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Difference between intensive and extensive property state variable , state function and path function ? sample space , trial , enthalpy , free energy and event?

(Lec 5-6 )

Difference between intensive and extensive property ?

INTENSIVE PROPERTY EXTENSIVE PROPERTY
The property which don’t depend on mass (free from size   and shape ) .The property which depend on mass (shape and size ) .
For example : temperature , pressure , rowh e.t.cFor example : Mass , Energy , volume , Entholpy  e.t.c.

Difference between state variable , state function and path function ?

STATE VARIABLESTATE FUNCTIONPATH FUNCTION
The variable with define the state of system is called STATE VARIABLE .’’The function whose value depend on initial and final state of a system independent of path following to change the state it does not depend on the past history it only depends on state of a system is called’’ STATE FUNCTION .’’Those functions which are dependent on path followed to reach that state are called ‘’ PATH FUNCTION ‘’
For example : Temperature , pressure , volume e.t.cFor example : all types of energies ( G,F,U,V,T).For example : Work , Heat .

FREE ENERGY :

The energy of thermodynamic system which can be converted into useful work is called free energy and it depends on some conditions constraints.

TYPES / cases :

(i) Internal Energy : from first law of thermodynamics

dQ= dU + PdV

dQ – PdV = dU

dU = dQ – P dV (eq 1 )

we know that dS = dQ /T

TdS = dQ (eq 2 )

putting 2 in 1 eq we get

dU = TdS -PdV eq 3 {useful relation }

U=U(S,V)

dU = ( dU /dS )V dS + ( dU /dV ) S dV ( eq 4 )

comare eq 3 and 4 we get

T=dU/dS , P = -dU/dV

here U is known as thermodynamical potential .

(ii) Enthalpy :

H=U+PV ( eq 1 )

dH = dU +PdV+ V dP [differentiate eq 1 ]

putting dU value in above equation from case 1

dH = TdS –PdV +PdV +VdP

dH = TdS + U dP (eq 2 )

H = H(S,P)

dH = ( dH/dS )P dS+ ( dH/dP )S dP ( eq 3)

compareing eq 3 and 2 we get

T = (dH/dS )p ,V = ( dH/dP )s

where H is termodynamical potential .

(iii) Helmholtz free Energy .

F=U-TS

dF =dU -TdS (eq 1 )

dF = TdS -PdV –TdS -SdT

dF = -PdV -S dT ( eq 2 )

F = ( V , T )

dF = ( dF /dV )t dT +(dF / dT )v dV ( eq 3 )

compare 2 and eq 3

P ( -dF /dV )p ,S = (-dF/dT)

where F is thermodynamical potential .

(iv) Gibbs’s Free Energy .

G=U+PV -TS (eq 1 0

differentiate above eq

dG = dU + PdV -TdS +VdP +SdT

putting value of dU in above eq

dG = TdSPdV +PdVTdS +VdP + SdT

dG = VdP +SdT (eq 2)

G= G(V,S )

dG + (dG/dV) dT + ( dG /dS ) dT ( eq 3 )

comapre eq 2 and eq 3 we get

= V = ( dG /dP )P and S = (dG /dT )P

here G is thermodynamical potential .

Some basic Concepts

TRIAL :

Any experiment having unpredictable outcome is called trial.

for example = (i)executed performed according to the few present values. (ii)it should be repeated arbitary or randamly .

EVENT :

Possible outcome of any trial is called event.

for example = easy tossing a coin in this case possible outcomes head and tail.
SAMPLE SPACE :

Set of all possible outcomes of trial. ” or ” sample space is a collection or set of all possible outcomes of random experiment denoted by ”S” .

In case of tossing a coin S ={H,T} .

In case of throwing a dice ,S={1,2,3,4,5,6}

types of events

MUTUALLY EXCLUSIVE EVENT : two events aur mutually exclusive events if they cannot occurred same time.

By much will you save you mean that if one event occur than another cannot .

for example =you tossing a coin either it is head or tail.

EXHAUSTIVE EVENTS :

Total number of possible outcomes in a trial .

EQUALLY LIKELY EVENT :

that has some thoretical probability (or likehood )of occurring .

example = number on a dice is equally like occur when the dice is tossed .

COMPOUND EVENTS :compound events are two or more events that happen together .

for example =two coins are flipped or coin is flipped and then flipped a second time.

RANDOM EVENTs :

If we cannot predict the occurance of any event before it’s happening then we call it random events.

FAVOURIBLE EVENTS :

The event which will give you surely of occurance of any event is called favourable event .

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