what is adiabatic?

2nd Law of Thermodynamics
The second law is concerned with entropy, which is a measure of disorder. The second law says that the entropy of the universe increases

There are two classical statements of the second law of thermodynamics:
Kelvin & Planc"No (heat) engine whose working fluid undergoes a cycle can absorb heat from a single reservoir, deliver an equivalent amount of work, and deliver no other effect"
Clausius"No machine whose working fluid undergoes a cycle can absorb heat from one system, reject heat to another system and produce no other effect"
Both statements of the second law place constraints on the first law by identifying that energy goes downhill.
The second law is concerned with entropy (S), which is a measure of disorder. The second law says that the entropy of the universe increases. An increase in overall disorder is therefore spontaneous. If the volume and energy of a system are constant, then every change to the system increases the entropy. If volume or energy change, then the entropy of the system actually decrease. However, the entropy of the universe does not decrease.
For energy to be available there must be a region with high energy level and a region with low energy level. Useful work must be derived from the energy that would flows from the high level to the low level.
100% of the energy can not be transformed to work
Entropy can be produced but never destroyed
Efficiency of a heat machine
The efficiency of a heat machine working between two energy levels is defined in terms of absolute temperature:
η = ( Th - Tc ) / Th = 1 - Tc / Th(1)
where
η = efficiency
Th = temperature high level (K)
Tc = temperature low level (K)
As a consequence, to attain maximum efficiency the Tc would have to be as cold as possible. For 100% efficiency the Tc would have to equal 0 K. This is practically impossible, so the efficiency is always less than 1 (less than 100%).
Change in entropy > 0, irreversible process
Change in entropy = 0, reversible process
Change in entropy < 0, impossible process
Entropy is used to define the unavailable energy in a system. Entropy defines the relative ability of one system to act to an other. As things moves toward a lower energy level, where one is less able to act upon the surroundings, the entropy is said to increase.
For the universe as a whole the entropy is increasing!
Entropy definition
Entropy is defined as :
S = H / T (2)
where
S = entrophy (kJ/kg K)
H = enthalpy (kJ/kg)
T = absolute temperature (K)
A change in the entropy of a system is caused by a change in its heat content, where the change of entropy is equal to the heat change divided by the average absolute temperature (Ta):
dS = dH / Ta (3)
The sum of (H / T) values for each step in the Carnot cycle equals 0. This only happens because for every positive H there is a countering negative H, overall.
Carnot Heat CycleIn a heat engine, a gas is reversibly heated and then cooled. A model of the cycle is as follows: State 1 --(isothermal expansion) --> State 2 --(adiabatic expansion) --> State 3 --(isothermal compression) --> State 4 --(adiabatic compression) --> State 1State 1 to State 2: Isothermal ExpansionIsothermal expansion occurs at a high temperature Th, dT = 0 and dE1 = 0. Since dE = H + w, w1 = - H1. For ideal gases, dE is dependent on temperature only.State 2 to State 3: Adiabatic ExpansionThe gas is cooled from the high temperature, Th, to the low temperature, Tc. dE2 = w2 and H2 = 0 (adiabatic).State 3 to State 4: Isothermal CompressionThis is the reverse of the process between states 1 and 2. The gas is compressed at Tc. dT = 0 and dE3 = 0. w3 = - H3State 4 to State 1: Adiabatic CompressionThis is the reverse of the process between states 2 and 3. dE4 = w4 and H4 = 0 (adiabatic).The processes in the Carnot cycle can be graphed as the pressure vs. the volume. The area enclosed in the curve is then the work for the Carnot cycle because w = - integral (P dV). Since this is a cycle, dE overall equals 0. Therefore,-w = H = H1 + H2 + H3 + H4If you decrease Tc, then the quantity -w gets larger in magnitude.if -w > 0 then H > 0 and the system, the heat engine, does work on the surroundings.
The laws of thermodynamics were determined empirically (by experiment). They are generalizations of repeated scientific experiments. The second law is a generalization of experiments dealing with entropy--it is that the dS of the system plus the dS of the surroundings is equal to or greater then 0.
Entropy is not conserved like energy!
Example - Entropy Heating Water
A process raises 1 kg of water from 0 to 100oC (273 to 373 K) under atmospheric conditions.Specific enthalpy at 0oC (hf) = 0 kJ/kg (from steam tables) (Specific - per unit mass)Specific enthalpy of water at 100oC (hf) = 419 kJ/kg (from steam tables)
Change in specific entropy:
dS = dH / Ta
= (419 - 0) / ((273 + 373)/2)
= 1.297 kJ/kgK
Example - Entropy Evaporation Water to Steam
A process changes 1 kg of water at 100oC (373 K) to saturated steam at 100oC (373 K) under atmospheric conditions.Specific enthalpy of steam at 100oC (373 K) before evaporating = 0 kJ/kg (from steam tables)
Specific enthalpy of steam at 100oC (373 K) after evaporating = 2 258 kJ/kg (from steam tables)Change in specific entropy:
dS = dH / Ta
= (2 258 - 0) / ((373 + 373)/2)
= 6.054 kJ/kgK
The total change in specific entropy from water at 0oC to saturated steam at 100oC is the sum of the change in specific entropy for the water, plus the change of specific entropy for the steam.
Example - Entropy Superheated Steam
A process superheats 1 kg of saturated steam at atmospheric pressure to 150oC (423 K).
Specific total enthalpy of steam at 100oC (373 K) = 2 675 kJ/kg (from steam tables)Specific total enthalpy of superheated steam at 150oC (373 K) = 2 777 kJ/kg (from steam tables)
Change in specific entropy:
dS = dH / Ta
= (2 777 - 2 675) / ((423 + 373)/2)
= 0.256 kJ/kgK
Entropy table for superheated steam [http://www.engineeringtoolbox.com/superheated-steam-entropy-d_100.html]

If saturated steam is exposed to a surface with a higher temperature, its temperature will increase above the evaporating temperature. The steam is then described as superheated by the temperature degrees above saturation temperature.
Note! Steam cannot be superheated whilst it is still in the contact with water, because additional heat will evaporate more water, cooling down the superheated steam.
Superheated steam is produced by passing saturated steam through an additional heat exchanger.
Superheated steam is also called
surcharged steam
anhydrous steam
steam gas

taken from: http://www.engineeringtoolbox.com/law-thermodynamics-d_94.html as 23April2007

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resources for FLUENT: *.MSH

RESOURCES file *.MSH for Tutorial FLUENT 6.X
http://www.liv.ac.uk/~em22/CFD/data/

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resources in standard deviation

how to calculate standard deviation:
http://faculty.tamu-commerce.edu/crrobinson/517/sdcalc.htm

calculator for statistics in internet:
http://www.easycalculation.com/statistics/learn-geometric-mean.php

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example: calculating a standard deviation

x x*x
data1 79 6241
data2 85 7225
data3 92 8464
data4 87 7569
data5 93 8649
data6 99 9801
sum 535 47949
ave 89.16666667 7991.5
ave^2 7950.694444

std_dev^2 40.80555556 =7991.5-7950.694
std_dev 6.39 =square root of 40.81

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calculating std dev

Calculating a Standard Deviation

According to Drummond & Jones (2006), a standard deviation "is the numerical value that describes the spread of scores away from the mean and is expressed in the same units as the original scores. The wider the spread of scores, the larger the standard deviation."

A standard deviation is calculated by subtracting the mean of a distribution from the value of each individual variable in the distribution, squaring each resulting difference, summing these squared differences, then dividing this sum by the number of variables, and finally taking the square root of this quotient. The formula for this process is often represented as follows:



Alternately, Drummond & Jones (2006) use s in place of s . They also suggest the following formula as a more convenient means of calculating a standard deviation:



Now, apply this formula to calculate a standard deviation for the following distribution:

X1 = 79

X2 = 85

X3 = 92

X4 = 87

X5 = 93

X6 = 99

There are several intermediate calculations which must be performed before proceeding to the standard deviation calculation. Let's calculate the mean first. Remember that the mean is calculated by summing the variables then dividing by the number (count) of variables included in the distribution. In this instance the sum of the variables (79+85+92+87+93+99) equals 535. The count equals 6. When we divide 535 by 6, we get a quotient of 89.17. This is the mean for this distribution. Let's go ahead and square the mean, getting a value of 7951.29. Next, let's square each variable, then sum them [(79 x 79)+(85 x 85)+(92 x 92)+(87 x 87)+(93 x 93)+(99 x 99)]. Performing this calculation yields a value of 47,949. Then, we divide this value by 6, giving us 7991.5. Now, we can subtract the squared mean (7951.29) from 7991.5. This gives us a value of 40.21. Finally, we must take the square root of this value, arriving at our standard deviation value of 6.34.

Following the formula mathematically looks like this:
















When we have a small sample (typically 20 or fewer variables) it is generally recommended that we substitute n-1 for n so that the standard deviation is not underestimated. Let's calculate a standard deviation using the original formula shown above, but substituting n-1 in place of n. We'll use the same variables as before. Remember, the mean equals 89.17. First, let's subtract the mean from each variable value: 79 - 89.17 = -10.17, 85 - 89.17 = -4.17, 92 - 89.17 = 2.83, 87 - 89.17 = -2.17, 93 - 89.17 = 3.83, and 99 - 89.17 = 9.83. Of course, 6-1 (n-1) equals 5. Next, we'll square these differences with the following respective results: 103.43, 17.39, 8.01, 4.71, 14.67, and 96.63. Then, let's sum those squares obtaining 244.84, divide by 5 (n-1 which is 6-1), obtaining 48.97 and take the square root of that quotient, giving us a standard deviation of 6.998, or 7.

Here it is presented mathematically:







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