The Uniqueness of Clausius' Integrating Factor
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Ordinary Differential Equations
Ordinary Differential Equations for Engineers and Scientists Gregg Waterman Oregon Institute of Technology c 2017 Gregg Waterman This work is licensed under the Creative Commons Attribution 4.0 International license. The essence of the license is that You are free to: Share copy and redistribute the material in any medium or format • Adapt remix, transform, and build upon the material for any purpose, even commercially. • The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution You must give appropriate credit, provide a link to the license, and indicate if changes • were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to the web page below. To view a full copy of this license, visit https://creativecommons.org/licenses/by/4.0/legalcode. -
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. -
6CCP3212 Statistical Mechanics Homework 1
6CCP3212 Statistical Mechanics Homework 1 Lecturer: Dr. Eugene A. Lim 2018-19 Year 3 Semester 1 https://nms.kcl.ac.uk/eugene.lim/teach/statmech/sm.html 1) (i) For the following differentials with α and β non-zero real constants, which are exact and which are inexact? Integrate the equation if it is exact. (a) x dG = αdx + β dy (1) y (b) α dG = dx + βdy (2) x (c) x2 dG = (x + y)dx + dy (3) 2 (ii) Show that the work done on the system at pressure P d¯W = −P dV (4) where dV is the change in volume is an inexact differential by showing that there exists no possible function of state for W (P; V ). (iii) Consider the differential dF = (x2 − y)dx + xdy : (5) (a) Show that this is not an exact differential. And hence integrate this equation in two different straight paths from (1; 1) ! (2; 2) and from (1; 1) ! (1; 2) ! (2; 2), where (x; y) indicates the locations. Compare the results { are they identical? (b) Define a new differential with dF y 1 dG ≡ = 1 − dx + dy : (6) x2 x2 x Show that dG is exact, and find G(x; y). 2) This problem asks you to derive some derivative identities of a system with three variables x, y and z, with a single constraint x(y; z). This kind of system is central to thermodynamics as we often use three state variables P , V and T , with an equation of state P (V; T ) (i.e. the constraint) to describe a system. -
3 More Applications of Derivatives
3 More applications of derivatives 3.1 Exact & inexact di®erentials in thermodynamics So far we have been discussing total or \exact" di®erentials µ ¶ µ ¶ @u @u du = dx + dy; (1) @x y @y x but we could imagine a more general situation du = M(x; y)dx + N(x; y)dy: (2) ¡ ¢ ³ ´ If the di®erential is exact, M = @u and N = @u . By the identity of mixed @x y @y x partial derivatives, we have µ ¶ µ ¶ µ ¶ @M @2u @N = = (3) @y x @x@y @x y Ex: Ideal gas pV = RT (for 1 mole), take V = V (T; p), so µ ¶ µ ¶ @V @V R RT dV = dT + dp = dT ¡ 2 dp (4) @T p @p T p p Now the work done in changing the volume of a gas is RT dW = pdV = RdT ¡ dp: (5) p Let's calculate the total change in volume and work done in changing the system between two points A and C in p; T space, along paths AC or ABC. 1. Path AC: dT T ¡ T ¢T ¢T = 2 1 ´ so dT = dp (6) dp p2 ¡ p1 ¢p ¢p T ¡ T1 ¢T ¢T & = ) T ¡ T1 = (p ¡ p1) (7) p ¡ p1 ¢p ¢p so (8) R ¢T R ¢T R ¢T dV = dp ¡ [T + (p ¡ p )]dp = ¡ (T ¡ p )dp (9) p ¢p p2 1 ¢p 1 p2 1 ¢p 1 R ¢T dW = ¡ (T ¡ p )dp (10) p 1 ¢p 1 1 T (p ,T ) 2 2 C (p,T) (p1,T1) A B p Figure 1: Path in p; T plane for thermodynamic process. -
New Dirac Delta Function Based Methods with Applications To
New Dirac Delta function based methods with applications to perturbative expansions in quantum field theory Achim Kempf1, David M. Jackson2, Alejandro H. Morales3 1Departments of Applied Mathematics and Physics 2Department of Combinatorics and Optimization University of Waterloo, Ontario N2L 3G1, Canada, 3Laboratoire de Combinatoire et d’Informatique Math´ematique (LaCIM) Universit´edu Qu´ebec `aMontr´eal, Canada Abstract. We derive new all-purpose methods that involve the Dirac Delta distribution. Some of the new methods use derivatives in the argument of the Dirac Delta. We highlight potential avenues for applications to quantum field theory and we also exhibit a connection to the problem of blurring/deblurring in signal processing. We find that blurring, which can be thought of as a result of multi-path evolution, is, in Euclidean quantum field theory without spontaneous symmetry breaking, the strong coupling dual of the usual small coupling expansion in terms of the sum over Feynman graphs. arXiv:1404.0747v3 [math-ph] 23 Sep 2014 2 1. A method for generating new representations of the Dirac Delta The Dirac Delta distribution, see e.g., [1, 2, 3], serves as a useful tool from physics to engineering. Our aim here is to develop new all-purpose methods involving the Dirac Delta distribution and to show possible avenues for applications, in particular, to quantum field theory. We begin by fixing the conventions for the Fourier transform: 1 1 g(y) := g(x) eixy dx, g(x)= g(y) e−ixy dy (1) √2π √2π Z Z To simplify the notation we denote integration over the real line by the absence of e e integration delimiters. -
Second Order Linear Differential Equations Y
Second Order Linear Differential Equations Second order linear equations with constant coefficients; Fundamental solutions; Wronskian; Existence and Uniqueness of solutions; the characteristic equation; solutions of homogeneous linear equations; reduction of order; Euler equations In this chapter we will study ordinary differential equations of the standard form below, known as the second order linear equations : y″ + p(t) y′ + q(t) y = g(t). Homogeneous Equations : If g(t) = 0, then the equation above becomes y″ + p(t) y′ + q(t) y = 0. It is called a homogeneous equation. Otherwise, the equation is nonhomogeneous (or inhomogeneous ). Trivial Solution : For the homogeneous equation above, note that the function y(t) = 0 always satisfies the given equation, regardless what p(t) and q(t) are. This constant zero solution is called the trivial solution of such an equation. © 2008, 2016 Zachary S Tseng B-1 - 1 Second Order Linear Homogeneous Differential Equations with Constant Coefficients For the most part, we will only learn how to solve second order linear equation with constant coefficients (that is, when p(t) and q(t) are constants). Since a homogeneous equation is easier to solve compares to its nonhomogeneous counterpart, we start with second order linear homogeneous equations that contain constant coefficients only: a y″ + b y′ + c y = 0. Where a, b, and c are constants, a ≠ 0. A very simple instance of such type of equations is y″ − y = 0 . The equation’s solution is any function satisfying the equality t y″ = y. Obviously y1 = e is a solution, and so is any constant multiple t −t of it, C1 e . -
Physical Chemistry II “The Mistress of the World and Her Shadow” Chemistry 402
Physical Chemistry II “The mistress of the world and her shadow” Chemistry 402 L. G. Sobotka Department of Chemistry Washington University, St Louis, MO, 63130 January 3, 2012 Contents IIntroduction 7 1 Physical Chemistry II - 402 -Thermodynamics (mostly) 8 1.1Who,when,where.............................................. 8 1.2CourseContent/Logistics.......................................... 8 1.3Grading.................................................... 8 1.3.1 Exams................................................. 8 1.3.2 Quizzes................................................ 8 1.3.3 ProblemSets............................................. 8 1.3.4 Grading................................................ 8 2Constants 9 3 The Structure of Physical Science 10 3.1ClassicalMechanics.............................................. 10 3.2QuantumMechanics............................................. 11 3.3StatisticalMechanics............................................. 11 3.4Thermodynamics............................................... 12 3.5Kinetics.................................................... 13 4RequisiteMath 15 4.1 Exact differentials.............................................. 15 4.2Euler’sReciprocityrelation......................................... 15 4.2.1 Example................................................ 16 4.3Euler’sCyclicrelation............................................ 16 4.3.1 Example................................................ 16 4.4Integratingfactors.............................................. 17 4.5LegendreTransformations......................................... -
Exact and Inexact Differentials in the Early Development of Mechanics
Revista Brasileira de Ensino de Física, vol. 42, e20190192 (2020) Articles www.scielo.br/rbef cb DOI: http://dx.doi.org/10.1590/1806-9126-RBEF-2019-0192 Licença Creative Commons Exact and inexact differentials in the early development of mechanics and thermodynamics Mário J. de Oliveira*1 1Universidade de São Paulo, Instituto de Física, São Paulo, SP, Brasil Received on July 31, 2019. Revised on October 8, 2019. Accepted on October 13, 2019. We give an account and a critical analysis of the use of exact and inexact differentials in the early development of mechanics and thermodynamics, and the emergence of differential calculus and how it was applied to solve some mechanical problems, such as those related to the cycloidal pendulum. The Lagrange equations of motions are presented in the form they were originally obtained in terms of differentials from the principle of virtual work. The derivation of the conservation of energy in differential form as obtained originally by Clausius from the equivalence of heat and work is also examined. Keywords: differential, differential calculus, analytical mechanics, thermodynamics. 1. Introduction variable x. If another variable y depends on the indepen- dent variable x, then the resulting increment dy of y is It is usual to formulate the basic equations of thermo- its differential. The quotient of these two differentials, dynamics in terms of differentials. The conservation of dy/dx, was interpreted geometrically by Leibniz as the energy is written as ratio of the ordinate y of a point on a curve and the length of the subtangent associated to this point. -
5 Mar 2009 a Survey on the Inverse Integrating Factor
A survey on the inverse integrating factor.∗ Isaac A. Garc´ıa (1) & Maite Grau (1) Abstract The relation between limit cycles of planar differential systems and the inverse integrating factor was first shown in an article of Giacomini, Llibre and Viano appeared in 1996. From that moment on, many research articles are devoted to the study of the properties of the inverse integrating factor and its relation with limit cycles and their bifurcations. This paper is a summary of all the results about this topic. We include a list of references together with the corresponding related results aiming at being as much exhaustive as possible. The paper is, nonetheless, self-contained in such a way that all the main results on the inverse integrating factor are stated and a complete overview of the subject is given. Each section contains a different issue to which the inverse integrating factor plays a role: the integrability problem, relation with Lie symmetries, the center problem, vanishing set of an inverse integrating factor, bifurcation of limit cycles from either a period annulus or from a monodromic ω-limit set and some generalizations. 2000 AMS Subject Classification: 34C07, 37G15, 34-02. Key words and phrases: inverse integrating factor, bifurcation, Poincar´emap, limit cycle, Lie symmetry, integrability, monodromic graphic. arXiv:0903.0941v1 [math.DS] 5 Mar 2009 1 The Euler integrating factor The method of integrating factors is, in principle, a means for solving ordinary differential equations of first order and it is theoretically important. The use of integrating factors goes back to Leonhard Euler. Let us consider a first order differential equation and write the equation in the Pfaffian form ω = P (x, y) dy Q(x, y) dx =0 . -
Handbook of Mathematics, Physics and Astronomy Data
Handbook of Mathematics, Physics and Astronomy Data School of Chemical and Physical Sciences c 2017 Contents 1 Reference Data 1 1.1 PhysicalConstants ............................... .... 2 1.2 AstrophysicalQuantities. ....... 3 1.3 PeriodicTable ................................... 4 1.4 ElectronConfigurationsoftheElements . ......... 5 1.5 GreekAlphabetandSIPrefixes. ..... 6 2 Mathematics 7 2.1 MathematicalConstantsandNotation . ........ 8 2.2 Algebra ......................................... 9 2.3 TrigonometricalIdentities . ........ 10 2.4 HyperbolicFunctions. ..... 12 2.5 Differentiation .................................. 13 2.6 StandardDerivatives. ..... 14 2.7 Integration ..................................... 15 2.8 StandardIndefiniteIntegrals . ....... 16 2.9 DefiniteIntegrals ................................ 18 2.10 CurvilinearCoordinateSystems. ......... 19 2.11 VectorsandVectorAlgebra . ...... 22 2.12ComplexNumbers ................................. 25 2.13Series ......................................... 27 2.14 OrdinaryDifferentialEquations . ......... 30 2.15 PartialDifferentiation . ....... 33 2.16 PartialDifferentialEquations . ......... 35 2.17 DeterminantsandMatrices . ...... 36 2.18VectorCalculus................................. 39 2.19FourierSeries .................................. 42 2.20Statistics ..................................... 45 3 Selected Physics Formulae 47 3.1 EquationsofElectromagnetism . ....... 48 3.2 Equations of Relativistic Kinematics and Mechanics . ............. 49 3.3 Thermodynamics and Statistical Physics -
FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS III: Numerical and More Analytic Methods
FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS III: Numerical and More Analytic Methods David Levermore Department of Mathematics University of Maryland 30 September 2012 Because the presentation of this material in lecture will differ from that in the book, I felt that notes that closely follow the lecture presentation might be appreciated. Contents 8. First-Order Equations: Numerical Methods 8.1. Numerical Approximations 2 8.2. Explicit and Implicit Euler Methods 3 8.3. Explicit One-Step Methods Based on Taylor Approximation 4 8.3.1. Explicit Euler Method Revisited 4 8.3.2. Local and Global Errors 4 8.3.3. Higher-Order Taylor-Based Methods (not covered) 5 8.4. Explicit One-Step Methods Based on Quadrature 6 8.4.1. Explicit Euler Method Revisited Again 6 8.4.2. Runge-Trapezoidal Method 7 8.4.3. Runge-Midpoint Method 9 8.4.4. Runge-Kutta Method 10 8.4.5. General Runge-Kutta Methods (not covered) 12 9. Exact Differential Forms and Integrating Factors 9.1. Implicit General Solutions 15 9.2. Exact Differential Forms 16 9.3. Integrating Factors 20 10. Special First-Order Equations and Substitution 10.1. Linear Argument Equations (not covered) 25 10.2. Dilation Invariant Equations (not covered) 26 10.3. Bernoulli Equations (not covered) 27 10.4. Substitution (not covered) 29 1 2 8. First-Order Equations: Numerical Methods 8.1. Numerical Approximations. Analytic methods are either difficult or impossible to apply to many first-order differential equations. In such cases direction fields might be the only graphical method that we have covered that can be applied. -
The First Law: the Machinery the Power of Thermodynamics – How to Establish Relations Between Different Properties of a System
The First Law: the machinery The power of thermodynamics – how to establish relations between different properties of a system. The procedure is based on the experimental fact that the internal energy and the enthalpy are state functions. We shall see that a property can be measured indirectly by measuring others and then combining their values. We shall also discuss the liquefaction of gases and establish the relation between Cp and CV. State functions and exact differentials State and path functions The initial state of the system is i and in this state the internal energy is Ui. Work is done by the system as it expands adiabatically to a state f (an internal energy Uf). The work done on the system as it changes along Path 1 from i to f is w. U – a property of the state; w – a property of the path. Consider another process, Path 2: the initial and final states are the same, but the expansion is not adiabatic. Because U is a state function, the internal energy of both the initial and the final states are the same as before, but an energy q’ enters the system as heat and the work w’ is not the same as w. The work and the heat are path functions. Exact and inexact differentials If a system is taken along a path, U changes from Ui to Uf and the overall change is the sum (integral) of all infinitesimal changes along the path: f ΔU = dU ∫i ΔU depends on the initial and final states but is independent of the path between them.