCHANGE OF GASES IN THE LUNGS OCCURS IN THE ALVEOLI. (Figure 46-16 AND 17)
26. The Alveoli consist of thin, flexible membranes that contain an extensive network of Capillaries. The Membranes separate a gas from liquid. The gas is the air we take in through our Respiratory System, and the liquid is BLOOD.
27. The Functional Unit of the LUNGS is the ALVEOLI; it is here that the Circulatory and Respiratory Systems come together, for the purpose of gas exchange. ALL EXCHANGE OF GASES IN THE LUNGS OCCURS IN THE ALVEOLI. Each Lung contains nearly 300 Million ALVEOLI and has a total surface area about 40 times the surface area of your skin.
MECHANISM OF BREATHING (Figure 46-18)
1. BREATHING IS THE ENTRANCE AND EXIT OF AIR INTO AND FROM THE LUNGS.
2. VENTILATION is the term for the movement of air to and from the Alveoli.
3. Every single time you take a breath, or move air in and out of your lungs, TWO major actions take place.
A. INHALATION - also called INSPIRATION, air is pulled into the LUNGS. (Figure 46-18 (a))
B. EXHALATION - also called EXPIRATION, air is pushed out of the Lungs. (Figure 46-18 (b))
4. These Two actions deliver oxygen to the Alveoli, and remove Carbon dioxide.
5. The Continuous Cycles of Inhalation and Exhalation are known as BREATHING. Most of us Breathe 10 to 15 times per minute.
6. The lungs are not directly attached to any Muscle, SO THEY CANNOT BE EXPANDED OR CONTRACTED.
7. Inhalation and Exhalation are actually produced by Movements of the LARGE FLAT MUSCLE CALLED THE DIAPHRAGM AND THE INTERCOSTAL (BETWEEN THE RIBS) MUSCLES.
8. The DIAPHRAGM is located along the BOTTOM of the RIB CAGE and SEPARATES THE THORACIC CAVITY FROM THE ABDOMINAL CAVITY.
9. Before Inhalation the Diaphragm is curved UPWARD into the chest. During Inhalation, the Diaphragm CONTRACTS and Moves DOWN, CAUSING THE VOLUME OF THE THORACIC CAVITY TO INCREASE.
10. When the Diaphragm moves Down, the Volume of the Thoracic Cavity INCREASES and the AIR PRESSURE INSIDE IT DECREASES.
11. The Air OUTSIDE is still at ATMOSPHERIC PRESSURE, TO EQUALIZE THE PRESSURE INSIDE AND OUT, THE AIR RUSHES THROUGH THE TRACHEA INTO THE LUNGS - INHALED. (Figure 46-18 (a))
12. When the Diaphragm relaxes, it returns to its curved position. THIS ACTION CAUSES THE VOLUME OF AIR IN THE THORACIC CAVITY TO DECREASE.
13. As the Volume Decreases, the pressure in the Thoracic Cavity outside the lungs increases. This INCREASE the Air pressure and causes the LUNGS to DECREASE IN SIZE.
14. The air inside the Lungs is Pushed Out or EXHALED. (Figure 46-18 (b))
15. We generally breathe with the Diaphragm and Intercostal Muscles (REST), under extreme conditions we can use other muscles in our Thoracic Cavity to breathe (ACTIVITY).
16. Since our Breathing is based on Atmospheric Pressure, the Lungs can only Work Properly if the space around them is SEALED.
17. When the Diaphragm contracts, the expanded volume in the Thoracic Cavity quickly fills as air rushes into the Lungs. If there is a small hole in the Thoracic Cavity, the Respiratory System will NOT Work.
18. Air will rush into the cavity through the hole, upset the pressure relationship, and possibly cause the collapse of a lung.
GAS EXCHANGE AND TRANSPORT (Figure 46-17)
1. Chemical Analysis of the gases that are inhaled and exhaled:
GAS INHALED -vs- EXHALED
O2 20.71% 14.6%
CO2 0.04% 4.0%
H2O 1.25% 5.9%
2. THREE IMPORTANT THINGS HAPPEN TO THE AIR WE INHALE:
A. OXYGEN IS REMOVED
B. CARBON DIOXIDE IS ADDED
C. WATER VAPOR IS ADDED.
3. This occurs in the ALVEOLI in the LUNGS; Our Lungs consist of nearly 300 million ALVEOLI where gas exchange occurs (THE EXCHANGE OF CARBON DIOXIDE AND OXYGEN).
4. Blood flowing from the HEART enters Capillaries surrounding each Alveolus and spreads around the Alveolus. This Blood contains a LARGE AMOUNT of CO2 and Very Little O2.
5. The Concentration of the gases in the blood and the alveolus are not Equal (Concentration Gradient). This causes the DIFFUSION of CO2 from the Blood to the Alveolus and the DIFFUSION of O2 from the Alveolus into the Blood. (Figure 46-17)
6. The Blood leaving the alveolus has nearly tripled the total amount of oxygen it originally carried.
7. TWO SPECIAL MOLECULES HELP THIS PROCESS OF GAS EXCHANGE WORK EFFECTIVELY:
A. MACROMOLECULES - Soaplike, consisting of phospholipid and protein, they coat the inner surface of the Alveolus.
B. HEMOGLOBIN - An Oxygen Carrying Molecule that is a component of Blood. Hemoglobin is a red colored protein found in red blood cells. Each Hemoglobin molecule has FOUR SITES to which O2 atoms can bind. Thus, One Hemoglobin molecule can carry up to Four molecules of oxygen. Most of the oxygen - 97 percent - moves into the red blood cells, where it combines with Hemoglobin.
REGULATION OF BREATHING
1. Breathing is such an important function that your NERVOUS SYSTEM will NOT let you have complete control of it.
2. TEST IT! HOW LONG CAN YOU HOLD YOUR BREATH!
3. BREATHING IS AN INVOLUNTARY ACTION UNDER CONTROL OF THE MEDULLA OBLONGATA IN THE LOWER PART OF THE BRAIN. Sensory neurons in this region control MOTOR NEURONS IN THE SPINAL CORD.
4. Although YOU can consciously controlled breathing to a limited extent-such as holding your breath-it CANNOT BE CONSCIOUSLY SUPPRESSED. THE NEED TO SUPPLY OXYGEN TO OUR CELLS AND REMOVE CARBON DIOXIDE IS A POWERFUL ONE.
5. You can only hold your breath until you lose Consciousness - Then the Brain takes control and normal breathing resumes.
6. CARBON DIOXIDE AND HYDROGEN IONS (BLOOD ACIDITY) ARE THE PRIMARY STIMULI THAT CAUSES US TO BREATHE.
7. The Nervous System must have a way to determine whether enough O2 is getting into the Blood.
8. Two special sets of SENSORY NEURONS constantly check the levels of gases in the Blood. THESE SPECIAL SENSORY RECEPTORS ARE SENSITIVE TO THE LEVELS OF GASES IN THE BLOOD, ESPECIALLY THE LEVEL OF CARBON DIOXIDE.
9. One set is located IN the CAROTID ARTERIES in the NECK, which Carry Blood to the BRAIN.
10. The other set is located NEAR the AORTA, the large ARTERY that Carries Blood FROM THE HEART TO THE REST OF THE BODY.
11. When Carbon Dioxide Dissolves in the blood, it forms AN ACID KNOWN AS CARBONIC ACID. CARBONIC ACID IS SO UNSTABLE THAT IT IMMEDIATELY BREAKS DOWN INTO HYDROGEN ION (H+) AND A BICARBONATE IONS (HCO3-).
CO2 + H20 H2CO3
H2CO3 H+ + HCO3-
12. Most carbon dioxide travels in the blood as Bicarbonate Ions. When the Blood reaches the Lungs, the series of reactions is reversed. The Bicarbonate ions combine with a proton to form Carbonic Acid, which in turn forms Carbon Dioxide and Water. The carbon dioxide Diffuses out of the capillaries into the Alveoli and is exhaled into the atmosphere.
13. The Hydrogen Ions change the ACIDITY (pH) of the Blood, and it is this change in Acidity the special sensory cells respond to.
14. The Lungs of an average person have a total air capacity of about 6.0 liters. Only about 0.6 liter is exchange during Normal Breathing. This is all the air we need at rest.
15. During Exercise, deep breathing forces out much more of the total lung capacity. As much as 4.5 liters of air can be Inhaled or Exhaled with effort.
16. The MAXIMUM Amount of Air that can be moved into and out of the Respiratory System is Known AS THE VITAL CAPACITY OF THE LUNGS.
17. The Vital Capacity is ALWAYS 1 to 1.5 liters LESS than the Total Capacity because the Lungs Cannot be completely Deflated without serious damage.
18. The extra capacity allows us to exercise for long periods of time. Rather than Breathing 12 times a minute, as most of us do at REST, a Runner may Breath as often as 50 times a minute.
19. For rapid and deep breathing during vigorous exercise you use the muscles of the rib cage.
Type of indoor airflow & standard that related to Indoor air quality,
From doc….
Ending: more than 4 simulation …mapping
References
Boehm, B.: Software Risk Management. IEEE Computer Society Press. (1989)
Boehm, B.: A spiral model of software development and enhancement. IEEE Com-
puters. (1988) 61-62
Cairo, O., Barreiro, J., Solsona, F., Software Methodologies at Risky, WWW home page: http://cannes.divcom.itam.mx/Osvaldo, Instituto Tecnologico Autonomo de Mexico (ITAM), Universidad Nacional Autonoma de Mexico (UNAM), Mexico
Knowledge Acquisition, Modeling and Management: 11th European Workshop, EKAW '99, Dagstuhl Castle, Germany, May 1999. Proceedings
Peng, S.-H. and L. Davidson. Performance evaluation of a displacement ventilation
system for improving indoor air quality: a numerical study. in 8th International
Conference on Indoor Air Quality and Climate. 1999. Edinburgh, Scotland.
Di Tommaso, R.M., E. Nino, and G.V. Fracastoro, Influence of the boundary thermal
conditions on the air change efficiency indexes. Indoor Air, 1999. 9: p. 63-69.
Zhang, Y., X. Wang, G.L. Riskowski, and L.L. Christianson, Quantifying ventilation
effectiveness for air quality control. Transactions of the American Society of
Agricultural and Biological Engineers (ASABE), 2001. 44(2): p. 385-390.
Linden, P.F., The fluid mechanics of natural ventilation. Annu. Rev. Fluid Mech., 1999.
31: p. 201-238.
The main factors affecting contaminants
Characteristics of indoor air flows
Aerosol as one kind of Particulate Matter and contaminants,
The respiratory system
Type of indoor airflow & standard that related to Indoor air quality,
Ending: more than 4 simulation …
http://continuousimprovement.blogsome.com
http://Life4aaK.blogspot.com
http://godoproduction.blogspot.com
A typical dictionary defines risk as the possibility of loss or injury. It implies that risk has two main components: the probability of some event occurring and the negative consequence if it occurs. Thus, to analyze risk we should be able to estimate these two factors. Boehm [1] translated this defnition into the
fundamental concept of risk management: the risk exposure, sometimes called risk impact.
Fundamental concept of risk (Cairo., et al., 1999)
A typical dictionary defines risk as the possibility of loss or injury. It implies that risk has two main components: the probability of some event occurring and the negative consequence if it occurs. Thus, to analyze risk we should be able to estimate these two factors. Boehm (1989) translated this definition into the fundamental concept of risk management: the risk exposure, sometimes called risk impact.
Where RE means risk exposure, P(UO) expresses the probability of an unsatisfactory outcome, and L(UO) means the loss to the parties affected if the outcome is unsatisfactory.
Usually the perception of risk is higher for those items over which one have little or no control. However, the importance of the risk factors might be considered as some combination of risk frequency (that is, how likely it is that the risk will occur) and risk impact (such as, how serious a threat the risk represents if it does occur). In considering risks you must also consider their perceived level of control. This represents the degree to which the project manager perceived that their actions could prevent the risk from occurring. Most of the probable risks or threats to projects can be reduced or avoided using an appropriate methodology. It can also be complemented with approximative methods, which can provide enough information to support risk management decisions.
Risk-reduction is a fundamental part of project management in software and knowledge engineering. Software risk management is important because it helps people to avoid disasters, rework, and overkill, it also stimulates win-win situations on software projects (Boehm, 1989).
We should be aware that by avoiding or reducing the most significant risks, managers make more informed decisions, we obtain better outcomes, and hence the project will have a higher probability of success.
Boehm (1988) suggests to use a software risk management plan, which consists of five steps:
• Identify the project's top risk items.
• Present a plan for resolving each risk item.
• Update list of top risk items, plan, and results monthly.
• Highlight risk-item status in monthly project reviews.
• Initiate appropriate corrective actions.
Successful management of a project leads to control. Control leads to quality. Quality leads to satisfied customers. And we know customers are the final arbiters of a product or service.
The main factors affecting contaminants OK
Characteristics of indoor air flows:
Gant., et al.; 2006 state a number of parameters which can be used to characterize the dispersion of a contaminant inside a room, i. e.:
1. Fresh Air/ Contaminant Distribution:
Contaminant Concentration, Local Mean Age of Air, Purging Effectiveness of Inlets, Local Specific Contaminant-Accumulating Index, Air Change Efficiency, Ventilation Effectiveness Factor, Relative Ventilation Efficiency.
2. Stability and Bouyancy of the Room Air:
Reynold Number, Rayleigh Number, Grashof Number, Froude Number, Richardson Number, Flux Richardson Number, Bouyancy Flux.
3. Temperature Distribution:
Air Diffusion Performance Index, Effective Draft Temperature.
4. Supply Air Conditions:
Purging Effectiveness of Inlet, Reynold Number, Froude Number, Archimedes Number.
Due to overlap between these subjects, some parameters appear more than once. Some parameters characterize directly the observed pattern of contaminant distribution whilst others characterize flow features, such as stability. Flow parameters such as the ‘mean age of air’ are difficult but not impossible to calculate experimentally. They are used mainly as a tool to help interpret data from numerical simulations of contaminant dispersion. For discussions on how these parameters are used to assess compliance with standards on room air quality, see Peng & Davidson (1999) or the ASHRAE Guides (2003).
Clearly the simplest indicator of contaminant distribution in a room is the contaminant concentration, i.e. the mass of contaminant per unit volume of air (measured in kg/m3). Contaminant concentration is sometimes expressed in terms of parts per million (ppm), or parts per billion, trillion etc. This can be based on either the mass fraction or the volume fraction.
Local Mean Age of Air is commonly used to evaluate the performance of a ventilation system and indoor air quality. The precise meaning of the local mean age is defined in Di Tommaso et al.; (1999) as follows: “the average time it takes for air to travel from the inlet to any point P in the room”.
The purging effectiveness of an inlet is a quantity that can be used to identify the relative performance of each inlet in a room where there are multiple inlets.
Peng et al.; (1999) classify the various measures used to characterize ventilation performance into three groups: measures of ventilation air-diffusing efficiency which indicate the ability to provide fresh air to occupants, ventilation effectiveness which indicate the ability to remove contaminants from a ventilated space and specific ventilation effectiveness which deals with specific situations.
Air Change Efficiency is a measure of how effectively the air present in a room is replaced by fresh air from the ventilation system (Di Tommaso et al.; 1999). It is the ratio of the room mean age that would exist if the air in the room were completely mixed to the average time of replacement of the room.
The Ventilation Effectiveness Faction (VEF) appears to be ASHRAE’s preferred method for characterizing indoor air quality and is based on the work of Zhang et al. (2001).
The relative ventilation efficiency is the ratio of the local mean age that would exist if the air in the room were completely mixed to the local mean age that is actually measured at a point.
Air Diffusion Performance Index (ADPI) is primarily a measure of occupant comfort rather than an indicator of contaminant concentrations. It expresses the percentage of locations in an occupied zone that meet air movement and temperature specifications for comfort.
The temperature effectiveness is similar in concept to ventilation effectiveness and reflects the ability of a ventilation system to remove heat.
The effective draft temperature, θ, indicates the feeling of coolness due to air motion:
where Tx and Tc are the local air-stream and average room dry-bulb temperatures (in ºC or K), Vx is the local air-stream centre-line velocity (in m/s) and θ is measured in K.
The Reynolds number, Re, expresses the ratio of the inertial forces to viscous forces:
where U and L are characteristic velocity and length scales of the flow and ν is the kinematic
viscosity.
Natural convection flows are often characterized using the Rayleigh Number, Ra, given by:
where g is the acceleration due to gravity (g = 9.81 m/s2), β the coefficient of thermal expansion (where for an ideal gas, β = T 1 ), ∆T the temperature difference, L the length scale (e.g. the height of the heated surface), υ the kinematic viscosity and α the thermal diffusivity (α = k /ρCp).
The Grashof number, Gr, is equivalent to the Rayleigh number divided by the Prandtl number:
where g is the acceleration due to gravity, β the coefficient of thermal expansion ∆T temperature difference, L the length scale and υ the kinematic viscosity.
The following form of the Froude number is used by Linden [6] to characterize flow through corridors and doorways and in combined displacement and wind ventilation cases.
where U and L are characteristic velocity and length scales, respectively, and g the acceleration due to gravity.
The Richardson number, Ri, characterizes the importance of buoyancy. It is calculated from:
where ∆ ρ is the density difference that occurs over a typical (usually vertical) length scale, L, in a flow of velocity, U.
The flux Richardson number, Rif, is used to characterize the stabilizing effect of stratification on turbulence:
where Pkb and Pk are the turbulence production due to buoyancy and shear respectively
The buoyancy flux, B, is calculated from:
Linden (1999) uses this to characterize buoyancy driven flows, where W is the heat flux, β = 1/ T is the coefficient of expansion and cp is the specific heat capacity at constant pressure.
The conditions of the supplied air are often characterized by the discharge Archimedes number, Ar, which expresses the ratio of the buoyancy forces to momentum forces or the strength of natural convection to forced convection:
where T ∆ is the temperature difference between supply and exhaust, U is the initial velocity of the discharged air, g is the acceleration due to gravity and L is the length scale of the supply terminal (i.e. diffuser or grille).
Aerosol as one kind of Particulate Matter and contaminants,
From pre-proposal….
The respiratory system (http://www.sirinet.net/~jgjohnso/respiratory.html accesed 01st March 2007)
CHAPTER 46, SECTION 3
THE RESPIRATORY SYSTEM
You have read how the blood transports oxygen from the lungs to cells and carries carbon dioxide from the cells to the lungs. It is the function of the respiratory system to transport gases to and from the circulatory system. The respiratory system involves both External and Internal respiration.
External Respiration is the exchange of gases between the atmosphere and the blood. Internal Respiration is the exchange of gases between the blood and the cells of the body. Cellular Respiration or Aerobic Respiration involves the use of oxygen to break down glucose in the cell. We will examine the structures and mechanisms that carry oxygen to the cells for use in aerobic respiration and that eliminate the carbon dioxide that is produced by the same process.
OBJECTIVES:
1. Differentiate external respiration from internal respiration.
2. Trace the path of air from the atmosphere to the bloodstream.
3. Describe how gases are exchanged in the lungs and transported in the bloodstream.
4. Summarize the skeletal and muscular changes that occur during breathing.
5. Describe how the rate of breathing is controlled.
RESPIRATION
1. THE MAIN JOB OF THE RESPIRATORY SYSTEM IS TO GET OXYGEN INTO THE BODY AND WASTE GASES OUT OF THE BODY. IT IS THE FUNCTION OF THE RESPIRATORY SYSTEM TO TRANSPORT GASES TO AND FROM THE CIRCULATORY SYSTEM.
2. Respiration is a vital function of all living organisms.
3. Respiration occurs at TWO DIFFERENT LEVELS:
A. The level of the CELL. In the Mitochondria of Eukaryotic Cells, Aerobic Respiration requires OXYGEN to break down Glucose, releases CARBON DIOXIDE, and produces large amounts of ATP. THIS LEVEL OF RESPIRATION IS CALLED INTERNAL RESPIRATION OR CELLULAR RESPIRATION.
B. The level of the ORGANISM. An organism must get oxygen into its CELLS and CARBON DIOXIDE back out. THIS LEVEL OF RESPIRATION IS CALLED EXTERNAL RESPIRATION BECAUSE THE EXCHANGE OF GASES TAKES PLACE WITH THE EXTERNAL ENVIRONMENT. THE EXCHANGE OF GASES, OXYGEN (O2) AND CARBON DIOXIDE (CO2) BETWEEN AIR AND BLOOD.
4. EXTERNAL RESPIRATION INVOLVES THE RESPIRATORY SYSTEM.
5. A RESPIRATORY SYSTEM IS A GROUP OF ORGANS WORKING TOGETHER TO BRING ABOUT THE EXCHANGE OF OXYGEN AND CARBON DIOXIDE WITH THE ENVIRONMENT.
6. A single-celled organism living in water (DIFFUSION) gets its oxygen directly from its surroundings (the water). The oxygen easily diffuses across the Cell Membrane. Carbon dioxide also diffuses across the Cell Membrane; thus single-celled organisms do not need a Respiratory System.
7. In MULTICELLULAR ORGANISMS, Each Cell consumes Oxygen and produces Carbon dioxide. Large Multicellular organism must have a Respiratory System to ensure the effective exchange of gasses with the Atmosphere quickly and efficiently to survive.
8. THIS OCCURS EVERY TIME AN ORGANISM TAKES A BREATH.
9. The atmosphere of planet Earth is approximately 78% Nitrogen and 21% Oxygen. The remaining 1% is made up of Carbon Dioxide, Water Vapor, and other trace gases.
10. Humans are Air Breathers; our Respiratory System has adapted to these concentrations of gases in the Atmosphere. If the amount of Oxygen FALLS much below 15 %, our Respiratory System will be UNABLE to provide enough Oxygen to support cellular respiration.
THE PASSAGE OF AIR AND THE RESPIRATORY STRUCTURES (Figure 46-16)
1. THE HUMAN RESPIRATORY SYSTEM CONSIST OF THE NOSE, NASAL CAVITY, PHARYNX, LARYNX, TRACHEA, SMALLER CONDUCTING PASSAGEWAYS (BRONCHI AND BRONCHIOLES), AND LUNGS.
2. The Respiratory System may be divided into the UPPER RESPIRATORY TRACT AND THE LOWER RESPIRATORY TRACT.
3. THE UPPER RESPIRATORY TRACT CONSISTS OF THE PARTS OUTSIDE THE THORACIC (CHEST) CAVITY: THE AIR PASSAGES OF THE NOSE, NASAL CAVITIES, PHARYNX (WINDPIPE), LARYNX (VOICE BOX), AND UPPER TRACHEA.
4. THE LOWER RESPIRATORY TRACT CONSISTS OF THE PARTS FOUND IN THE THORACIC (CHEST) CAVITY: THE LOWER TRACHEA AND THE LUNGS THEMSELVES.
5. Air ENTERS the Respiratory System through the Mouth or Nose.
6. Air entering the Nose passes into the NASAL CAVITY. The Nasal Cavity is richly supplied with arteries, veins, and capillaries, which bring nutrients and water to its cells.
7. As air pushes back from the Nasal Cavity, it enters the PHARYNX. The Pharynx is located in the back of the mouth and serves as a passageway for BOTH AIR AND FOOD. When food is swallowed, a Flap of Cartilage, called the EPIGLOTTIS, presses down and covers the opening to the air passage (ever have food go "Down the Wrong Way"?).
8. From the Pharynx, the air moves through the LARYNX, the upper end of the Trachea, and into the TRACHEA (WINDPIPE), WHICH LEADS DIRECTLY TO THE LUNGS.
9. These passageways provide a direct connection between the outside air and some of the most Delicate Tissue in the body.
10. These passageways must filter out dust, dirt, smoke, bacteria, and a variety of other contaminants found in air.
11. THE FIRST FILTERING IS DONE IN THE NOSE. THE NOSE WILL DO THREE THINGS TO THE AIR WE BREATHE IN:
A. FILTER THE AIR
B. WARM THE AIR
C. PROVIDE MOISTURE (WATER VAPOR OR HUMIDITY) TO THE AIR.
12. As air passes through the nasal cavities it is warmed and humidified, so that air that reaches the lungs is warmed and moist.
13. The Nasal Airways are lined with Cilia and kept moist by Mucous secretions. The combination of Cilia and Mucous helps to filter out solid particles from the air an Warm and Moisten the air, which prevents damage to the delicate tissues that form the Respiratory System.
14. The moisture in the nose helps to heat and humidify the air, Increasing the amount of Water Vapor the air entering the Lungs contains.
15. This helps to keep the air entering the nose from Drying out the Lungs and other parts of our Respiratory System.
16. When air enters the Respiratory System through the Mouth, much less filtering is done. It is generally better to take in air through the Nose.
17. At the top of the Trachea is the LARYNX (Voice Box or Adam's Apple). Inside, and stretched across the Larynx are two highly elastic folds of tissue (Ligaments) called the VOCAL CORDS. Air rushing through the voice box causes the vocal cords to vibrate producing sound waves.
18. From the Larynx, the Warmed, Filtered, and Moistened air passes downward into the Thoracic Cavity through the Trachea.
19. The Walls of the Trachea are made up of C-Shaped rings of tough flexible Cartilage. These rings of cartilage Protect the Trachea, make it Flexible, and keep it from Collapsing or over expanding.
20. The Cells that line the trachea produce Mucus; the mucus helps to capture things still in the air (Dust and Microorganisms), and is swept out of the air passageway by tiny Cilia into the Digestion System.
21. Within the Thoracic Cavity, the Trachea divides into TWO Branches, the Right and Left BRONCHI. Each BRONCHUS enters the LUNG on its respective side. The Lungs are the Site of Gas Exchange Between the Atmosphere and the Blood. The Right Lung has Three Divisions or Lobes, and is slightly larger than the Two Lobed Left Lung. The Lungs are inside the Thoracic Cavity, bounded by the Rib Cage and Diaphragm. Lining the entire cavity and encasing the Lungs are PLEURA MEMBRANES that secrete a Mucus that decreases friction from the movement of the Lungs during Breathing. (Figure 47-16)
22. The further branching of the BRONCHIAL TUBES is often called the BRONCHIAL TREE.
23. Imagine the Trachea as the trunk of an upside down tree with extensive branches that become smaller and smaller; these smaller branches are the BRONCHIOLES.
24. Both Bronchi and Bronchioles contain Smooth Muscle Tissue in their walls. This muscle tissue controls the SIZE of the Air Passage.
25. The Bronchioles continue to subdivide until they finally end in Clusters of Tiny Hallow AIR SACS called ALVEOLI. Groups of Alveoli look like bunches of grapes. ALL EXCHANGE OF GASES IN THE LUNGS OCCURS IN THE ALVEOLI. (Figure 46-16 AND 17)
26. The Alveoli consist of thin, flexible membranes that contain an extensive network of Capillaries. The Membranes separate a gas from liquid. The gas is the air we take in through our Respiratory System, and the liquid is BLOOD.
27. The Functional Unit of the LUNGS is the ALVEOLI; it is here that the Circulatory and Respiratory Systems come together, for the purpose of gas exchange. ALL EXCHANGE OF GASES IN THE LUNGS OCCURS IN THE ALVEOLI. Each Lung contains nearly 300 Million ALVEOLI and has a total surface area about 40 times the surface area of your skin.
MECHANISM OF BREATHING (Figure 46-18)
1. BREATHING IS THE ENTRANCE AND EXIT OF AIR INTO AND FROM THE LUNGS.
2. VENTILATION is the term for the movement of air to and from the Alveoli.
3. Every single time you take a breath, or move air in and out of your lungs, TWO major actions take place.
A. INHALATION - also called INSPIRATION, air is pulled into the LUNGS. (Figure 46-18 (a))
B. EXHALATION - also called EXPIRATION, air is pushed out of the Lungs. (Figure 46-18 (b))
4. These Two actions deliver oxygen to the Alveoli, and remove Carbon dioxide.
5. The Continuous Cycles of Inhalation and Exhalation are known as BREATHING. Most of us Breathe 10 to 15 times per minute.
6. The lungs are not directly attached to any Muscle, SO THEY CANNOT BE EXPANDED OR CONTRACTED.
7. Inhalation and Exhalation are actually produced by Movements of the LARGE FLAT MUSCLE CALLED THE DIAPHRAGM AND THE INTERCOSTAL (BETWEEN THE RIBS) MUSCLES.
8. The DIAPHRAGM is located along the BOTTOM of the RIB CAGE and SEPARATES THE THORACIC CAVITY FROM THE ABDOMINAL CAVITY.
9. Before Inhalation the Diaphragm is curved UPWARD into the chest. During Inhalation, the Diaphragm CONTRACTS and Moves DOWN, CAUSING THE VOLUME OF THE THORACIC CAVITY TO INCREASE.
10. When the Diaphragm moves Down, the Volume of the Thoracic Cavity INCREASES and the AIR PRESSURE INSIDE IT DECREASES.
11. The Air OUTSIDE is still at ATMOSPHERIC PRESSURE, TO EQUALIZE THE PRESSURE INSIDE AND OUT, THE AIR RUSHES THROUGH THE TRACHEA INTO THE LUNGS - INHALED. (Figure 46-18 (a))
12. When the Diaphragm relaxes, it returns to its curved position. THIS ACTION CAUSES THE VOLUME OF AIR IN THE THORACIC CAVITY TO DECREASE.
13. As the Volume Decreases, the pressure in the Thoracic Cavity outside the lungs increases. This INCREASE the Air pressure and causes the LUNGS to DECREASE IN SIZE.
14. The air inside the Lungs is Pushed Out or EXHALED. (Figure 46-18 (b))
15. We generally breathe with the Diaphragm and Intercostal Muscles (REST), under extreme conditions we can use other muscles in our Thoracic Cavity to breathe (ACTIVITY).
16. Since our Breathing is based on Atmospheric Pressure, the Lungs can only Work Properly if the space around them is SEALED.
17. When the Diaphragm contracts, the expanded volume in the Thoracic Cavity quickly fills as air rushes into the Lungs. If there is a small hole in the Thoracic Cavity, the Respiratory System will NOT Work.
18. Air will rush into the cavity through the hole, upset the pressure relationship, and possibly cause the collapse of a lung.
GAS EXCHANGE AND TRANSPORT (Figure 46-17)
1. Chemical Analysis of the gases that are inhaled and exhaled:
GAS INHALED -vs- EXHALED
O2 20.71% 14.6%
CO2 0.04% 4.0%
H2O 1.25% 5.9%
2. THREE IMPORTANT THINGS HAPPEN TO THE AIR WE INHALE:
A. OXYGEN IS REMOVED
B. CARBON DIOXIDE IS ADDED
C. WATER VAPOR IS ADDED.
3. This occurs in the ALVEOLI in the LUNGS; Our Lungs consist of nearly 300 million ALVEOLI where gas exchange occurs (THE EXCHANGE OF CARBON DIOXIDE AND OXYGEN).
4. Blood flowing from the HEART enters Capillaries surrounding each Alveolus and spreads around the Alveolus. This Blood contains a LARGE AMOUNT of CO2 and Very Little O2.
5. The Concentration of the gases in the blood and the alveolus are not Equal (Concentration Gradient). This causes the DIFFUSION of CO2 from the Blood to the Alveolus and the DIFFUSION of O2 from the Alveolus into the Blood. (Figure 46-17)
6. The Blood leaving the alveolus has nearly tripled the total amount of oxygen it originally carried.
7. TWO SPECIAL MOLECULES HELP THIS PROCESS OF GAS EXCHANGE WORK EFFECTIVELY:
A. MACROMOLECULES - Soaplike, consisting of phospholipid and protein, they coat the inner surface of the Alveolus.
B. HEMOGLOBIN - An Oxygen Carrying Molecule that is a component of Blood. Hemoglobin is a red colored protein found in red blood cells. Each Hemoglobin molecule has FOUR SITES to which O2 atoms can bind. Thus, One Hemoglobin molecule can carry up to Four molecules of oxygen. Most of the oxygen - 97 percent - moves into the red blood cells, where it combines with Hemoglobin.
REGULATION OF BREATHING
1. Breathing is such an important function that your NERVOUS SYSTEM will NOT let you have complete control of it.
2. TEST IT! HOW LONG CAN YOU HOLD YOUR BREATH!
3. BREATHING IS AN INVOLUNTARY ACTION UNDER CONTROL OF THE MEDULLA OBLONGATA IN THE LOWER PART OF THE BRAIN. Sensory neurons in this region control MOTOR NEURONS IN THE SPINAL CORD.
4. Although YOU can consciously controlled breathing to a limited extent-such as holding your breath-it CANNOT BE CONSCIOUSLY SUPPRESSED. THE NEED TO SUPPLY OXYGEN TO OUR CELLS AND REMOVE CARBON DIOXIDE IS A POWERFUL ONE.
5. You can only hold your breath until you lose Consciousness - Then the Brain takes control and normal breathing resumes.
6. CARBON DIOXIDE AND HYDROGEN IONS (BLOOD ACIDITY) ARE THE PRIMARY STIMULI THAT CAUSES US TO BREATHE.
7. The Nervous System must have a way to determine whether enough O2 is getting into the Blood.
8. Two special sets of SENSORY NEURONS constantly check the levels of gases in the Blood. THESE SPECIAL SENSORY RECEPTORS ARE SENSITIVE TO THE LEVELS OF GASES IN THE BLOOD, ESPECIALLY THE LEVEL OF CARBON DIOXIDE.
9. One set is located IN the CAROTID ARTERIES in the NECK, which Carry Blood to the BRAIN.
10. The other set is located NEAR the AORTA, the large ARTERY that Carries Blood FROM THE HEART TO THE REST OF THE BODY.
11. When Carbon Dioxide Dissolves in the blood, it forms AN ACID KNOWN AS CARBONIC ACID. CARBONIC ACID IS SO UNSTABLE THAT IT IMMEDIATELY BREAKS DOWN INTO HYDROGEN ION (H+) AND A BICARBONATE IONS (HCO3-).
CO2 + H20 H2CO3
H2CO3 H+ + HCO3-
12. Most carbon dioxide travels in the blood as Bicarbonate Ions. When the Blood reaches the Lungs, the series of reactions is reversed. The Bicarbonate ions combine with a proton to form Carbonic Acid, which in turn forms Carbon Dioxide and Water. The carbon dioxide Diffuses out of the capillaries into the Alveoli and is exhaled into the atmosphere.
13. The Hydrogen Ions change the ACIDITY (pH) of the Blood, and it is this change in Acidity the special sensory cells respond to.
14. The Lungs of an average person have a total air capacity of about 6.0 liters. Only about 0.6 liter is exchange during Normal Breathing. This is all the air we need at rest.
15. During Exercise, deep breathing forces out much more of the total lung capacity. As much as 4.5 liters of air can be Inhaled or Exhaled with effort.
16. The MAXIMUM Amount of Air that can be moved into and out of the Respiratory System is Known AS THE VITAL CAPACITY OF THE LUNGS.
17. The Vital Capacity is ALWAYS 1 to 1.5 liters LESS than the Total Capacity because the Lungs Cannot be completely Deflated without serious damage.
18. The extra capacity allows us to exercise for long periods of time. Rather than Breathing 12 times a minute, as most of us do at REST, a Runner may Breath as often as 50 times a minute.
19. For rapid and deep breathing during vigorous exercise you use the muscles of the rib cage.
Type of indoor airflow & standard that related to Indoor air quality,
From doc….
Ending: more than 4 simulation …mapping
References
Boehm, B.: Software Risk Management. IEEE Computer Society Press. (1989)
Boehm, B.: A spiral model of software development and enhancement. IEEE Com-
puters. (1988) 61-62
Cairo, O., Barreiro, J., Solsona, F., Software Methodologies at Risky, WWW home page: http://cannes.divcom.itam.mx/Osvaldo, Instituto Tecnologico Autonomo de Mexico (ITAM), Universidad Nacional Autonoma de Mexico (UNAM), Mexico
Knowledge Acquisition, Modeling and Management: 11th European Workshop, EKAW '99, Dagstuhl Castle, Germany, May 1999. Proceedings
Peng, S.-H. and L. Davidson. Performance evaluation of a displacement ventilation
system for improving indoor air quality: a numerical study. in 8th International
Conference on Indoor Air Quality and Climate. 1999. Edinburgh, Scotland.
Di Tommaso, R.M., E. Nino, and G.V. Fracastoro, Influence of the boundary thermal
conditions on the air change efficiency indexes. Indoor Air, 1999. 9: p. 63-69.
Zhang, Y., X. Wang, G.L. Riskowski, and L.L. Christianson, Quantifying ventilation
effectiveness for air quality control. Transactions of the American Society of
Agricultural and Biological Engineers (ASABE), 2001. 44(2): p. 385-390.
Linden, P.F., The fluid mechanics of natural ventilation. Annu. Rev. Fluid Mech., 1999.
31: p. 201-238.
The main factors affecting contaminants
Characteristics of indoor air flows
Aerosol as one kind of Particulate Matter and contaminants,
The respiratory system
Type of indoor airflow & standard that related to Indoor air quality,
Ending: more than 4 simulation …
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Monday, February 19, 2007
[researcher]tiga model sistem perkuliahan
Module I: 36 units=thesis
Module II: 30 units=core couses + 12 units=thesis == 42 units
Module III: 30 core courses + 6 units = minor-thesis + 6 units = thesis == 42 units
If you receive shocarshipnya,, you in combination: 18 Core + 18 Thesis = 36 Units...
CORE:
3Operations Management
3Managerial Accounting
3Marketing Management
3Organizational Behavior
3Managerial economics
3Business Research
3Financial mgt
3HRM
3MIS
3Strategic Mgt
3Minor-Thesis
Pre-Requisites:
3Priciples of Economics
3Business Law
3Business Finance
3Financial Accounting
Elective:
3Business Intelligence
3Knowledge Management
3Innovation and Change Management
3The Government and Business Sector (The Public Policy Process)
3Small Business Management
3Seminar in HRM
3Human Factors Application in Business
3Seminar in International Business
3Negotiation
3Comparative and International Management
3Foreign Business Studies
3Marine Transport Business
3Electronic Commerce
3Seminar in Marketing Problems
3International Marketing
3Marketing in Service Industries
3Logistics and Supply Chain Management
3International Financila Management
3Securities Investment
3Islamic Banking Management
3Investment Banking
3Derivatives Market
3Special Topics in Business Adm. I
3Special Topics in Business Adm. II
3Special Topics in Business Adm. III
3Special Topics in Business Adm. IV
www.mgt.psu.ac.th or www.psu.ac.th or http://www.international.psu.ac.th/
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Module II: 30 units=core couses + 12 units=thesis == 42 units
Module III: 30 core courses + 6 units = minor-thesis + 6 units = thesis == 42 units
If you receive shocarshipnya,, you in combination: 18 Core + 18 Thesis = 36 Units...
CORE:
3Operations Management
3Managerial Accounting
3Marketing Management
3Organizational Behavior
3Managerial economics
3Business Research
3Financial mgt
3HRM
3MIS
3Strategic Mgt
3Minor-Thesis
Pre-Requisites:
3Priciples of Economics
3Business Law
3Business Finance
3Financial Accounting
Elective:
3Business Intelligence
3Knowledge Management
3Innovation and Change Management
3The Government and Business Sector (The Public Policy Process)
3Small Business Management
3Seminar in HRM
3Human Factors Application in Business
3Seminar in International Business
3Negotiation
3Comparative and International Management
3Foreign Business Studies
3Marine Transport Business
3Electronic Commerce
3Seminar in Marketing Problems
3International Marketing
3Marketing in Service Industries
3Logistics and Supply Chain Management
3International Financila Management
3Securities Investment
3Islamic Banking Management
3Investment Banking
3Derivatives Market
3Special Topics in Business Adm. I
3Special Topics in Business Adm. II
3Special Topics in Business Adm. III
3Special Topics in Business Adm. IV
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[biomasspowerplant]Thailand
Friday, February 16, 2007
Thailand approves seven bioenergy plants as CDM projects
The Thai government has approved the first batch of seven alternative energy projects which would be eligible for carbon credits under the Kyoto Protocol's Clean Development Mechanism. Five biomass and two biogas power plants were approved.They are:
a power plant in Yala that uses waste wood from rubber plantations
a biomass cogeneration plant in Suphan Buri
a rice-husk-fuelled biomass plant in Pichit
a biomass cogeneration plant in Chaiyaphum
a bagasse-fuelled power plant in Khon Kaen (bagasse is the waste generated from pressing sugar juice out of canes)
a municipal waste-to-biogas project in Khon Kaen
a farm based biogas project in RatchaburiThe second batch of eight alternative projects, already approved by the national environment committee, will be submitted for cabinet approval within a month. The Clean Development Mechanism (CDM) is designed to help industrialised countries meet the protocol's greenhouse gas emissions reduction target by investing in clean technology and sustainable development projects, including afforestation, in developing countries. The system is part of an emerging global carbon market (earlier post).The Thai government has announced that it will accept only alternative energy projects, but will ban afforestations, known as carbon sinks, for fear that they would trigger land-use conflicts in the country: biomass :: bioenergy :: biofuels :: energy :: sustainability :: biogas :: bagasse :: rubber wood :: Clean Development Program :: Thailand :: The cabinet also set up a panel, chaired by Khunying Suthawan Sathirathai, to draft regulations regarding the implementation of the CDM projects and study the pros and cons of the scheme. The panel's findings will help the country better deal with the proposed CDM projects.There are currently more than 400 schemes, mostly developed by Japanese and Danish firms, on the committee's list of potential CDM projects and awaiting the cabinet's approval, according to the Office of Natural Resources and Environmental Policy and Planning
posted by Biopact team at 12:33 PM
taken from: http://biopact.com/2007/02/thailand-approves-seven-bioenergy.html
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Thailand approves seven bioenergy plants as CDM projects
The Thai government has approved the first batch of seven alternative energy projects which would be eligible for carbon credits under the Kyoto Protocol's Clean Development Mechanism. Five biomass and two biogas power plants were approved.They are:
a power plant in Yala that uses waste wood from rubber plantations
a biomass cogeneration plant in Suphan Buri
a rice-husk-fuelled biomass plant in Pichit
a biomass cogeneration plant in Chaiyaphum
a bagasse-fuelled power plant in Khon Kaen (bagasse is the waste generated from pressing sugar juice out of canes)
a municipal waste-to-biogas project in Khon Kaen
a farm based biogas project in RatchaburiThe second batch of eight alternative projects, already approved by the national environment committee, will be submitted for cabinet approval within a month. The Clean Development Mechanism (CDM) is designed to help industrialised countries meet the protocol's greenhouse gas emissions reduction target by investing in clean technology and sustainable development projects, including afforestation, in developing countries. The system is part of an emerging global carbon market (earlier post).The Thai government has announced that it will accept only alternative energy projects, but will ban afforestations, known as carbon sinks, for fear that they would trigger land-use conflicts in the country: biomass :: bioenergy :: biofuels :: energy :: sustainability :: biogas :: bagasse :: rubber wood :: Clean Development Program :: Thailand :: The cabinet also set up a panel, chaired by Khunying Suthawan Sathirathai, to draft regulations regarding the implementation of the CDM projects and study the pros and cons of the scheme. The panel's findings will help the country better deal with the proposed CDM projects.There are currently more than 400 schemes, mostly developed by Japanese and Danish firms, on the committee's list of potential CDM projects and awaiting the cabinet's approval, according to the Office of Natural Resources and Environmental Policy and Planning
posted by Biopact team at 12:33 PM
taken from: http://biopact.com/2007/02/thailand-approves-seven-bioenergy.html
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the advantages of the use of biogas
The Advantages of the use of BIOGAS:
REF. 1: [http://www.enerecosrl.com/biodiesel_biogas_en.php] accces 19th February 2007
BIOFUELS are the products of the fermentation and distillation of BIOMASS.
In particular, BIOGAS is produced using the humid part of the citizens’ rubbish or the animal dejections.
In BIOGAS production, the technology now allows to realise simpler and cheaper systems than before.
BIOGAS is generally composed by METHANE and a small percentage of rare gas, so that it can be used for those typical applications of methane.
If it is properly purified, BIOGAS can be even put into the city methane pipelines. However, it doesn’t happen because of the energy necessary for the gas purification.
I. (VERY IMPORTANT) Ecological advantages of the use of BIOGAS:
1.1. in the combustion of BIOFUELS (BIOGAS included) the CO² produced is at the so called “zero balance”, i.e. there’s the emission of the same quantity of CO² that plants and animals have absorbed during their life. Therefore, the environmental impact is much lower in comparison with the traditional fuels.
1.2. because BIOGAS is generally composed by METHANE and a small percentage of rare gas, so that it can be prevented the introduction in the troposphere of the methane naturally emitted by organic biomass in a state of decomposition (animal dejections, organic remains, vegetal biomass, ext.). Indeed methane is one of the most dangerous “greenhouse gases”, therefore combustion is preferred.
II. Other advantages of the use of BIOGAS
REF.2 [www.edu.pe.ca/agriculture/biogas.pdf] Accesed 19th Fberuary 2007
Advantages of biogas include its renewability, abundance, and low cost. Also, it helps with the problem of disposal of organic waste.
DISADVANTAGES of the use of BIOGAS:
1. (main disadvantage) the loss of the organic waste for compost or fertilizer.
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REF. 1: [http://www.enerecosrl.com/biodiesel_biogas_en.php] accces 19th February 2007
BIOFUELS are the products of the fermentation and distillation of BIOMASS.
In particular, BIOGAS is produced using the humid part of the citizens’ rubbish or the animal dejections.
In BIOGAS production, the technology now allows to realise simpler and cheaper systems than before.
BIOGAS is generally composed by METHANE and a small percentage of rare gas, so that it can be used for those typical applications of methane.
If it is properly purified, BIOGAS can be even put into the city methane pipelines. However, it doesn’t happen because of the energy necessary for the gas purification.
I. (VERY IMPORTANT) Ecological advantages of the use of BIOGAS:
1.1. in the combustion of BIOFUELS (BIOGAS included) the CO² produced is at the so called “zero balance”, i.e. there’s the emission of the same quantity of CO² that plants and animals have absorbed during their life. Therefore, the environmental impact is much lower in comparison with the traditional fuels.
1.2. because BIOGAS is generally composed by METHANE and a small percentage of rare gas, so that it can be prevented the introduction in the troposphere of the methane naturally emitted by organic biomass in a state of decomposition (animal dejections, organic remains, vegetal biomass, ext.). Indeed methane is one of the most dangerous “greenhouse gases”, therefore combustion is preferred.
II. Other advantages of the use of BIOGAS
REF.2 [www.edu.pe.ca/agriculture/biogas.pdf] Accesed 19th Fberuary 2007
Advantages of biogas include its renewability, abundance, and low cost. Also, it helps with the problem of disposal of organic waste.
DISADVANTAGES of the use of BIOGAS:
1. (main disadvantage) the loss of the organic waste for compost or fertilizer.
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Tuesday, February 13, 2007
[biogasRENEWABLEenergy]12.02.2007 Class
BIOGAS DESIGN & PERFORMANCE (TECHNOLOGY)
Capacity of BIOGAS PLANT = 100ft^3.
BIOGAS is used to run the engine-generator setting to produce electricity:
#Thermal efficiency of engine = 40%;
#Electro Mechanical Efficiency of Generator = 75%;
#1ft^3 of biogas containing 55% Methane (CH4) provides 550 Btu of heat;
#40% of fuel energy is tranferable to cooling water;
#1kWh=3411Btu;
#10 lb of Dung plus Water is need to prepare Slurry which occupies a volume of 2/7 ft^3. (equivalent to 1.8 litre of Slurry per kg of Dung);
#Digester is expected to operated at 95oF (=35oC);
#Village needs 125 kWh of Electricity per day.
FIND:
[1]. Biogass (CH4, CO2, H2S, H2) Requirement for Biogass Equipment in m3/day.
[2]. Estimation of Manure Requirement.
[3]. Estimation Digester Capacity (Cylinder). Additional information: 4308 lb (1955kg) is feed to digester daily & should remain inside for 50days for Anaerobic Fermentation.
[4]. Estimation of Gas Holder Size.
[5]. Estimation of heat requirement in Joule (from 68oF to 95oF).
Solution:
[1]. ok
[2]. ok
[3]. ok
[4]. ok
[5]. This Assignment...
Amount of dung / day = 4,308 lb;
Amount of water / day = Amount of dung / day = 4,308 lb;
So, Total mass that need to heat is = 4,308 + 4,308 = 8,616 lb=3908.2176 kg (1 lb=0.4536kg);
95oF= 52.725oC (1 oF = 0.555 oC) and
68oF= 37.74oC.
Assumption: dung+water is well-mixed so, therfore: Cp of Dung=Cp of Water.
Definition of kcal: "The kcal is the heat needed to raise 1 kg of water by 1 oC" [2005. Pearson Education, Inc., Upper Saddle River, NJ. "Answer to Question of Chapter 14: Heat, p.340]
By this definition we can find the heat needed, as below:
Q = 3908.2176 (kg) x (52.725 - 37.74) (oC) x [1 kcal / (1 kg)(1oC)] x [4186 J / 1 kcal] = ...Joule
Q = 3908.2176 x 14.985 x 4186 (Joule)
Q = 245,151,586.120896 J.
Q = 245.1516 MJ/day
Q = 245.1516 x 1055.1 MBtu/day
Q = 258,659.4385 MBtu/day
(because: 1 Btu/s = 1055.1 W; 1 W = 1 J/s; there fore: 1Btu/s=1055.1J/s)
Lasman Parulian Purba, ST (mr)
SN: 4910120113
Master Degree Student in
Mechanical Engineering
Faculty of Engineering
Prince of Songkla University,
HatYai Campus,
THAILAND
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Capacity of BIOGAS PLANT = 100ft^3.
BIOGAS is used to run the engine-generator setting to produce electricity:
#Thermal efficiency of engine = 40%;
#Electro Mechanical Efficiency of Generator = 75%;
#1ft^3 of biogas containing 55% Methane (CH4) provides 550 Btu of heat;
#40% of fuel energy is tranferable to cooling water;
#1kWh=3411Btu;
#10 lb of Dung plus Water is need to prepare Slurry which occupies a volume of 2/7 ft^3. (equivalent to 1.8 litre of Slurry per kg of Dung);
#Digester is expected to operated at 95oF (=35oC);
#Village needs 125 kWh of Electricity per day.
FIND:
[1]. Biogass (CH4, CO2, H2S, H2) Requirement for Biogass Equipment in m3/day.
[2]. Estimation of Manure Requirement.
[3]. Estimation Digester Capacity (Cylinder). Additional information: 4308 lb (1955kg) is feed to digester daily & should remain inside for 50days for Anaerobic Fermentation.
[4]. Estimation of Gas Holder Size.
[5]. Estimation of heat requirement in Joule (from 68oF to 95oF).
Solution:
[1]. ok
[2]. ok
[3]. ok
[4]. ok
[5]. This Assignment...
Amount of dung / day = 4,308 lb;
Amount of water / day = Amount of dung / day = 4,308 lb;
So, Total mass that need to heat is = 4,308 + 4,308 = 8,616 lb=3908.2176 kg (1 lb=0.4536kg);
95oF= 52.725oC (1 oF = 0.555 oC) and
68oF= 37.74oC.
Assumption: dung+water is well-mixed so, therfore: Cp of Dung=Cp of Water.
Definition of kcal: "The kcal is the heat needed to raise 1 kg of water by 1 oC" [2005. Pearson Education, Inc., Upper Saddle River, NJ. "Answer to Question of Chapter 14: Heat, p.340]
By this definition we can find the heat needed, as below:
Q = 3908.2176 (kg) x (52.725 - 37.74) (oC) x [1 kcal / (1 kg)(1oC)] x [4186 J / 1 kcal] = ...Joule
Q = 3908.2176 x 14.985 x 4186 (Joule)
Q = 245,151,586.120896 J.
Q = 245.1516 MJ/day
Q = 245.1516 x 1055.1 MBtu/day
Q = 258,659.4385 MBtu/day
(because: 1 Btu/s = 1055.1 W; 1 W = 1 J/s; there fore: 1Btu/s=1055.1J/s)
Lasman Parulian Purba, ST (mr)
SN: 4910120113
Master Degree Student in
Mechanical Engineering
Faculty of Engineering
Prince of Songkla University,
HatYai Campus,
THAILAND
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[preliminary energy audit biomass boiler] OTHER losses Energy is about 43.78% ?
Message from Head of Energy Audit Team Engineering--Ardjan Chukiat K.: "This Losses is Not Usual: It is a MUST to know where is the potentials to make that's inefficiency!."
We must concentrate to this measure.
1. May be the reference that members use not the same, so that m*Cp*dT and enthalpy not the same value.
2. Combustion Chamber, especially we must know the efficiency or optimize.
3. Boiler...is the other one Chamber that we must know the efficiency or optimize.
E5, E6, E7, E9 is as in the usual range. But E8 other losses not as usual.
Indonesia (supplier): 1bucket=12Kg of Palm Shell Waste; ....transport---Thailand: one bucket=8Kg (PT. CMC)
To improve the efficiency of boiler is usually use the equation: INPUT - (Losses / INPUT) not (Output / INPUT ).
HOPE, the second EXPERIENCE will be BETTER and SUCCESFULL...
...Thank You For All...
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We must concentrate to this measure.
1. May be the reference that members use not the same, so that m*Cp*dT and enthalpy not the same value.
2. Combustion Chamber, especially we must know the efficiency or optimize.
3. Boiler...is the other one Chamber that we must know the efficiency or optimize.
E5, E6, E7, E9 is as in the usual range. But E8 other losses not as usual.
Indonesia (supplier): 1bucket=12Kg of Palm Shell Waste; ....transport---Thailand: one bucket=8Kg (PT. CMC)
To improve the efficiency of boiler is usually use the equation: INPUT - (Losses / INPUT) not (Output / INPUT ).
HOPE, the second EXPERIENCE will be BETTER and SUCCESFULL...
...Thank You For All...
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[infoINTERNATIONALconference]June2007
international conference June 2007 related to environmental energy and risk management...
http://www.wessex.ac.uk/conferences/2007/health07/index.html#secretariat
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Template RISK Tech 2007 Indonesia
Title of Paper
1,2First Author, 1Next Author & 2Last Author
1Author Address
2Author Address
Contact Person:
Contact person’s name
Address
Phone, email, homepage
Abstract. Use 10 pt Times font for body of the text with one spacing between lines, and 12 pt spacing for the next heading. Left and right indent 0.5 cm. Maximum length 200 words.
Keywords: use 10 pt; lower case; italic; Times; write alphabetically in 5-10 words.
1 Introduction
The paper be written in A4 size with the left margin of 3 cm and right margin of 2 cm. The proceedings will be printed in black and white format.
The section title use 14 pt, bold, Times, title case with 6 pt spacing to the body text. Use 11 pt Times for body of the text with one spacing between lines, 12 pt spacing between paragraph and 18 pt spacing for the next heading.[1] To set the style, simply use this template and follow the instructions on section 2.
2 Style and Formatting
This template already set the style and formatting for the paper, so you can use those styles by typing the style name on the style box as shown in the figure below:
The styles used in this paper are:
1. Title, for paper’s title
2. Author, for author’s name
3. Address, for author’s address
4. Abstract, for abstract
5. Heading 1, for section title
6. Heading 2, for sub section title
7. Heading 3, 4, 5, 6, 7, 8, 9 for the next sub … sub-section title
8. Text, for body text
9. Equation and Enumeration
10. Figure (or Gambar), for figure caption
11. Table (or Tabel), for table caption
12. Reference, for references
13. Acknowledge, for References and Acknowledge header
2.1 Mathematical Formulation
Equation should be type with indent 1.27 pt, and numbered consecutively starting with (1) set flush right.
To set the style, type Equation in the style box. But this style only set the tab stop position. To put the equation on the right place just press tab button one time. And to type the equation number, press tab button once again from the right side of the equation.
(1)
2.1.1 Section and Sub-section Title
Just type Heading 1 for section title, Heading 2 for sub section title, and Heading 3 for sub sub-section title. The number will set automatically.
2.1.2 Figures and Tables
All figures and tables should be centered and numbered consecutively.
FIGURE
Figure 1 Type Figure in style box. The caption should be typed in lower case. Choose center if the caption fit on one line.
Table 1 Summary of Physical Parameters
No
Segments
Length
(km)
Elevation
(meter)
1
A-B
25
30
2
B-C
75.15
10
3
C-D
44.75
50
4
D-E
72.5
10
5
E-F
21.25
10
3 Length
Maximum length of article is 20 pages including all pictures, tables, nomenclature, references, etc.
4 Acknowledgement
You can type your acknowledgement here, including the fund source. (“Parts of this research is funded by Riset ITB No. …. “)
5 Nomenclature (if necessary)
List the nomenclature in alphabetical order. List Roman letters followed by Greek symbols followed by subscript and superscripts.
A
=
Amplitude
Cd
=
drag coefficient
fe
=
linearization coefficient
Ki
=
modification factor
g
=
wave number
y
=
Complex wave number
6 References
Within the text, references should be cited by giving last name of the author(s) and the year of the publication as:
Whitson (1995) has studied ….
...... the resulting equation is (Becker, 1998; Graf, 1999 and Morris et. al, 1996)
(2) (2)
Note that in the case of three or more authors, only the last name of the first author is cited and the others are denoted by et al. The same rule is also hold for header title in even page.
Use the same typeface as the body of the text for the references, or just type Reference in style box. Examples are:
4.1. Suharto (ed), Title of paper, Name of Proc., Publisher (1998).
1.2. Sutasurya, L. A., Title of paper, Name of Journal 5, 1-5 (1998).
2.3. Sutasurya, L. A., Handojo, A. & Riyanto, B., Title of paper, Name of Journal 8, 20-25 (1999).
3.4. Sutasurya, L. A., Handojo, A. & Riyanto, B., Title of book, ed. 2, Publisher (1997).
5. Name of the author(s) (if available), Title of paper (if available), Organization, website address, (1 April 1999).
7 Appendix
Manuscript Content
The contents of the paper should be in the following order:
1. Title of Paper
2. Author names and affiliation
3. Abstract
4. Body of the text (Introduction ………. Conclusion)
5. Acknowledgements
6. Nomenclature
7. References
8. Appendix
Soft copy can be emailed to risktech@edc.ms.itb.ac.id.
[1] For typing footnote, simply choose Insert Footnote on the menu bar, it numbered automatically.
taken from: http://risktech-2007.info/web%20RISKTECH_files/Page677.htm
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1,2First Author, 1Next Author & 2Last Author
1Author Address
2Author Address
Contact Person:
Contact person’s name
Address
Phone, email, homepage
Abstract. Use 10 pt Times font for body of the text with one spacing between lines, and 12 pt spacing for the next heading. Left and right indent 0.5 cm. Maximum length 200 words.
Keywords: use 10 pt; lower case; italic; Times; write alphabetically in 5-10 words.
1 Introduction
The paper be written in A4 size with the left margin of 3 cm and right margin of 2 cm. The proceedings will be printed in black and white format.
The section title use 14 pt, bold, Times, title case with 6 pt spacing to the body text. Use 11 pt Times for body of the text with one spacing between lines, 12 pt spacing between paragraph and 18 pt spacing for the next heading.[1] To set the style, simply use this template and follow the instructions on section 2.
2 Style and Formatting
This template already set the style and formatting for the paper, so you can use those styles by typing the style name on the style box as shown in the figure below:
The styles used in this paper are:
1. Title, for paper’s title
2. Author, for author’s name
3. Address, for author’s address
4. Abstract, for abstract
5. Heading 1, for section title
6. Heading 2, for sub section title
7. Heading 3, 4, 5, 6, 7, 8, 9 for the next sub … sub-section title
8. Text, for body text
9. Equation and Enumeration
10. Figure (or Gambar), for figure caption
11. Table (or Tabel), for table caption
12. Reference, for references
13. Acknowledge, for References and Acknowledge header
2.1 Mathematical Formulation
Equation should be type with indent 1.27 pt, and numbered consecutively starting with (1) set flush right.
To set the style, type Equation in the style box. But this style only set the tab stop position. To put the equation on the right place just press tab button one time. And to type the equation number, press tab button once again from the right side of the equation.
(1)
2.1.1 Section and Sub-section Title
Just type Heading 1 for section title, Heading 2 for sub section title, and Heading 3 for sub sub-section title. The number will set automatically.
2.1.2 Figures and Tables
All figures and tables should be centered and numbered consecutively.
FIGURE
Figure 1 Type Figure in style box. The caption should be typed in lower case. Choose center if the caption fit on one line.
Table 1 Summary of Physical Parameters
No
Segments
Length
(km)
Elevation
(meter)
1
A-B
25
30
2
B-C
75.15
10
3
C-D
44.75
50
4
D-E
72.5
10
5
E-F
21.25
10
3 Length
Maximum length of article is 20 pages including all pictures, tables, nomenclature, references, etc.
4 Acknowledgement
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taken from: http://risktech-2007.info/web%20RISKTECH_files/Page677.htm
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Abstaract for RISK Tech 2007 Bandung Indonesia
Airflow Modeling: Efforts to Find the Better Models for Building Air Quality Simulation.
Purba, L.P.(1), Tekasakul, P.(2), Maliwan, K.(3)
1, Mechanical Engineering Department Student of Prince of Songkla University, Hat Yai Campus, Thailand, 90110
Email: las.et.nic@gmail.com
Abstract
All combustion sources, such as motor vehicle traffic, industrial combustion processes, burning, cooking, heating, and tobacco smoking, generate large quantities of fine (aerodynamic diameter smaller than 2.5 mm) and ultra-fine (smaller than 0.1 mm) particles. Smaller particles can penetrate deeper into the respiratory tract and therefore have a higher potential to induce health effects than larger particles.
Suspended particulate matter can serve as nuclei and carriers for airborne viruses and bacteria, resulting in the spread of diseases. In addition, fine particles themselves can deposit in the lungs and cause respiratory diseases. As people spend about 90% of their lifetime indoors, indoor particulate matter can have great impact on human health. Thus, a good understanding of particle transport is crucial for creating healthy indoor environments.
In this paper, more than four model simulation of indoor airflow for building is reviewed. Hope fully, this help decisions maker have many consideration to improve or manage airflow for building. This is an effort to improve working environment in factory that seems to be severely affected by particulate matter.
Keywords: Particulate Matter, Airflow, Building, Simulation.
References:
[1].Michael D. Sohn, Michael G. Apte, Richard G. Sextro, Alvin C. K. Lai, 2006. Predicting size-resolved particle behaviour in multizone buildings”. Atmospheric Environment (2006),DOI:10.1016/ j.atmosenv.2006.10.010
[2].Nazaroff and Cass, 1989. Mathematical modeling of indoor aerosol dynamics. Environmental Science and Technology 23 (2), 157-166
[3].Feustel, H. E., 1999. COMIS-An international multizone air-flow and contaminant transport model. Energy and buildings 30, 3-18
[4].Dols, W.S., Walton, G.N, 2002. CONTAMW 2.0 User Manual, National Institute of Standards and Technology, NISTIR 6921
[5].Tareq Hussein, Hannele Korhonen, Erik Herrmann, Kaarle H¨ameri, Kari E. J. Lehtinen, and Markku Kulmala. 2005. "Emission Rates Due to Indoor Activities: Indoor Aerosol Model Development, Evaluation, and Applications," Aerosol Science and Technology, 39:1111–1127, Copyright: American Association for Aerosol Research, ISSN: 0278-6826 print / 1521-7388 online; DOI: 10.1080/02786820500421513
[6].Zhang, Z. and Chen, Q. 2006. “Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms,” Atmospheric Environment, 40(18), 3396-3408.
[7].Klepeis, N.E., Nelson, W.C., Ott, W.R., Robinson, J.P., Tsang, A.M., Switzer, P., Behar, J.V., Hern, S.C., and Engelmann, W.H., 2001, “The national human activity pattern survey (NHAPS): A resource for assessing exposure to environmental pollutants,” Journal of Exposure Analysis and Environmental Epidemiology, Vol. 11 (3), pp 231-252.
[8].Aliage, C. and Winqvist, K., 2003, “Commnet les femmes et les homes utilisent leurs temps-Résultats de 13 pays européens,” Eurostat, KS-NK-03-012-FR-N.
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Purba, L.P.(1), Tekasakul, P.(2), Maliwan, K.(3)
1, Mechanical Engineering Department Student of Prince of Songkla University, Hat Yai Campus, Thailand, 90110
Email: las.et.nic@gmail.com
Abstract
All combustion sources, such as motor vehicle traffic, industrial combustion processes, burning, cooking, heating, and tobacco smoking, generate large quantities of fine (aerodynamic diameter smaller than 2.5 mm) and ultra-fine (smaller than 0.1 mm) particles. Smaller particles can penetrate deeper into the respiratory tract and therefore have a higher potential to induce health effects than larger particles.
Suspended particulate matter can serve as nuclei and carriers for airborne viruses and bacteria, resulting in the spread of diseases. In addition, fine particles themselves can deposit in the lungs and cause respiratory diseases. As people spend about 90% of their lifetime indoors, indoor particulate matter can have great impact on human health. Thus, a good understanding of particle transport is crucial for creating healthy indoor environments.
In this paper, more than four model simulation of indoor airflow for building is reviewed. Hope fully, this help decisions maker have many consideration to improve or manage airflow for building. This is an effort to improve working environment in factory that seems to be severely affected by particulate matter.
Keywords: Particulate Matter, Airflow, Building, Simulation.
References:
[1].Michael D. Sohn, Michael G. Apte, Richard G. Sextro, Alvin C. K. Lai, 2006. Predicting size-resolved particle behaviour in multizone buildings”. Atmospheric Environment (2006),DOI:10.1016/ j.atmosenv.2006.10.010
[2].Nazaroff and Cass, 1989. Mathematical modeling of indoor aerosol dynamics. Environmental Science and Technology 23 (2), 157-166
[3].Feustel, H. E., 1999. COMIS-An international multizone air-flow and contaminant transport model. Energy and buildings 30, 3-18
[4].Dols, W.S., Walton, G.N, 2002. CONTAMW 2.0 User Manual, National Institute of Standards and Technology, NISTIR 6921
[5].Tareq Hussein, Hannele Korhonen, Erik Herrmann, Kaarle H¨ameri, Kari E. J. Lehtinen, and Markku Kulmala. 2005. "Emission Rates Due to Indoor Activities: Indoor Aerosol Model Development, Evaluation, and Applications," Aerosol Science and Technology, 39:1111–1127, Copyright: American Association for Aerosol Research, ISSN: 0278-6826 print / 1521-7388 online; DOI: 10.1080/02786820500421513
[6].Zhang, Z. and Chen, Q. 2006. “Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms,” Atmospheric Environment, 40(18), 3396-3408.
[7].Klepeis, N.E., Nelson, W.C., Ott, W.R., Robinson, J.P., Tsang, A.M., Switzer, P., Behar, J.V., Hern, S.C., and Engelmann, W.H., 2001, “The national human activity pattern survey (NHAPS): A resource for assessing exposure to environmental pollutants,” Journal of Exposure Analysis and Environmental Epidemiology, Vol. 11 (3), pp 231-252.
[8].Aliage, C. and Winqvist, K., 2003, “Commnet les femmes et les homes utilisent leurs temps-Résultats de 13 pays européens,” Eurostat, KS-NK-03-012-FR-N.
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Sunday, February 11, 2007
[study4progressreport]monday meeting
Comparison of indoor aerosol particle concentration and deposition in different ventilated rooms by numerical method
Bin Zhao, Ying Zhang, Xianting Li, Xudong Yang, Dongtao Huang
Dept. of Biulding Science & Dept of Engineering Mechanics,Tsinghua University, Beijing, China
University of Miami, Coral Gables, FL 33124-0630, USA
Building and Environment 39 (2004) 1-8
PM is a ubiquitous pollutan indoor and outdoor around the world. Aerosol particles are regarded as significant pollutant sources in the indoor environment. The aerosol particle concentration is a room greatly influences the IAQ.
Aerosol particles may also be deposited on interior surfaces, causing a soiling problem and further leading to damage, for example on works of art in museums.
The movement of particles in ventilated areas is influenced by many factors, such as:
airflow pattern,
particle properties,
geometry configurations,
ventilation rates,
supply and exhaust diffuser locations,
internal partitions,
thermal buoyancy due to the heat generated by occupants and/or equipment,
etc. [1 and 2].
1. W. Lu and A.T. Howarth, Numerical analysis of indoor aerosol particle deposition and distribution in two-zone ventilated system. Building and Environment 31 (1996), pp. 41–50. SummaryPlus | Full Text + Links | PDF (986 K) | Abstract + References in Scopus | Cited By in Scopus
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Bin Zhao, Ying Zhang, Xianting Li, Xudong Yang, Dongtao Huang
Dept. of Biulding Science & Dept of Engineering Mechanics,Tsinghua University, Beijing, China
University of Miami, Coral Gables, FL 33124-0630, USA
Building and Environment 39 (2004) 1-8
PM is a ubiquitous pollutan indoor and outdoor around the world. Aerosol particles are regarded as significant pollutant sources in the indoor environment. The aerosol particle concentration is a room greatly influences the IAQ.
Aerosol particles may also be deposited on interior surfaces, causing a soiling problem and further leading to damage, for example on works of art in museums.
The movement of particles in ventilated areas is influenced by many factors, such as:
airflow pattern,
particle properties,
geometry configurations,
ventilation rates,
supply and exhaust diffuser locations,
internal partitions,
thermal buoyancy due to the heat generated by occupants and/or equipment,
etc. [1 and 2].
1. W. Lu and A.T. Howarth, Numerical analysis of indoor aerosol particle deposition and distribution in two-zone ventilated system. Building and Environment 31 (1996), pp. 41–50. SummaryPlus | Full Text + Links | PDF (986 K) | Abstract + References in Scopus | Cited By in Scopus
2. W. Lu, A.T. Howarth, N. Adam and S. Riffat, Modeling and measurement of airflow and aerosol particle distribution in a ventilated two-zone chamber. Building and Environment 31 (1996), pp. 417–423. SummaryPlus | Full Text + Links | PDF (630 K) | Abstract + References in Scopus | Cited By in Scopus
3. W. Lu and A.T. Howarth, Indoor aerosol particle deposition and distribution: numerical analysis for a one-zone ventilation system. Building Services Engineering Research and Technology 16 (1995), pp. 141–147. Abstract + References in Scopus | Cited By in Scopus
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Saturday, January 13, 2007
Summary of paperONE (Michael et al., 2006)
Understanding the dynamic behavior of indoor aerosols is essential for accurately predicting their concentrations and fates within a building, and for estimating human exposures. (Michael et el., 2006 (this paper))
Processes such as coagulation, deposition, and removal by indoor filtration can depend strongly on the particle size distribution of the species, and these processes can affect the overall airborne concentration in buildings.
The particle size distribution is also an important element in estimating the quantity and location of particle deposition in the lung.
Mathematical Eq(s). to express these process in building, and computer software to solve them have been developed and applied successfully [for predicting aerosol concentrations in various indoor systems]
1. Nazaroff and Cass, 1989:
The aerosol dynamics model (ADM):
*simulates the evolution of particle size distributions, using a multi-component sectional representation
*utilizes a multi-zone representation of a building. [each zone is considered independently well-mixed]]
*equations are written based on the principle of mass conservation (solve numerically)
An important component of ADM is the explicit incorporation of particle size distribution information.
Particle size governs almost all particle behavior (Hinds, 1982), including:
# the removal efficiency of an air filter,
# the rate of deposition onto surfaces,
# the coagulation of small particles with larger ones, and
# the retention efficiency of the lung upon inhalation.
The ADM accounts for many factors, including:
@. Direct ETS particle emissions,
@. Inter-zonal mixing,
@. Ventilation,
@. Filtration,
@. Coagulation, and
@. Deposition onto surfaces.
But The ADM not included accounts:
¨ Evaporation,
¨ Condensation, and
¨ Homogenous nucleation.
COMIS:
CONTAM:
CONTAM (Dols, W. Stuart. Walton, G. N. (BUILDING ENVIRONMENT DIVISION - 863)
CONTAMW 2.0 User Manual (NISTIR 6921) - November 01, 2002 )
This manual describes the computer program CONTAMW version 2.0 developed by NIST. CONTAMW is a multizone indoor air quality and ventilation analysis program designed to help you determine: airflows and pressures – infiltration, exfiltration, and room-to-room airflows and pressure differences in building systems driven by mechanical means, wind pressures acting on the exterior of the building, and buoyancy effects induced by temperature differences between the building and the outside; contaminant concentrations – the dispersal of airborne contaminants transported by these airflows and transformed by a variety of processes including chemical and radio-chemical transformation, adsorption and desorption to building materials, filtration, and deposition to building surfaces; and/or personal exposure – the prediction of exposure of building occupants to airborne contaminants for eventual risk assessment. CONTAMW can be useful in a variety of applications. Its ability to calculate building airflows and relative pressures between zones of the building is useful for assessing the adequacy of ventilation rates in a building, to determine the variation in ventilation rates over time, to determine the distribution of ventilation air within a building, and to estimate the impact of envelope airtightening efforts on infiltration rates. The program has been used extensively for the design and analysis of smoke management systems. The prediction of contaminant concentrations can be used to determine the indoor air quality performance of buildings before they are constructed and occupied, to investigate the impacts of various design decisions related to ventilation system design and building material selection, to evaluate indoor air quality control technologies, and to assess the indoor air quality performance of existing buildings. Predicted contaminant concentrations can also be used to estimate personal exposure based on occupancy patterns. Version 2.0 contains several new features including: non-grace contaminants, unlimited number of contaminants, contaminant-related libraries, separate weather and ambient contaminant files, building controls, scheduled zone temperatures, improved solver to reduce simulation times and several user interface related features to improve usability.
Keywords: airflow analysis , building technology , computer program , contaminant dispersal , controls , indoor air quality , multizone analysis , smoke control , smoke management
Point2: Coupled airflow and aerosol transport
We use the COMIS airflow model (Feustel, 1999)
to predict the airflows between rooms, and between indoors and outdoors.
COMIS predicts the steady-state flow of air (las: airflow) induced by:
> wind,
> thermal buoyancy,and
> mechanical ventilation
by representing a building:
$ as a collection of zones,
$ connected by flow paths (such as cracks, doors and windows, and ductwork).
Assumptions:
1. Air=incompressible fluid flow,
2. Airflow (through these pathways) is calculated by
balancing pressure differences between the zones.
Feustel (1999) and Lorenzetti (2002) describe the mathematical foundations of the COMIS model.
COMIS has been applied to predict airflow and gas transport:
@ in residences (Feustel et al., 1985; Sextro et al., 1999),
@ in small office buildings (Feustel, 1990),
@ in controlled experimental test houses (Haghighat and Megri, 1996), and
@ in single-family houses (Haghighat and Megri, 1996, Zhao et al., 1998).
OUTPUT from COMIS: airflows. (Michael et al., 2006)this paperONE)
Air flows between rooms and across the building envelope for:
& every user-defined building operating mode, and
& meteorological condition.
Then Michael et al. (2006) use the MIAQ4 aerosol dynamics software based-on
(Nazaroff and Cass, 1989):
@ to predict the size-resolved transport, and
@ to predict the evolution of particle concentrations
prompted by the COMIS-calculated airflows,
and directed by particle dynamics behavior such as
>gravitational settling,
>coagulation, and
>thermal diffusion.
MIAQ4 simulates a size- and chemically-resolved particle size distribution.
It does not take into account:
* evaporation,
* condensation, or
* homogeneous nucleation.
The aerosol model was originally developed for and applied to predicting the behavior of:
1. particles from cigarette smoke in a chamber(Nazaroff and Cass, 1989) and
2. particulate matter (PM) in museums (Nazaroff et al., 1990).
The COMIS&MIAQ4 are linked in a feed-forward manner.(Las: in--->COMIS---(Perl)--->MIAQ4--->out (mungkin dapat di umpanbaikkan ke sisi in dari COMIS))
The airflows predicted by COMIS serve as inputs to MIAQ4.
Feedback from MIAQ4 to COMIS is unnecessary since:
<> the total airflow mass is much greater than the pollutant mass, and
Feedback from MIAQ4 to COMIS can thus be ignored in the airflow mass balance equations.
We linked the COMIS&MIAQ4 by writing a computer program that transforms output from COMIS into MIAQ4.
We wrote the linking software in the Perl scripting language:
? because PERL contains several built-in functions for formatting text and numbers, and
? because PERL is available for most computer systems.
Since linking is in a feed-forward manner, the Perl script first runs COMIS for an entire simulation for:
# all HVAC operations, and
# meteorological conditions of interest.
Perl then runs MIAQ4:
% in intermediate steps,
% halting the simulation (to readjust the flows when changes in airflow or temperature conditions occur), and
% restarting the simulation with the new state of the pollutant mass transport or loss.
3. Application COMIS&MIAQ4:
!. predict ETS particle transport in a three-room experimental chamber, and
!. compared predictions to data.
Apte et al. (2004) conducted tracer and ETS experiments in a full-scale, three-room, laboratory chamber. (as in Fig. 1)
Side-stream smoke was produced by machine-smoked cigarettes in Room 2 for approximately 8 min, while mainstream smoke was vented outside.
Sulfur hexafluoride (SF6) was injected simultaneously into Room 2 as a tracer gas.
Small mixing fans were running in each room at all times to increase well-mixed conditions.
Air sampling tubes were installed in each room to draw air from the chamber to external analytical equipment.
For our purposes here, we chose an experiment where:
@ the door between Rooms 1 and 3 was open fully and
@ the door between Rooms 2 and 3 was partially open (0.0254 m).
Both doors were standard height (2.12 m).
The temperature difference between rooms varied from 0 to 1 degree of Celcius during the experiment.
>Gas- and particle-phase ETS tracer concentrations,
>ETS particle mass, and
>particle size distributions in each room were measured as a
function of time.
3.1. Tracer gas and ETS particle characterization
Data consisted of time-series and point measurements of:
(1) tracer gas concentrations,
(2) total ETS mass concentration
(3) size-resolved particle concentrations and
(4) room air temperatures.
SF6 tracer gas was measured using a gas chromatograph (GC) with an electron capture detector (Hewlett Packard Model 5890).
Air was continuously drawn from each room via 3-mm-ID copper tubing (~1.8m from the floor) at 1 L/min.
To avoid lag time in the sample line, the gas sampling ports were sampled continuously, and vented out of the building when not being measured by the GC (every 4 min).
Total ETS particle mass was measured gravimetrically
(Cahn Model 21 Automatic Electrobalance, with 0.1-microgram resolution) by particle collection on precleaned (Sohxlet extration) and pre-weighed 47-mm-diameter Teflon-coated glass fiber filters (Fiberfilm T60A20, Gelman/Pallflex).
Filters in each room were connected to sampling pumps located outside the chamber.
Due to the low air exchange rate of the environmental chamber and to the very infrequent opening of the space, the infiltration of
ambient PM into the chamber was negligible.
Thus, the dominant source of PM in the chamber was the ETS generated during experiment.
For this reason, it was not necessary to use a size selective inlet for particle sampling in the chamber experiments.
The filter samples contained only respirable suspended PM (RSP) with a maximum particle aerodynamic diameter less than 1.5 mm.
Filter samples were each taken for 30 min at 3, 6 and 24 h during the experiment.
As discussed below, the intermittent operation of the particle-sampling pumps led to enhanced ventilation air flows in the
chamber for which we needed to explicitly account for in the modeling.
In addition, size- and time-resolved particle concentration measurements (pengukuran konsentrasi partikel dalam waktu [konsentrasi partikel sebagai fungsi waktu] dan ukuran partikel dalam waktu [ukuran partikel sebagai fungsi waktu]) were provided by:
#1. a Differential Mobility Particle Sizer (TSI/Classifier 3071 Ultrafine Condensation Particle Counter),
-->measure particle size diameters from 0.01 to 0.45 micrometer in diameter]
-->provide data from each room every hour, and
#2. an optical particle counter (LAS-X OPC),
-->measured particle diameters from 0.09 to 43.5 micrometer.
-->provide data from each room every 3 min.
These instruments (DMPS & OPC) all sampled from a continuously flowing sampling manifold connected to the center of each room.
3.2. Model-measurement comparisons
We developed a COMIS model of:
* the three-room chamber with room dimensions,
* the size of door openings, and
* room temperatures (as a function of time) as model inputs.
Because the experiments were run with the doors between the rooms open, we did not incorporate any added room-to-room leakages
(e.g. cracks) in the model.
We did include the air leakage between the chamber and the outside in the model, which we determined to be approximately 0.01 air changes per hour from tracer gas decay rate measurements, when the SF6 and DMPS/OPC sampler pumps were operating, but not the pumps for the open face filter samples.
We distributed this leakage uniformly across the outer walls of the
rooms.
Fig. 1 shows the predicted airflows at one instant in time during the experiment when the filter pumps were not running.
The airflows change moderately over time due to changing room temperatures and, as we describe later, due to the intermittent operation of the pumps for the aerosol filter samples. The airflow between Rooms 2 and 3 is significantly lower then the flow between Rooms 1 and 3 because the door between Rooms 2 and 3 is only partially open.
We used the airflow calculations to predict the dispersion of a puff release of 0.01 g of SF6 in Room 2 and compared the COMIS predictions
to measurements (Fig. 2). The COMIS model was not calibrated to the data; the input parameters, including size of the door opening
between Rooms 2 and 3, were measured independently.
Fig. 2 shows model-to-data comparisons with and without including the intermittent operation of the pumps to collect the total mass ETS particle samples at 3, 6 and 24 h. The figure shows that the
sampling pumps, though the amount of air removed is small (4.5–4.8m3 h1 for 30 min), increase the ventilation rate of the chamber, causing an appreciable reduction in the observed concentration of SF6
in the air. Because the overall leakage in the chamber is low, the pumping is a significant driver for air leakage when the pumps are operating. The inclusion of the air sampling pumps reduced the
root-mean-squared error (RMSE) when comparing the predictions to the experimental data by 76% in zone 1 and 60% in zone 2. We also tested the sensitivity of the model to the size of the door opening between Rooms 2 and 3 in other model runs, and found openings larger or smaller than the actual measured opening size produced inferior
matches to the data.
The model-to-data comparison for Room 3 is
similar to the comparisons for Room 1 because the
door between them is completely open, and
temperature differences between the rooms, though
small, are predicted to generate large inter-room
airflow, and thus mixing, between them. These
model predictions are, therefore, also consistent
with the data.
We next predicted the dispersion of ETS particles
from smoking one cigarette in Room 2. Inputs to
the MIAQ4 model were the airflow conditions predicted by COMIS, with inclusion of the intermittent
use of the filter pumps, the chamber
dimensions, measured temperatures as a function
of time, and an emission rate profile for side-stream
ETS particles, which we specified independently of
the data from this experiment (Nazaroff et al., 1993)
(Fig. 3). We also specified the turbulence intensity
factor for the chamber, which describes the streamwise
velocity gradient at the vicinity of the chamber
wall (Crump and Seinfeld, 1981). In this application,
we adjusted the turbulence intensity factor to
calibrate the model predictions to the overall
airborne ETS concentration data. We selected an
intensity factor of 1.2 s1, which is consistent with values reported by Furtaw et al. (1996) and Lai and
Nazaroff (2000).
Fig. 4 shows the measured and modeled concentration
of total ETS particles in Rooms 1 and 2, as
measured by the filter samples and by the DMPS.
The slopes of the decay curves are fairly consistent
with the measured data, suggesting that, in general,
MIAQ4 is properly predicting the transport and
losses due to deposition and surface diffusion.
However, Fig. 4 shows predicted particle concentrations,
in general, lower than were measured
(R2 ¼ 0.93, RMSE ¼ 52 mgm3). Since the SF6
dispersion predictions agree well with measurements,
it is unlikely that the MIAQ4 is incorrectly
predicting airflows. It is more likely that the actual
ETS released during the experiment was larger than
we assumed for input into the model (Fig. 3) since
the total side-stream particle mass emitted from a
cigarette can vary from one experiment to the next
(e.g., see Fig. 12 in Apte et al.). Because of this
variability, however, estimating an experimentspecific
mass emission entails back estimating the
mass based on model-to-data comparisons. We
chose not to do this calibration since it diminishes
the persuasiveness of the model-data comparisons.
It is also possible that the turbulence intensity factor
chosen for the model was not correct, thus underpredicting
particle deposition onto surfaces, and, therefore, underestimating these losses. Further
experiments and modeling will be needed to
determine the primary causes of the differences,
but such analyses were beyond the scope of this
demonstration.
Figs. 5 and 6 shows MIAQ4-predicted concentrations
of ETS in Room 2 resolved by particle size
compared to DMPS measurements at 40, 160, 460,
and 640 min after the cigarette was smoked. Figs. 7
and 8 shows model-to-data comparisons for Room
1. In general, the overall shapes of the model
predictions agree well with the data. The difference
between modeled and measured binned particle
concentrations is consistent with the discrepancies
in total concentrations shown in Fig. 4. The
size-resolved plots also show that relative differences
between the measured and modeled are
small and that across particle size and concentration
no consistent biases exist in the model’s
predictions.
4. Discussion and concluding remarks
We have linked the COMIS-multizone airflow model with the MIAQ4-aerosol dynamics model:
@ to predict size-resolved aerosol transport in multiroom buildings.
-->Though both models have been reported and demonstrated individually in the
literature, they have not been applied together to predict size-resolved aerosol transport in multiroom buildings, or compared to real data.
-->The linked model will be a useful tool for examining the behavior of aerosols in multizone buildings and predicting concentrations and exposures as a function of particle size. The latter may be especially important for evaluating different strategies for reducing aerosol exposures within buildings.
@can also be used to aid in the design and interpretation of field experiments.
As proof of concept, we applied the models to predict the transport and behavior of tracer gas
and ETS particles measured in a three-room chamber. We obtained excellent agreement between the predicted and observed tracer gas concentrations in all three rooms. The predictions of both ETS particle mass and size-resolved particle
concentrations also agreed well with the measurements.
COMIS was particularly helpful for estimating the inter-room airflows caused by operating the
filter-sampling pumps, and therefore reduced the number of experiments needed to characterize the airflows.
From Literatures Study More:
Apte et al. (2004)
Test space description
Chamber layout and construction
A 50 m3 multizone environmental chamber was constructed within a temperature controlled single-story building at Lawrence Berkeley National Laboratory (LBNL). The chamber was designed to mimic conditions of a multi-room residential or office building where ETS might be generated in one room and transported to others. The layout of the chamber, shown in Figure 1, consisted of three rooms, a smoking room (SR), a connecting corridor (COR), and a non-smoking room (NSR). The chamber was built using wood frame construction with taped and painted gypsum wallboard walls and ceiling, and a high-quality nylon carpet laid over plywood sub-flooring in all three
chamber rooms. The entry and interconnecting doors were standard solid core wood design; however, magnetic refrigerator door seals (and accompanying steel flanges for the door openings) were added to the entire door perimeters to ensure near airtight sealing when the doors were fully closed. Low volatile organic compound (VOC) emitting
paints and sealants were used throughout the chamber in order to minimize the buildup of unwanted VOCs in the chambers. A plastic (PVC) membrane vapor barrier was placed behind the gypsum wallboard on the interior walls between the SR and the other two
chambers to retard any diffusion of ETS components through the wall materials between rooms. Fully closed, the baseline air exchange rate (λv) of the chamber and its composite sub-rooms was approximately 0.01 h-1.
Four 10- cm-diameter axial mixing fans were placed in each room, mounted at a height of approximately 1.5m above the floor, at about 1.5m along the diagonals between corners. The fan axes were horizontal and were oriented in opposing directions in order to
enhance the mixing within each room. The fan speed was controlled using a Variac transformer at a speed just high enough to achieve uniform mixing of gases, based upon previous chamber experiments.
Each chamber room was equipped with a set of small- and large-diameter sampling ports, each with a plug to close the ports not in use. The large sampling ports were just large enough to permit the insertion of a 47mm particle sampling filter holder, while the small
ports allowed for the insertion of nicotine sampling sorbent tubes into the chamber.
http://continuousimprovement.blogsome.com
Processes such as coagulation, deposition, and removal by indoor filtration can depend strongly on the particle size distribution of the species, and these processes can affect the overall airborne concentration in buildings.
The particle size distribution is also an important element in estimating the quantity and location of particle deposition in the lung.
Mathematical Eq(s). to express these process in building, and computer software to solve them have been developed and applied successfully [for predicting aerosol concentrations in various indoor systems]
1. Nazaroff and Cass, 1989:
The aerosol dynamics model (ADM):
*simulates the evolution of particle size distributions, using a multi-component sectional representation
*utilizes a multi-zone representation of a building. [each zone is considered independently well-mixed]]
*equations are written based on the principle of mass conservation (solve numerically)
An important component of ADM is the explicit incorporation of particle size distribution information.
Particle size governs almost all particle behavior (Hinds, 1982), including:
# the removal efficiency of an air filter,
# the rate of deposition onto surfaces,
# the coagulation of small particles with larger ones, and
# the retention efficiency of the lung upon inhalation.
The ADM accounts for many factors, including:
@. Direct ETS particle emissions,
@. Inter-zonal mixing,
@. Ventilation,
@. Filtration,
@. Coagulation, and
@. Deposition onto surfaces.
But The ADM not included accounts:
¨ Evaporation,
¨ Condensation, and
¨ Homogenous nucleation.
COMIS:
CONTAM:
CONTAM (Dols, W. Stuart. Walton, G. N. (BUILDING ENVIRONMENT DIVISION - 863)
CONTAMW 2.0 User Manual (NISTIR 6921) - November 01, 2002 )
This manual describes the computer program CONTAMW version 2.0 developed by NIST. CONTAMW is a multizone indoor air quality and ventilation analysis program designed to help you determine: airflows and pressures – infiltration, exfiltration, and room-to-room airflows and pressure differences in building systems driven by mechanical means, wind pressures acting on the exterior of the building, and buoyancy effects induced by temperature differences between the building and the outside; contaminant concentrations – the dispersal of airborne contaminants transported by these airflows and transformed by a variety of processes including chemical and radio-chemical transformation, adsorption and desorption to building materials, filtration, and deposition to building surfaces; and/or personal exposure – the prediction of exposure of building occupants to airborne contaminants for eventual risk assessment. CONTAMW can be useful in a variety of applications. Its ability to calculate building airflows and relative pressures between zones of the building is useful for assessing the adequacy of ventilation rates in a building, to determine the variation in ventilation rates over time, to determine the distribution of ventilation air within a building, and to estimate the impact of envelope airtightening efforts on infiltration rates. The program has been used extensively for the design and analysis of smoke management systems. The prediction of contaminant concentrations can be used to determine the indoor air quality performance of buildings before they are constructed and occupied, to investigate the impacts of various design decisions related to ventilation system design and building material selection, to evaluate indoor air quality control technologies, and to assess the indoor air quality performance of existing buildings. Predicted contaminant concentrations can also be used to estimate personal exposure based on occupancy patterns. Version 2.0 contains several new features including: non-grace contaminants, unlimited number of contaminants, contaminant-related libraries, separate weather and ambient contaminant files, building controls, scheduled zone temperatures, improved solver to reduce simulation times and several user interface related features to improve usability.
Keywords: airflow analysis , building technology , computer program , contaminant dispersal , controls , indoor air quality , multizone analysis , smoke control , smoke management
Point2: Coupled airflow and aerosol transport
We use the COMIS airflow model (Feustel, 1999)
to predict the airflows between rooms, and between indoors and outdoors.
COMIS predicts the steady-state flow of air (las: airflow) induced by:
> wind,
> thermal buoyancy,and
> mechanical ventilation
by representing a building:
$ as a collection of zones,
$ connected by flow paths (such as cracks, doors and windows, and ductwork).
Assumptions:
1. Air=incompressible fluid flow,
2. Airflow (through these pathways) is calculated by
balancing pressure differences between the zones.
Feustel (1999) and Lorenzetti (2002) describe the mathematical foundations of the COMIS model.
COMIS has been applied to predict airflow and gas transport:
@ in residences (Feustel et al., 1985; Sextro et al., 1999),
@ in small office buildings (Feustel, 1990),
@ in controlled experimental test houses (Haghighat and Megri, 1996), and
@ in single-family houses (Haghighat and Megri, 1996, Zhao et al., 1998).
OUTPUT from COMIS: airflows. (Michael et al., 2006)this paperONE)
Air flows between rooms and across the building envelope for:
& every user-defined building operating mode, and
& meteorological condition.
Then Michael et al. (2006) use the MIAQ4 aerosol dynamics software based-on
(Nazaroff and Cass, 1989):
@ to predict the size-resolved transport, and
@ to predict the evolution of particle concentrations
prompted by the COMIS-calculated airflows,
and directed by particle dynamics behavior such as
>gravitational settling,
>coagulation, and
>thermal diffusion.
MIAQ4 simulates a size- and chemically-resolved particle size distribution.
It does not take into account:
* evaporation,
* condensation, or
* homogeneous nucleation.
The aerosol model was originally developed for and applied to predicting the behavior of:
1. particles from cigarette smoke in a chamber(Nazaroff and Cass, 1989) and
2. particulate matter (PM) in museums (Nazaroff et al., 1990).
The COMIS&MIAQ4 are linked in a feed-forward manner.(Las: in--->COMIS---(Perl)--->MIAQ4--->out (mungkin dapat di umpanbaikkan ke sisi in dari COMIS))
The airflows predicted by COMIS serve as inputs to MIAQ4.
Feedback from MIAQ4 to COMIS is unnecessary since:
<> the total airflow mass is much greater than the pollutant mass, and
Feedback from MIAQ4 to COMIS can thus be ignored in the airflow mass balance equations.
We linked the COMIS&MIAQ4 by writing a computer program that transforms output from COMIS into MIAQ4.
We wrote the linking software in the Perl scripting language:
? because PERL contains several built-in functions for formatting text and numbers, and
? because PERL is available for most computer systems.
Since linking is in a feed-forward manner, the Perl script first runs COMIS for an entire simulation for:
# all HVAC operations, and
# meteorological conditions of interest.
Perl then runs MIAQ4:
% in intermediate steps,
% halting the simulation (to readjust the flows when changes in airflow or temperature conditions occur), and
% restarting the simulation with the new state of the pollutant mass transport or loss.
3. Application COMIS&MIAQ4:
!. predict ETS particle transport in a three-room experimental chamber, and
!. compared predictions to data.
Apte et al. (2004) conducted tracer and ETS experiments in a full-scale, three-room, laboratory chamber. (as in Fig. 1)
Side-stream smoke was produced by machine-smoked cigarettes in Room 2 for approximately 8 min, while mainstream smoke was vented outside.
Sulfur hexafluoride (SF6) was injected simultaneously into Room 2 as a tracer gas.
Small mixing fans were running in each room at all times to increase well-mixed conditions.
Air sampling tubes were installed in each room to draw air from the chamber to external analytical equipment.
For our purposes here, we chose an experiment where:
@ the door between Rooms 1 and 3 was open fully and
@ the door between Rooms 2 and 3 was partially open (0.0254 m).
Both doors were standard height (2.12 m).
The temperature difference between rooms varied from 0 to 1 degree of Celcius during the experiment.
>Gas- and particle-phase ETS tracer concentrations,
>ETS particle mass, and
>particle size distributions in each room were measured as a
function of time.
3.1. Tracer gas and ETS particle characterization
Data consisted of time-series and point measurements of:
(1) tracer gas concentrations,
(2) total ETS mass concentration
(3) size-resolved particle concentrations and
(4) room air temperatures.
SF6 tracer gas was measured using a gas chromatograph (GC) with an electron capture detector (Hewlett Packard Model 5890).
Air was continuously drawn from each room via 3-mm-ID copper tubing (~1.8m from the floor) at 1 L/min.
To avoid lag time in the sample line, the gas sampling ports were sampled continuously, and vented out of the building when not being measured by the GC (every 4 min).
Total ETS particle mass was measured gravimetrically
(Cahn Model 21 Automatic Electrobalance, with 0.1-microgram resolution) by particle collection on precleaned (Sohxlet extration) and pre-weighed 47-mm-diameter Teflon-coated glass fiber filters (Fiberfilm T60A20, Gelman/Pallflex).
Filters in each room were connected to sampling pumps located outside the chamber.
Due to the low air exchange rate of the environmental chamber and to the very infrequent opening of the space, the infiltration of
ambient PM into the chamber was negligible.
Thus, the dominant source of PM in the chamber was the ETS generated during experiment.
For this reason, it was not necessary to use a size selective inlet for particle sampling in the chamber experiments.
The filter samples contained only respirable suspended PM (RSP) with a maximum particle aerodynamic diameter less than 1.5 mm.
Filter samples were each taken for 30 min at 3, 6 and 24 h during the experiment.
As discussed below, the intermittent operation of the particle-sampling pumps led to enhanced ventilation air flows in the
chamber for which we needed to explicitly account for in the modeling.
In addition, size- and time-resolved particle concentration measurements (pengukuran konsentrasi partikel dalam waktu [konsentrasi partikel sebagai fungsi waktu] dan ukuran partikel dalam waktu [ukuran partikel sebagai fungsi waktu]) were provided by:
#1. a Differential Mobility Particle Sizer (TSI/Classifier 3071 Ultrafine Condensation Particle Counter),
-->measure particle size diameters from 0.01 to 0.45 micrometer in diameter]
-->provide data from each room every hour, and
#2. an optical particle counter (LAS-X OPC),
-->measured particle diameters from 0.09 to 43.5 micrometer.
-->provide data from each room every 3 min.
These instruments (DMPS & OPC) all sampled from a continuously flowing sampling manifold connected to the center of each room.
3.2. Model-measurement comparisons
We developed a COMIS model of:
* the three-room chamber with room dimensions,
* the size of door openings, and
* room temperatures (as a function of time) as model inputs.
Because the experiments were run with the doors between the rooms open, we did not incorporate any added room-to-room leakages
(e.g. cracks) in the model.
We did include the air leakage between the chamber and the outside in the model, which we determined to be approximately 0.01 air changes per hour from tracer gas decay rate measurements, when the SF6 and DMPS/OPC sampler pumps were operating, but not the pumps for the open face filter samples.
We distributed this leakage uniformly across the outer walls of the
rooms.
Fig. 1 shows the predicted airflows at one instant in time during the experiment when the filter pumps were not running.
The airflows change moderately over time due to changing room temperatures and, as we describe later, due to the intermittent operation of the pumps for the aerosol filter samples. The airflow between Rooms 2 and 3 is significantly lower then the flow between Rooms 1 and 3 because the door between Rooms 2 and 3 is only partially open.
We used the airflow calculations to predict the dispersion of a puff release of 0.01 g of SF6 in Room 2 and compared the COMIS predictions
to measurements (Fig. 2). The COMIS model was not calibrated to the data; the input parameters, including size of the door opening
between Rooms 2 and 3, were measured independently.
Fig. 2 shows model-to-data comparisons with and without including the intermittent operation of the pumps to collect the total mass ETS particle samples at 3, 6 and 24 h. The figure shows that the
sampling pumps, though the amount of air removed is small (4.5–4.8m3 h1 for 30 min), increase the ventilation rate of the chamber, causing an appreciable reduction in the observed concentration of SF6
in the air. Because the overall leakage in the chamber is low, the pumping is a significant driver for air leakage when the pumps are operating. The inclusion of the air sampling pumps reduced the
root-mean-squared error (RMSE) when comparing the predictions to the experimental data by 76% in zone 1 and 60% in zone 2. We also tested the sensitivity of the model to the size of the door opening between Rooms 2 and 3 in other model runs, and found openings larger or smaller than the actual measured opening size produced inferior
matches to the data.
The model-to-data comparison for Room 3 is
similar to the comparisons for Room 1 because the
door between them is completely open, and
temperature differences between the rooms, though
small, are predicted to generate large inter-room
airflow, and thus mixing, between them. These
model predictions are, therefore, also consistent
with the data.
We next predicted the dispersion of ETS particles
from smoking one cigarette in Room 2. Inputs to
the MIAQ4 model were the airflow conditions predicted by COMIS, with inclusion of the intermittent
use of the filter pumps, the chamber
dimensions, measured temperatures as a function
of time, and an emission rate profile for side-stream
ETS particles, which we specified independently of
the data from this experiment (Nazaroff et al., 1993)
(Fig. 3). We also specified the turbulence intensity
factor for the chamber, which describes the streamwise
velocity gradient at the vicinity of the chamber
wall (Crump and Seinfeld, 1981). In this application,
we adjusted the turbulence intensity factor to
calibrate the model predictions to the overall
airborne ETS concentration data. We selected an
intensity factor of 1.2 s1, which is consistent with values reported by Furtaw et al. (1996) and Lai and
Nazaroff (2000).
Fig. 4 shows the measured and modeled concentration
of total ETS particles in Rooms 1 and 2, as
measured by the filter samples and by the DMPS.
The slopes of the decay curves are fairly consistent
with the measured data, suggesting that, in general,
MIAQ4 is properly predicting the transport and
losses due to deposition and surface diffusion.
However, Fig. 4 shows predicted particle concentrations,
in general, lower than were measured
(R2 ¼ 0.93, RMSE ¼ 52 mgm3). Since the SF6
dispersion predictions agree well with measurements,
it is unlikely that the MIAQ4 is incorrectly
predicting airflows. It is more likely that the actual
ETS released during the experiment was larger than
we assumed for input into the model (Fig. 3) since
the total side-stream particle mass emitted from a
cigarette can vary from one experiment to the next
(e.g., see Fig. 12 in Apte et al.). Because of this
variability, however, estimating an experimentspecific
mass emission entails back estimating the
mass based on model-to-data comparisons. We
chose not to do this calibration since it diminishes
the persuasiveness of the model-data comparisons.
It is also possible that the turbulence intensity factor
chosen for the model was not correct, thus underpredicting
particle deposition onto surfaces, and, therefore, underestimating these losses. Further
experiments and modeling will be needed to
determine the primary causes of the differences,
but such analyses were beyond the scope of this
demonstration.
Figs. 5 and 6 shows MIAQ4-predicted concentrations
of ETS in Room 2 resolved by particle size
compared to DMPS measurements at 40, 160, 460,
and 640 min after the cigarette was smoked. Figs. 7
and 8 shows model-to-data comparisons for Room
1. In general, the overall shapes of the model
predictions agree well with the data. The difference
between modeled and measured binned particle
concentrations is consistent with the discrepancies
in total concentrations shown in Fig. 4. The
size-resolved plots also show that relative differences
between the measured and modeled are
small and that across particle size and concentration
no consistent biases exist in the model’s
predictions.
4. Discussion and concluding remarks
We have linked the COMIS-multizone airflow model with the MIAQ4-aerosol dynamics model:
@ to predict size-resolved aerosol transport in multiroom buildings.
-->Though both models have been reported and demonstrated individually in the
literature, they have not been applied together to predict size-resolved aerosol transport in multiroom buildings, or compared to real data.
-->The linked model will be a useful tool for examining the behavior of aerosols in multizone buildings and predicting concentrations and exposures as a function of particle size. The latter may be especially important for evaluating different strategies for reducing aerosol exposures within buildings.
@can also be used to aid in the design and interpretation of field experiments.
As proof of concept, we applied the models to predict the transport and behavior of tracer gas
and ETS particles measured in a three-room chamber. We obtained excellent agreement between the predicted and observed tracer gas concentrations in all three rooms. The predictions of both ETS particle mass and size-resolved particle
concentrations also agreed well with the measurements.
COMIS was particularly helpful for estimating the inter-room airflows caused by operating the
filter-sampling pumps, and therefore reduced the number of experiments needed to characterize the airflows.
From Literatures Study More:
Apte et al. (2004)
Test space description
Chamber layout and construction
A 50 m3 multizone environmental chamber was constructed within a temperature controlled single-story building at Lawrence Berkeley National Laboratory (LBNL). The chamber was designed to mimic conditions of a multi-room residential or office building where ETS might be generated in one room and transported to others. The layout of the chamber, shown in Figure 1, consisted of three rooms, a smoking room (SR), a connecting corridor (COR), and a non-smoking room (NSR). The chamber was built using wood frame construction with taped and painted gypsum wallboard walls and ceiling, and a high-quality nylon carpet laid over plywood sub-flooring in all three
chamber rooms. The entry and interconnecting doors were standard solid core wood design; however, magnetic refrigerator door seals (and accompanying steel flanges for the door openings) were added to the entire door perimeters to ensure near airtight sealing when the doors were fully closed. Low volatile organic compound (VOC) emitting
paints and sealants were used throughout the chamber in order to minimize the buildup of unwanted VOCs in the chambers. A plastic (PVC) membrane vapor barrier was placed behind the gypsum wallboard on the interior walls between the SR and the other two
chambers to retard any diffusion of ETS components through the wall materials between rooms. Fully closed, the baseline air exchange rate (λv) of the chamber and its composite sub-rooms was approximately 0.01 h-1.
Four 10- cm-diameter axial mixing fans were placed in each room, mounted at a height of approximately 1.5m above the floor, at about 1.5m along the diagonals between corners. The fan axes were horizontal and were oriented in opposing directions in order to
enhance the mixing within each room. The fan speed was controlled using a Variac transformer at a speed just high enough to achieve uniform mixing of gases, based upon previous chamber experiments.
Each chamber room was equipped with a set of small- and large-diameter sampling ports, each with a plug to close the ports not in use. The large sampling ports were just large enough to permit the insertion of a 47mm particle sampling filter holder, while the small
ports allowed for the insertion of nicotine sampling sorbent tubes into the chamber.
http://continuousimprovement.blogsome.com
Saturday, October 21, 2006
my cv
CURRICULUM VITAE
PERSONAL INFORMATION Surname(s) / First name(s) Purba / Lasman Parulian
Address(es) Wisma Kedung Asem Indah K.14 Surabaya, 60298.
Telephone 62-31-8703918, 62-81-55045980
Email Address Las.et.nic@gmail.com; lasman@stikom.edu; lasevinik@yahoo.com;
Blog http://continuousimprovement.blogsome.com
Nationality(-ies) Indonesia
Date of Birth 07th September 1974
Religion Christian
Gender/ Marital Status Male/ Married
WORK EXPERIENCE (08/05/00 – now)
Lecturer
Preparing lecture note and presentation; Delivering the material in front of the class as well as doing student examination; Supervising the internship students; Supervising students’ final project; Doing research in the area of computer controlled-systems; Committee member of some National Seminars that have been held in STIKOM.
(07/06/99 –16/07/99)
Observation Trainee in Control System Laboratory ITS Researching and implementing Proportional + Integral + Derivative (PID) Controller on PLC OMRON C200H type ASC02 and PID03;
Writing and presenting the Final Report.
(24/08/98 –25/08/98)
Observation Trainee in PT. SEMEN KUPANG, Kupang, Nusa Tenggara Timur
Observing the process of how to make cement;
Observing the implementation of the theory that had learnt in campus, especially for Programmable Logic Controller (PLC) subject;
Finding out optimization problem in factory; Proposing the problem solving for Final Report in front of the Factory Chairmen Board Forum.
EDUCATION BACKGROUND (dd/mm/yy – dd/mm/yy)
(postgraduate education) (name, place, country of institution)
(field of study)
(diploma or degree obtained)
(01/08/93 – 16/02/00)
(ITS Institut Teknologi Sepuluh Nopember Surabaya) Institut Teknologi Sepuluh Nopember Surabaya
ITS Surabaya, Jawa Timur, Indonesia
field of study: Electrical Engineering Major in Control System Engineering
Degree obtained: Bachelor (Sarjana Teknik, ST)
GPA: 2.81 (4 Scale)
(16/07/90 – 12/06/93)
(SMA 2 Pematang Siantar) SMA Negeri 2 Pematang Siantar, (Senior High School)
City: Pematang Siantar,
Prov.: Sumatera Utara (North Sumatra)
(…/07/87 –… /07/90)
(SMP 2 Pematang Siantar) SMP Negeri 2 Pematang Siantar, (Junior High School)
City: Pematang Siantar,
Prov.: Sumatera Utara (North Sumatra)
(…/07/81 – …/07/87)
(SMA 2 Pematang Siantar) SD Inpres No. 094154 Talun Kondot,
City: Pematang Siantar, Kab. Simalungun,
Prov.: Sumatera Utara (North Sumatra)
TRAINING, COURSE, SEMINAR & PUBLICATIONS 19 October 2006 Publish Book in Computer Controlled-System topic [Sistem Pengaturan dengan Komputer) from GRAHA ILMU Indonesia
21 September 2006 Public Speaking’s Seminar ”Become a Creative & Profesional Speaker” in cooperate with Suara Surabaya FM Radio and Hard Rock FM Radio.
26 Agustus 2006 Information System and Information Technology National Seminar (SNASTI2006)
24 Agustus 2006 Education System Seminar: KURIKULUM BERBASIS KOMPETENSI (supported by: University of Surabaya-STIKOM Surabaya)
23 Agustus 2006 Penulis Jurnal Kwalitas A versi DP2M DIKTI Indonesia dalam Acara Competition Handout Book
Agustus 2006 Participan on Writing Competition of Text Book by Private University Lecturer Se-Indonesia 2006
As in RGB Tabloid: Agustus2006 Edition Colomnis ’Ethics in Information Age’ (Tabloid ’RedGreenBlue/ RGB’).
Januari 2006 – 26 Agustus2006 (end) Komite Pelaksana Seminar Nasional Teknologi dan Informasi Nasional (SNASTI2006)/ Member of Committee National Scientific Seminar on Informatin System and Information Technology
…/08.06 Lomba Mengetik Bahasa Inggris antar Bagian di STIKOM Surabaya
Agustus 2006 “Sistem Pengaturan dengan Komputer” Edisi SATU, Proses Penerbitan GRAHA ILMU
Juni 2005 - Nopember 2005 FreelancePembuatan Buku Besar, Jurnal Harian, Jurnal Bulanan, Laporan Rugi Laba dan Analisi Pajak, PT. STSJ Surabaya
(01/03/05 – 31/08/05)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Algoritma Dijkstra untuk Pemantauan Lalu Lintas dan Pelacakan Jalur Alternatif Optimal
(11/06/05 – 11/06/05)
Proceeding of Seminar on ReTII2005, STTNasional Yogyakarta, Indonesia/ National.
Performansi Dua Buah Motor DC Berdasarkan Identifikasi Dinamis untuk Digunakan Sebagai Penggerak Robot Line Follower
(02/05/05 – 02/05/05)
SITIA2005 Seminar on Inteligent Technology and Its Application/ National.
Kompas Jalur Pendek: Suatu Detektor Lintasan Terpendek Berbasis Mikrokontroler
(01/09/04 – 28/02/05)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Sistem Identifikasi Model Dinamika Motor DC untuk Digunakan pada Desain Controller
(26/01/05 – 27/01/05)
Held byUBAYA Surabaya - UK PETRA Surabaya / Regional Course.
Active Trainee in RESEARCH PROPOSAL ARRANGEMENT TRAINING held by Groups of Private Research League East Java, Surabaya Indonesia
(19/08/04 -21/08/04)
STIKOM/ Local Course.
Active Participant in APPLIED APPROACH TRAINING held by Pusat Pembinaan dan Pengembangan Pendidikan UNESA
(01/03/04 – 31/08/04)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Sistem Identifikasi Model Motor DC untuk Digunakan pada Desain PID Controller
(25/05/04 – 26/05/04)
Proceeding of ECCIS2004 Seminar on Electrical Communication Control Information System, Brawijaya University/ National.
Perancangan dan Pembuatan Pengontrol PID-Optimal Berdasarkan Kriteria Performansi Kwadratik untuk Pengendalian Motor DC
(25/05/04 – 26/05/04)
Proceeding of ECCIS2004 Seminar on Electrical Communication Control Information System, Brawijaya University/ National.
Sistem Pengendalian Posisi Motor DC Servo dengan Algoritma Adaptive Neuro Fuzzy Inference Systems (ANFIS)
(03/05/04 – 03/05/04)
Proceeding of SITIA2004 Seminar on Intelligent Technology and It’s Applications, ITS/ National.
Sistem Pengendalian Posisi Motor DC dengan Menggunakan JST dengan Algoritma Belajar Error Back Propagation
(01/09/03 – 29/02/04)
Journal of Computer Engineering GEMATEK, STIKOM/ National (Vol. 5 No. 2 Tahun 2003).
Sistem Kendali Motor DC Berbasis Komputer dengan Menggunakan Jaringan Syaraf Tiruan
(19/09/03 – 19/09/03)
Seminar Local STIKOM;
Active Participant in Seminar ‘Smart Better Communication’ by Baby Joewono
(16/09/03 – 16/09/03)
DES2003 Deuleureon Extreme Science 2003, STIKOM/ Regional.
Tips & Trik Pemilihan Kontroler yang Tepat dengan Performansi Terbaik untuk Plant Motor DC
(01/03/03 – 31/08/03)
Journal of Computer Engineering GEMATEK, STIKOM/ National (Vol.5 No. 1 Tahun 2003).
Aplikasi Simulasi Pengendalian Manipulator Robot dengan Algoritma Pembelajaran Hibrida Fungsi Basis Radial, Simualation and Control Robot with Hibrida Radial Basis Function Networks.
(04/06/03 – 04/06/03)
Course Local STIKOM.
Active Participant in Course ‘Quality Assurance: Educational System to Increase Quality Alumni” by Prof. Ir. Sudjarwadi, M.Eng., Ph.D (From Gadjah Mada University)
(15/03/03 – 16/03/03)
Regional Training,
Active Trainee in RESEARCH PROPOSAL ARRANGEMENT TRAINING held by Research League of Airlangga University
(30/10/02 – 30/10/02)
Regional Training,
Active Participant in LOKAKARYA PENGEMBANGAN PROGRAM Co-Op (CO-OPERATIVE ACADEMIC EDUCATION) that held by ITS in Cooperation with DPPKPM-DIKTI (Directorate of Higher Education)
(18/09/02 – 18/09/02)
DES2002 Deuleureon Extreme Science 2002, STIKOM/ Regional Seminar.
Aplikasi Kontrol Neuro-Fuzzy pada Industri
(01/03/02 – 31/08/02)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Kontroller PID Berbasis MATLAB 6.1 : Sebuah Informasi Tutorial (PID Controller MATLAB 6.1-Based: A Tutorial Information)
(14/03/02 - 17/03/02)
IKPN/ National Course.
Active Participant in ‘Institut Kepemimpinan Para Navigator Indonesia’
(14/09/01 – 14/09/01)
Electrical Engineering PETRA Christian Univ. Surabaya/ Seminar/ Regional.
Active Participant in topical Seminar: Applikasi Intelligent Control pada Industri.
(07/03/01 – 08/03/01)
CECI2001 International Conference on Electrics, Electronics, Communications and Informations, BPPT-Jakarta/ International.
Control Robot Manipulators with Hybrid Learning Algorithm Radial Basis Function Networks in Operational Space
(08/02/01 – 09/02/01)
Develop how to Supervising Internship Students/ STIKOM/ Local.
Active Participant in “Pelatihan dan Pengembangan Dosen Wali”
(29/05/01 – 02/06/01)
Seminar Nasional & Pameran Multimedia, STIKOM
Active Participant in Seminar ’Multimedia Interaktif: Media Baru untuk Meningkatkan Publikasi’
(02/10/00 – 02/10/00)
WMNet2000, World Media Network,Univ. Wangsa Manggala Yogyakarta/ National.
Perancangan Pengendalian Manipulator Robot Di Operational Space Dengan Algoritma Pembelajaran Hibrida Jaringan Syaraf Tiruan Fungsi Basis Radial. (Design of Control Robot Manipulators in Operational Space with Hybrid Learning Algorithm Radial Basis Function Networks).
(26/07/99 -05/9/99)
Acara Latihan 1999/ Nasional Course.
Active Participant in ”Acara Latihan Kampus Nasional Para Navigator 1999”
(19/05/00 – 19/05/00)
SITIA2000 Seminar on Intelligent Technology and It’s Applications, ITS/ National.
Pengendalian Manipulator Robot Di Operational Space Dengan Jaringan Syaraf Tiruan Fungsi Basis Radial
(Control Robot Manipulators in OperationalSpace with Radial Basis Function Networks )
PERSONAL SKILLS & COMPETENCES Organisation Skill and competences:
Planner, Organizing Committee National Scientific Seminar, Steering Committee
Artistic Skills and competences:
Music, Singing, Dancing
Computer:
Simulation software: MATLAB, Ladder Support System, FRANKLIN, FIXDMAX,
Operating systems: Windows95, Windows98, Windows2000, WindowsXP, DOS, Windows Advance Server2000, Windows Professional 2000,
Office applications: MS Word, Power Point, MS Excel, MS Access, MS Frontpage, InternetAcccess, MS Outlook,
Others: C/ C++, PASCAL, BASIC, FORTRAN, Delphi ,Visual Basic FLUENT (in process),
Interpersonal:
Leadership Skill, Interpesonal Skill…
Driving License:
SIM C (Motorcycle Driving Licence), SIM A (in Process)
Profesional Member/ Mailing List *SoftComputingIndonesia: sc-ina@yahoogroups.com
*Information Technology and Information System Indonesia (Internasional): rsiti@yahoogroups.com
*Centre for Inttellectual Property Right Indonesia: SentraHaKI@yahoogroups.com
*MASyarakat Sistem KenDALI Indonesia: MASDALI
I declared all information in these curriculum vitae is true
www.life4family.blogspot.com
www.continuousimprovement.blogspot.com
PERSONAL INFORMATION Surname(s) / First name(s) Purba / Lasman Parulian
Address(es) Wisma Kedung Asem Indah K.14 Surabaya, 60298.
Telephone 62-31-8703918, 62-81-55045980
Email Address Las.et.nic@gmail.com; lasman@stikom.edu; lasevinik@yahoo.com;
Blog http://continuousimprovement.blogsome.com
Nationality(-ies) Indonesia
Date of Birth 07th September 1974
Religion Christian
Gender/ Marital Status Male/ Married
WORK EXPERIENCE (08/05/00 – now)
Lecturer
Preparing lecture note and presentation; Delivering the material in front of the class as well as doing student examination; Supervising the internship students; Supervising students’ final project; Doing research in the area of computer controlled-systems; Committee member of some National Seminars that have been held in STIKOM.
(07/06/99 –16/07/99)
Observation Trainee in Control System Laboratory ITS Researching and implementing Proportional + Integral + Derivative (PID) Controller on PLC OMRON C200H type ASC02 and PID03;
Writing and presenting the Final Report.
(24/08/98 –25/08/98)
Observation Trainee in PT. SEMEN KUPANG, Kupang, Nusa Tenggara Timur
Observing the process of how to make cement;
Observing the implementation of the theory that had learnt in campus, especially for Programmable Logic Controller (PLC) subject;
Finding out optimization problem in factory; Proposing the problem solving for Final Report in front of the Factory Chairmen Board Forum.
EDUCATION BACKGROUND (dd/mm/yy – dd/mm/yy)
(postgraduate education) (name, place, country of institution)
(field of study)
(diploma or degree obtained)
(01/08/93 – 16/02/00)
(ITS Institut Teknologi Sepuluh Nopember Surabaya) Institut Teknologi Sepuluh Nopember Surabaya
ITS Surabaya, Jawa Timur, Indonesia
field of study: Electrical Engineering Major in Control System Engineering
Degree obtained: Bachelor (Sarjana Teknik, ST)
GPA: 2.81 (4 Scale)
(16/07/90 – 12/06/93)
(SMA 2 Pematang Siantar) SMA Negeri 2 Pematang Siantar, (Senior High School)
City: Pematang Siantar,
Prov.: Sumatera Utara (North Sumatra)
(…/07/87 –… /07/90)
(SMP 2 Pematang Siantar) SMP Negeri 2 Pematang Siantar, (Junior High School)
City: Pematang Siantar,
Prov.: Sumatera Utara (North Sumatra)
(…/07/81 – …/07/87)
(SMA 2 Pematang Siantar) SD Inpres No. 094154 Talun Kondot,
City: Pematang Siantar, Kab. Simalungun,
Prov.: Sumatera Utara (North Sumatra)
TRAINING, COURSE, SEMINAR & PUBLICATIONS 19 October 2006 Publish Book in Computer Controlled-System topic [Sistem Pengaturan dengan Komputer) from GRAHA ILMU Indonesia
21 September 2006 Public Speaking’s Seminar ”Become a Creative & Profesional Speaker” in cooperate with Suara Surabaya FM Radio and Hard Rock FM Radio.
26 Agustus 2006 Information System and Information Technology National Seminar (SNASTI2006)
24 Agustus 2006 Education System Seminar: KURIKULUM BERBASIS KOMPETENSI (supported by: University of Surabaya-STIKOM Surabaya)
23 Agustus 2006 Penulis Jurnal Kwalitas A versi DP2M DIKTI Indonesia dalam Acara Competition Handout Book
Agustus 2006 Participan on Writing Competition of Text Book by Private University Lecturer Se-Indonesia 2006
As in RGB Tabloid: Agustus2006 Edition Colomnis ’Ethics in Information Age’ (Tabloid ’RedGreenBlue/ RGB’).
Januari 2006 – 26 Agustus2006 (end) Komite Pelaksana Seminar Nasional Teknologi dan Informasi Nasional (SNASTI2006)/ Member of Committee National Scientific Seminar on Informatin System and Information Technology
…/08.06 Lomba Mengetik Bahasa Inggris antar Bagian di STIKOM Surabaya
Agustus 2006 “Sistem Pengaturan dengan Komputer” Edisi SATU, Proses Penerbitan GRAHA ILMU
Juni 2005 - Nopember 2005 FreelancePembuatan Buku Besar, Jurnal Harian, Jurnal Bulanan, Laporan Rugi Laba dan Analisi Pajak, PT. STSJ Surabaya
(01/03/05 – 31/08/05)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Algoritma Dijkstra untuk Pemantauan Lalu Lintas dan Pelacakan Jalur Alternatif Optimal
(11/06/05 – 11/06/05)
Proceeding of Seminar on ReTII2005, STTNasional Yogyakarta, Indonesia/ National.
Performansi Dua Buah Motor DC Berdasarkan Identifikasi Dinamis untuk Digunakan Sebagai Penggerak Robot Line Follower
(02/05/05 – 02/05/05)
SITIA2005 Seminar on Inteligent Technology and Its Application/ National.
Kompas Jalur Pendek: Suatu Detektor Lintasan Terpendek Berbasis Mikrokontroler
(01/09/04 – 28/02/05)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Sistem Identifikasi Model Dinamika Motor DC untuk Digunakan pada Desain Controller
(26/01/05 – 27/01/05)
Held byUBAYA Surabaya - UK PETRA Surabaya / Regional Course.
Active Trainee in RESEARCH PROPOSAL ARRANGEMENT TRAINING held by Groups of Private Research League East Java, Surabaya Indonesia
(19/08/04 -21/08/04)
STIKOM/ Local Course.
Active Participant in APPLIED APPROACH TRAINING held by Pusat Pembinaan dan Pengembangan Pendidikan UNESA
(01/03/04 – 31/08/04)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Sistem Identifikasi Model Motor DC untuk Digunakan pada Desain PID Controller
(25/05/04 – 26/05/04)
Proceeding of ECCIS2004 Seminar on Electrical Communication Control Information System, Brawijaya University/ National.
Perancangan dan Pembuatan Pengontrol PID-Optimal Berdasarkan Kriteria Performansi Kwadratik untuk Pengendalian Motor DC
(25/05/04 – 26/05/04)
Proceeding of ECCIS2004 Seminar on Electrical Communication Control Information System, Brawijaya University/ National.
Sistem Pengendalian Posisi Motor DC Servo dengan Algoritma Adaptive Neuro Fuzzy Inference Systems (ANFIS)
(03/05/04 – 03/05/04)
Proceeding of SITIA2004 Seminar on Intelligent Technology and It’s Applications, ITS/ National.
Sistem Pengendalian Posisi Motor DC dengan Menggunakan JST dengan Algoritma Belajar Error Back Propagation
(01/09/03 – 29/02/04)
Journal of Computer Engineering GEMATEK, STIKOM/ National (Vol. 5 No. 2 Tahun 2003).
Sistem Kendali Motor DC Berbasis Komputer dengan Menggunakan Jaringan Syaraf Tiruan
(19/09/03 – 19/09/03)
Seminar Local STIKOM;
Active Participant in Seminar ‘Smart Better Communication’ by Baby Joewono
(16/09/03 – 16/09/03)
DES2003 Deuleureon Extreme Science 2003, STIKOM/ Regional.
Tips & Trik Pemilihan Kontroler yang Tepat dengan Performansi Terbaik untuk Plant Motor DC
(01/03/03 – 31/08/03)
Journal of Computer Engineering GEMATEK, STIKOM/ National (Vol.5 No. 1 Tahun 2003).
Aplikasi Simulasi Pengendalian Manipulator Robot dengan Algoritma Pembelajaran Hibrida Fungsi Basis Radial, Simualation and Control Robot with Hibrida Radial Basis Function Networks.
(04/06/03 – 04/06/03)
Course Local STIKOM.
Active Participant in Course ‘Quality Assurance: Educational System to Increase Quality Alumni” by Prof. Ir. Sudjarwadi, M.Eng., Ph.D (From Gadjah Mada University)
(15/03/03 – 16/03/03)
Regional Training,
Active Trainee in RESEARCH PROPOSAL ARRANGEMENT TRAINING held by Research League of Airlangga University
(30/10/02 – 30/10/02)
Regional Training,
Active Participant in LOKAKARYA PENGEMBANGAN PROGRAM Co-Op (CO-OPERATIVE ACADEMIC EDUCATION) that held by ITS in Cooperation with DPPKPM-DIKTI (Directorate of Higher Education)
(18/09/02 – 18/09/02)
DES2002 Deuleureon Extreme Science 2002, STIKOM/ Regional Seminar.
Aplikasi Kontrol Neuro-Fuzzy pada Industri
(01/03/02 – 31/08/02)
Journal of Computer Engineering GEMATEK, STIKOM/ National.
Kontroller PID Berbasis MATLAB 6.1 : Sebuah Informasi Tutorial (PID Controller MATLAB 6.1-Based: A Tutorial Information)
(14/03/02 - 17/03/02)
IKPN/ National Course.
Active Participant in ‘Institut Kepemimpinan Para Navigator Indonesia’
(14/09/01 – 14/09/01)
Electrical Engineering PETRA Christian Univ. Surabaya/ Seminar/ Regional.
Active Participant in topical Seminar: Applikasi Intelligent Control pada Industri.
(07/03/01 – 08/03/01)
CECI2001 International Conference on Electrics, Electronics, Communications and Informations, BPPT-Jakarta/ International.
Control Robot Manipulators with Hybrid Learning Algorithm Radial Basis Function Networks in Operational Space
(08/02/01 – 09/02/01)
Develop how to Supervising Internship Students/ STIKOM/ Local.
Active Participant in “Pelatihan dan Pengembangan Dosen Wali”
(29/05/01 – 02/06/01)
Seminar Nasional & Pameran Multimedia, STIKOM
Active Participant in Seminar ’Multimedia Interaktif: Media Baru untuk Meningkatkan Publikasi’
(02/10/00 – 02/10/00)
WMNet2000, World Media Network,Univ. Wangsa Manggala Yogyakarta/ National.
Perancangan Pengendalian Manipulator Robot Di Operational Space Dengan Algoritma Pembelajaran Hibrida Jaringan Syaraf Tiruan Fungsi Basis Radial. (Design of Control Robot Manipulators in Operational Space with Hybrid Learning Algorithm Radial Basis Function Networks).
(26/07/99 -05/9/99)
Acara Latihan 1999/ Nasional Course.
Active Participant in ”Acara Latihan Kampus Nasional Para Navigator 1999”
(19/05/00 – 19/05/00)
SITIA2000 Seminar on Intelligent Technology and It’s Applications, ITS/ National.
Pengendalian Manipulator Robot Di Operational Space Dengan Jaringan Syaraf Tiruan Fungsi Basis Radial
(Control Robot Manipulators in OperationalSpace with Radial Basis Function Networks )
PERSONAL SKILLS & COMPETENCES Organisation Skill and competences:
Planner, Organizing Committee National Scientific Seminar, Steering Committee
Artistic Skills and competences:
Music, Singing, Dancing
Computer:
Simulation software: MATLAB, Ladder Support System, FRANKLIN, FIXDMAX,
Operating systems: Windows95, Windows98, Windows2000, WindowsXP, DOS, Windows Advance Server2000, Windows Professional 2000,
Office applications: MS Word, Power Point, MS Excel, MS Access, MS Frontpage, InternetAcccess, MS Outlook,
Others: C/ C++, PASCAL, BASIC, FORTRAN, Delphi ,Visual Basic FLUENT (in process),
Interpersonal:
Leadership Skill, Interpesonal Skill…
Driving License:
SIM C (Motorcycle Driving Licence), SIM A (in Process)
Profesional Member/ Mailing List *SoftComputingIndonesia: sc-ina@yahoogroups.com
*Information Technology and Information System Indonesia (Internasional): rsiti@yahoogroups.com
*Centre for Inttellectual Property Right Indonesia: SentraHaKI@yahoogroups.com
*MASyarakat Sistem KenDALI Indonesia: MASDALI
I declared all information in these curriculum vitae is true
www.life4family.blogspot.com
www.continuousimprovement.blogspot.com
Wednesday, August 02, 2006
[resource-yg-mantap]anggota milis profesional
rsiti@yahoogroups.com -->milis risit sistem informasi dan teknologi informasi INDONESIA moderator: Pak IBAM dari UI + Pak Husni ITS
sc-ina@yahoogroups.com -->milis komunitas soft-computing indonesia moderator: Pak Son Kuswadi (Rabbit PENS ITS) + Pak Anto Satriyo Nugroho sedang study s3? di jepang
http://life4family.blogspot.com
http://continuousimprovement.blogsome.com
sc-ina@yahoogroups.com -->milis komunitas soft-computing indonesia moderator: Pak Son Kuswadi (Rabbit PENS ITS) + Pak Anto Satriyo Nugroho sedang study s3? di jepang
http://life4family.blogspot.com
http://continuousimprovement.blogsome.com
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