Chapter 5 Thermodynamic Properties of Real Fluids
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On Entropy, Information, and Conservation of Information
entropy Article On Entropy, Information, and Conservation of Information Yunus A. Çengel Department of Mechanical Engineering, University of Nevada, Reno, NV 89557, USA; [email protected] Abstract: The term entropy is used in different meanings in different contexts, sometimes in contradic- tory ways, resulting in misunderstandings and confusion. The root cause of the problem is the close resemblance of the defining mathematical expressions of entropy in statistical thermodynamics and information in the communications field, also called entropy, differing only by a constant factor with the unit ‘J/K’ in thermodynamics and ‘bits’ in the information theory. The thermodynamic property entropy is closely associated with the physical quantities of thermal energy and temperature, while the entropy used in the communications field is a mathematical abstraction based on probabilities of messages. The terms information and entropy are often used interchangeably in several branches of sciences. This practice gives rise to the phrase conservation of entropy in the sense of conservation of information, which is in contradiction to the fundamental increase of entropy principle in thermody- namics as an expression of the second law. The aim of this paper is to clarify matters and eliminate confusion by putting things into their rightful places within their domains. The notion of conservation of information is also put into a proper perspective. Keywords: entropy; information; conservation of information; creation of information; destruction of information; Boltzmann relation Citation: Çengel, Y.A. On Entropy, 1. Introduction Information, and Conservation of One needs to be cautious when dealing with information since it is defined differently Information. Entropy 2021, 23, 779. -
Thermodynamic Potentials and Natural Variables
Revista Brasileira de Ensino de Física, vol. 42, e20190127 (2020) Articles www.scielo.br/rbef cb DOI: http://dx.doi.org/10.1590/1806-9126-RBEF-2019-0127 Licença Creative Commons Thermodynamic Potentials and Natural Variables M. Amaku1,2, F. A. B. Coutinho*1, L. N. Oliveira3 1Universidade de São Paulo, Faculdade de Medicina, São Paulo, SP, Brasil 2Universidade de São Paulo, Faculdade de Medicina Veterinária e Zootecnia, São Paulo, SP, Brasil 3Universidade de São Paulo, Instituto de Física de São Carlos, São Carlos, SP, Brasil Received on May 30, 2019. Revised on September 13, 2018. Accepted on October 4, 2019. Most books on Thermodynamics explain what thermodynamic potentials are and how conveniently they describe the properties of physical systems. Certain books add that, to be useful, the thermodynamic potentials must be expressed in their “natural variables”. Here we show that, given a set of physical variables, an appropriate thermodynamic potential can always be defined, which contains all the thermodynamic information about the system. We adopt various perspectives to discuss this point, which to the best of our knowledge has not been clearly presented in the literature. Keywords: Thermodynamic Potentials, natural variables, Legendre transforms. 1. Introduction same statement cannot be applied to the temperature. In real fluids, even in simple ones, the proportionality Basic concepts are most easily understood when we dis- to T is washed out, and the Internal Energy is more cuss simple systems. Consider an ideal gas in a cylinder. conveniently expressed as a function of the entropy and The cylinder is closed, its walls are conducting, and a volume: U = U(S, V ). -
Practice Problems from Chapter 1-3 Problem 1 One Mole of a Monatomic Ideal Gas Goes Through a Quasistatic Three-Stage Cycle (1-2, 2-3, 3-1) Shown in V 3 the Figure
Practice Problems from Chapter 1-3 Problem 1 One mole of a monatomic ideal gas goes through a quasistatic three-stage cycle (1-2, 2-3, 3-1) shown in V 3 the Figure. T1 and T2 are given. V 2 2 (a) (10) Calculate the work done by the gas. Is it positive or negative? V 1 1 (b) (20) Using two methods (Sackur-Tetrode eq. and dQ/T), calculate the entropy change for each stage and ∆ for the whole cycle, Stotal. Did you get the expected ∆ result for Stotal? Explain. T1 T2 T (c) (5) What is the heat capacity (in units R) for each stage? Problem 1 (cont.) ∝ → (a) 1 – 2 V T P = const (isobaric process) δW 12=P ( V 2−V 1 )=R (T 2−T 1)>0 V = const (isochoric process) 2 – 3 δW 23 =0 V 1 V 1 dV V 1 T1 3 – 1 T = const (isothermal process) δW 31=∫ PdV =R T1 ∫ =R T 1 ln =R T1 ln ¿ 0 V V V 2 T 2 V 2 2 T1 T 2 T 2 δW total=δW 12+δW 31=R (T 2−T 1)+R T 1 ln =R T 1 −1−ln >0 T 2 [ T 1 T 1 ] Problem 1 (cont.) Sackur-Tetrode equation: V (b) 3 V 3 U S ( U ,V ,N )=R ln + R ln +kB ln f ( N ,m ) V2 2 N 2 N V f 3 T f V f 3 T f ΔS =R ln + R ln =R ln + ln V V 2 T V 2 T 1 1 i i ( i i ) 1 – 2 V ∝ T → P = const (isobaric process) T1 T2 T 5 T 2 ΔS12 = R ln 2 T 1 T T V = const (isochoric process) 3 1 3 2 2 – 3 ΔS 23 = R ln =− R ln 2 T 2 2 T 1 V 1 T 2 3 – 1 T = const (isothermal process) ΔS 31 =R ln =−R ln V 2 T 1 5 T 2 T 2 3 T 2 as it should be for a quasistatic cyclic process ΔS = R ln −R ln − R ln =0 cycle 2 T T 2 T (quasistatic – reversible), 1 1 1 because S is a state function. -
Lecture 4: 09.16.05 Temperature, Heat, and Entropy
3.012 Fundamentals of Materials Science Fall 2005 Lecture 4: 09.16.05 Temperature, heat, and entropy Today: LAST TIME .........................................................................................................................................................................................2� State functions ..............................................................................................................................................................................2� Path dependent variables: heat and work..................................................................................................................................2� DEFINING TEMPERATURE ...................................................................................................................................................................4� The zeroth law of thermodynamics .............................................................................................................................................4� The absolute temperature scale ..................................................................................................................................................5� CONSEQUENCES OF THE RELATION BETWEEN TEMPERATURE, HEAT, AND ENTROPY: HEAT CAPACITY .......................................6� The difference between heat and temperature ...........................................................................................................................6� Defining heat capacity.................................................................................................................................................................6� -
Chapter 3. Second and Third Law of Thermodynamics
Chapter 3. Second and third law of thermodynamics Important Concepts Review Entropy; Gibbs Free Energy • Entropy (S) – definitions Law of Corresponding States (ch 1 notes) • Entropy changes in reversible and Reduced pressure, temperatures, volumes irreversible processes • Entropy of mixing of ideal gases • 2nd law of thermodynamics • 3rd law of thermodynamics Math • Free energy Numerical integration by computer • Maxwell relations (Trapezoidal integration • Dependence of free energy on P, V, T https://en.wikipedia.org/wiki/Trapezoidal_rule) • Thermodynamic functions of mixtures Properties of partial differential equations • Partial molar quantities and chemical Rules for inequalities potential Major Concept Review • Adiabats vs. isotherms p1V1 p2V2 • Sign convention for work and heat w done on c=C /R vm system, q supplied to system : + p1V1 p2V2 =Cp/CV w done by system, q removed from system : c c V1T1 V2T2 - • Joule-Thomson expansion (DH=0); • State variables depend on final & initial state; not Joule-Thomson coefficient, inversion path. temperature • Reversible change occurs in series of equilibrium V states T TT V P p • Adiabatic q = 0; Isothermal DT = 0 H CP • Equations of state for enthalpy, H and internal • Formation reaction; enthalpies of energy, U reaction, Hess’s Law; other changes D rxn H iD f Hi i T D rxn H Drxn Href DrxnCpdT Tref • Calorimetry Spontaneous and Nonspontaneous Changes First Law: when one form of energy is converted to another, the total energy in universe is conserved. • Does not give any other restriction on a process • But many processes have a natural direction Examples • gas expands into a vacuum; not the reverse • can burn paper; can't unburn paper • heat never flows spontaneously from cold to hot These changes are called nonspontaneous changes. -
Carbon Dioxide Heat Transfer Coefficients and Pressure
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Archivio della ricerca - Università degli studi di Napoli Federico II international journal of refrigeration 33 (2010) 1068e1085 available at www.sciencedirect.com www.iifiir.org journal homepage: www.elsevier.com/locate/ijrefrig Carbon dioxide heat transfer coefficients and pressure drops during flow boiling: Assessment of predictive methods R. Mastrullo a, A.W. Mauro a, A. Rosato a,*, G.P. Vanoli b a D.E.TE.C., Facolta` di Ingegneria, Universita` degli Studi di Napoli Federico II, p.le Tecchio 80, 80125 Napoli, Italy b Dipartimento di Ingegneria, Universita` degli Studi del Sannio, corso Garibaldi 107, Palazzo dell’Aquila Bosco Lucarelli, 82100 Benevento, Italy article info abstract Article history: Among the alternatives to the HCFCs and HFCs, carbon dioxide emerged as one of the most Received 13 December 2009 promising environmentally friendly refrigerants. In past years many works were carried Received in revised form out about CO2 flow boiling and very different two-phase flow characteristics from 8 February 2010 conventional fluids were found. Accepted 5 April 2010 In order to assess the best predictive methods for the evaluation of CO2 heat transfer Available online 9 April 2010 coefficients and pressure gradients in macro-channels, in the current article a literature survey of works and a collection of the results of statistical comparisons available in Keywords: literature are furnished. Heat exchanger In addition the experimental data from University of Naples are used to run a deeper Boiling analysis. Both a statistical and a direct comparison against some of the most quoted Carbon dioxide-review predictive methods are carried out. -
Math Background for Thermodynamics ∑
MATH BACKGROUND FOR THERMODYNAMICS A. Partial Derivatives and Total Differentials Partial Derivatives Given a function f(x1,x2,...,xm) of m independent variables, the partial derivative ∂ f of f with respect to x , holding the other m-1 independent variables constant, , is defined by i ∂ xi xj≠i ∂ f fx( , x ,..., x+ ∆ x ,..., x )− fx ( , x ,..., x ,..., x ) = 12ii m 12 i m ∂ lim ∆ xi x →∆ 0 xi xj≠i i nRT Example: If p(n,V,T) = , V ∂ p RT ∂ p nRT ∂ p nR = = − = ∂ n V ∂V 2 ∂T V VT,, nTV nV , Total Differentials Given a function f(x1,x2,...,xm) of m independent variables, the total differential of f, df, is defined by m ∂ f df = ∑ dx ∂ i i=1 xi xji≠ ∂ f ∂ f ∂ f = dx + dx + ... + dx , ∂ 1 ∂ 2 ∂ m x1 x2 xm xx2131,...,mm xxx , ,..., xx ,..., m-1 where dxi is an infinitesimally small but arbitrary change in the variable xi. nRT Example: For p(n,V,T) = , V ∂ p ∂ p ∂ p dp = dn + dV + dT ∂ n ∂ V ∂ T VT,,, nT nV RT nRT nR = dn − dV + dT V V 2 V B. Some Useful Properties of Partial Derivatives 1. The order of differentiation in mixed second derivatives is immaterial; e.g., for a function f(x,y), ∂ ∂ f ∂ ∂ f ∂ 22f ∂ f = or = ∂ y ∂ xx ∂ ∂ y ∂∂yx ∂∂xy y x x y 2 in the commonly used short-hand notation. (This relation can be shown to follow from the definition of partial derivatives.) 2. Given a function f(x,y): ∂ y 1 a. = etc. ∂ f ∂ f x ∂ y x ∂ f ∂ y ∂ x b. -
( ∂U ∂T ) = ∂CV ∂V = 0, Which Shows That CV Is Independent of V . 4
so we have ∂ ∂U ∂ ∂U ∂C =0 = = V =0, ∂T ∂V ⇒ ∂V ∂T ∂V which shows that CV is independent of V . 4. Using Maxwell’s relations. Show that (∂H/∂p) = V T (∂V/∂T ) . T − p Start with dH = TdS+ Vdp. Now divide by dp, holding T constant: dH ∂H ∂S [at constant T ]= = T + V. dp ∂p ∂p T T Use the Maxwell relation (Table 9.1 of the text), ∂S ∂V = ∂p − ∂T T p to get the result ∂H ∂V = T + V. ∂p − ∂T T p 97 5. Pressure dependence of the heat capacity. (a) Show that, in general, for quasi-static processes, ∂C ∂2V p = T . ∂p − ∂T2 T p (b) Based on (a), show that (∂Cp/∂p)T = 0 for an ideal gas. (a) Begin with the definition of the heat capacity, δq dS C = = T , p dT dT for a quasi-static process. Take the derivative: ∂C ∂2S ∂2S p = T = T (1) ∂p ∂p∂T ∂T∂p T since S is a state function. Substitute the Maxwell relation ∂S ∂V = ∂p − ∂T T p into Equation (1) to get ∂C ∂2V p = T . ∂p − ∂T2 T p (b) For an ideal gas, V (T )=NkT/p,so ∂V Nk = , ∂T p p ∂2V =0, ∂T2 p and therefore, from part (a), ∂C p =0. ∂p T 98 (a) dU = TdS+ PdV + μdN + Fdx, dG = SdT + VdP+ Fdx, − ∂G F = , ∂x T,P 1 2 G(x)= (aT + b)xdx= 2 (aT + b)x . ∂S ∂F (b) = , ∂x − ∂T T,P x,P ∂S ∂F (c) = = ax, ∂x − ∂T − T,P x,P S(x)= ax dx = 1 ax2. -
How Compressible Are Innovation Processes?
1 How Compressible are Innovation Processes? Hamid Ghourchian, Arash Amini, Senior Member, IEEE, and Amin Gohari, Senior Member, IEEE Abstract The sparsity and compressibility of finite-dimensional signals are of great interest in fields such as compressed sensing. The notion of compressibility is also extended to infinite sequences of i.i.d. or ergodic random variables based on the observed error in their nonlinear k-term approximation. In this work, we use the entropy measure to study the compressibility of continuous-domain innovation processes (alternatively known as white noise). Specifically, we define such a measure as the entropy limit of the doubly quantized (time and amplitude) process. This provides a tool to compare the compressibility of various innovation processes. It also allows us to identify an analogue of the concept of “entropy dimension” which was originally defined by R´enyi for random variables. Particular attention is given to stable and impulsive Poisson innovation processes. Here, our results recognize Poisson innovations as the more compressible ones with an entropy measure far below that of stable innovations. While this result departs from the previous knowledge regarding the compressibility of fat-tailed distributions, our entropy measure ranks stable innovations according to their tail decay. Index Terms Compressibility, entropy, impulsive Poisson process, stable innovation, white L´evy noise. I. INTRODUCTION The compressible signal models have been extensively used to represent or approximate various types of data such as audio, image and video signals. The concept of compressibility has been separately studied in information theory and signal processing societies. In information theory, this concept is usually studied via the well-known entropy measure and its variants. -
Thermodynamics
ME346A Introduction to Statistical Mechanics { Wei Cai { Stanford University { Win 2011 Handout 6. Thermodynamics January 26, 2011 Contents 1 Laws of thermodynamics 2 1.1 The zeroth law . .3 1.2 The first law . .4 1.3 The second law . .5 1.3.1 Efficiency of Carnot engine . .5 1.3.2 Alternative statements of the second law . .7 1.4 The third law . .8 2 Mathematics of thermodynamics 9 2.1 Equation of state . .9 2.2 Gibbs-Duhem relation . 11 2.2.1 Homogeneous function . 11 2.2.2 Virial theorem / Euler theorem . 12 2.3 Maxwell relations . 13 2.4 Legendre transform . 15 2.5 Thermodynamic potentials . 16 3 Worked examples 21 3.1 Thermodynamic potentials and Maxwell's relation . 21 3.2 Properties of ideal gas . 24 3.3 Gas expansion . 28 4 Irreversible processes 32 4.1 Entropy and irreversibility . 32 4.2 Variational statement of second law . 32 1 In the 1st lecture, we will discuss the concepts of thermodynamics, namely its 4 laws. The most important concepts are the second law and the notion of Entropy. (reading assignment: Reif x 3.10, 3.11) In the 2nd lecture, We will discuss the mathematics of thermodynamics, i.e. the machinery to make quantitative predictions. We will deal with partial derivatives and Legendre transforms. (reading assignment: Reif x 4.1-4.7, 5.1-5.12) 1 Laws of thermodynamics Thermodynamics is a branch of science connected with the nature of heat and its conver- sion to mechanical, electrical and chemical energy. (The Webster pocket dictionary defines, Thermodynamics: physics of heat.) Historically, it grew out of efforts to construct more efficient heat engines | devices for ex- tracting useful work from expanding hot gases (http://www.answers.com/thermodynamics). -
An Entropy-Stable Hybrid Scheme for Simulations of Transcritical Real-Fluid
Journal of Computational Physics 340 (2017) 330–357 Contents lists available at ScienceDirect Journal of Computational Physics www.elsevier.com/locate/jcp An entropy-stable hybrid scheme for simulations of transcritical real-fluid flows Peter C. Ma, Yu Lv ∗, Matthias Ihme Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA a r t i c l e i n f o a b s t r a c t Article history: A finite-volume method is developed for simulating the mixing of turbulent flows at Received 30 August 2016 transcritical conditions. Spurious pressure oscillations associated with fully conservative Received in revised form 9 March 2017 formulations are addressed by extending a double-flux model to real-fluid equations of Accepted 12 March 2017 state. An entropy-stable formulation that combines high-order non-dissipative and low- Available online 22 March 2017 order dissipative finite-volume schemes is proposed to preserve the physical realizability Keywords: of numerical solutions across large density gradients. Convexity conditions and constraints Real fluid on the application of the cubic state equation to transcritical flows are investigated, and Spurious pressure oscillations conservation properties relevant to the double-flux model are examined. The resulting Double-flux model method is applied to a series of test cases to demonstrate the capability in simulations Entropy stable of problems that are relevant for multi-species transcritical real-fluid flows. Hybrid scheme © 2017 Elsevier Inc. All rights reserved. 1. Introduction The accurate and robust simulation of transcritical real-fluid effects is crucial for many engineering applications, such as fuel injection in internal-combustion engines, rocket motors and gas turbines. -
Muddiest Point – Entropy and Reversible I Am Confused About Entropy and How It Is Different in a Reversible Versus Irreversible Case
1 Muddiest Point { Entropy and Reversible I am confused about entropy and how it is different in a reversible versus irreversible case. Note: Some of the discussion below follows from the previous muddiest points comment on the general idea of a reversible and an irreversible process. You may wish to have a look at that comment before reading this one. Let's talk about entropy first, and then we will consider how \reversible" gets involved. Generally we divide the universe into two parts, a system (what we are studying) and the surrounding (everything else). In the end the total change in the entropy will be the sum of the change in both, dStotal = dSsystem + dSsurrounding: This total change of entropy has only two possibilities: Either there is no spontaneous change (equilibrium) and dStotal = 0, or there is a spontaneous change because we are not at equilibrium, and dStotal > 0. Of course the entropy change of each piece, system or surroundings, can be positive or negative. However, the second law says the sum must be zero or positive. Let's start by thinking about the entropy change in the system and then we will add the entropy change in the surroundings. Entropy change in the system: When you consider the change in entropy for a process you should first consider whether or not you are looking at an isolated system. Start with an isolated system. An isolated system is not able to exchange energy with anything else (the surroundings) via heat or work. Think of surrounding the system with a perfect, rigid insulating blanket.