Partial Differential Equations

Similar documents
Chapter 4. Fourier Series

LINEARIZATION OF NONLINEAR EQUATIONS By Dominick Andrisani. dg x. ( ) ( ) dx

x x x 2x x N ( ) p NUMERICAL METHODS UNIT-I-SOLUTION OF EQUATIONS AND EIGENVALUE PROBLEMS By Newton-Raphson formula

d y f f dy Numerical Solution of Ordinary Differential Equations Consider the 1 st order ordinary differential equation (ODE) . dx

THE CONSERVATIVE DIFFERENCE SCHEME FOR THE GENERALIZED ROSENAU-KDV EQUATION

The Advection-Diffusion equation!

LIMITS AND DERIVATIVES

Most text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t

Castiel, Supernatural, Season 6, Episode 18

LIMITS AND DERIVATIVES NCERT

2. Fourier Series, Fourier Integrals and Fourier Transforms

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015

Numerical Methods for Finding Multiple Solutions of a Superlinear Problem

9.3 Power Series: Taylor & Maclaurin Series

x x x Using a second Taylor polynomial with remainder, find the best constant C so that for x 0,

The z Transform. The Discrete LTI System Response to a Complex Exponential

THE SOLUTION OF NONLINEAR EQUATIONS f( x ) = 0.

On the convergence, consistence and stability of a standard finite difference scheme

Fourier Series and the Wave Equation

An Insight into Differentiation and Integration

( a) ( ) 1 ( ) 2 ( ) ( ) 3 3 ( ) =!

MAT2400 Assignment 2 - Solutions

Chapter 10 Partial Differential Equations and Fourier Series

too many conditions to check!!

Differentiation Techniques 1: Power, Constant Multiple, Sum and Difference Rules

Mathematical Series (You Should Know)

September 2012 C1 Note. C1 Notes (Edexcel) Copyright - For AS, A2 notes and IGCSE / GCSE worksheets 1

Calculus 2 - D. Yuen Final Exam Review (Version 11/22/2017. Please report any possible typos.)

CHAPTER 5. Theory and Solution Using Matrix Techniques

Notes on iteration and Newton s method. Iteration

PROBLEMS AND SOLUTIONS 2

Introduction. Question: Why do we need new forms of parametric curves? Answer: Those parametric curves discussed are not very geometric.

Definition 2.1 (The Derivative) (page 54) is a function. The derivative of a function f with respect to x, represented by. f ', is defined by

e to approximate (using 4

Taylor Series (BC Only)

Solutions to Final Exam Review Problems

Elementary Linear Algebra

U8L1: Sec Equations of Lines in R 2

8. Applications To Linear Differential Equations

(c) Write, but do not evaluate, an integral expression for the volume of the solid generated when R is

Wavelets and Multiresolution. Processing. Multiresolution analysis. New basis functions called wavelets. Good old Fourier transform

ALLOCATING SAMPLE TO STRATA PROPORTIONAL TO AGGREGATE MEASURE OF SIZE WITH BOTH UPPER AND LOWER BOUNDS ON THE NUMBER OF UNITS IN EACH STRATUM

Linear Differential Equations of Higher Order Basic Theory: Initial-Value Problems d y d y dy

A New Hybrid in the Nonlinear Part of Adomian Decomposition Method for Initial Value Problem of Ordinary Differential Equation

Quiz. Use either the RATIO or ROOT TEST to determine whether the series is convergent or not.

Section 11.8: Power Series

Fundamental Concepts: Surfaces and Curves

LESSON 2: SIMPLIFYING RADICALS

Zeros of Polynomials

A Pseudo Spline Methods for Solving an Initial Value Problem of Ordinary Differential Equation

6.3 Testing Series With Positive Terms

Calculus 2 Quiz 1 Review / Fall 2011

Subject: Differential Equations & Mathematical Modeling -III. Lesson: Power series solutions of Differential Equations. about ordinary points

FREE VIBRATIONS OF SIMPLY SUPPORTED BEAMS USING FOURIER SERIES

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Curve Sketching Handout #5 Topic Interpretation Rational Functions

In algebra one spends much time finding common denominators and thus simplifying rational expressions. For example:

Topic 5 [434 marks] (i) Find the range of values of n for which. (ii) Write down the value of x dx in terms of n, when it does exist.

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Stability analysis of numerical methods for stochastic systems with additive noise

2.4 - Sequences and Series

Chapter 2: Numerical Methods

AP Calculus BC Review Applications of Derivatives (Chapter 4) and f,

PANIMALAR ENGINEERING COLLEGE

We are mainly going to be concerned with power series in x, such as. (x)} converges - that is, lims N n

On Exact Finite-Difference Scheme for Numerical Solution of Initial Value Problems in Ordinary Differential Equations.

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

: Transforms and Partial Differential Equations

Atomic Physics 4. Name: Date: 1. The de Broglie wavelength associated with a car moving with a speed of 20 m s 1 is of the order of. A m.

Time-Domain Representations of LTI Systems

(a) (b) All real numbers. (c) All real numbers. (d) None. to show the. (a) 3. (b) [ 7, 1) (c) ( 7, 1) (d) At x = 7. (a) (b)

which are generalizations of Ceva s theorem on the triangle

LECTURE 2 LEAST SQUARES CROSS-VALIDATION FOR KERNEL DENSITY ESTIMATION

Chapter 6 Principles of Data Reduction

Finite Difference Approximation for First- Order Hyperbolic Partial Differential Equation Arising in Neuronal Variability with Shifts

Finite Difference Approximation for Transport Equation with Shifts Arising in Neuronal Variability

Assignment Number 3 Solutions

Fourier Techniques lecture by Håkon Hoel

Infinite Sequences and Series

Taylor Polynomials and Taylor Series

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Explicit and closed formed solution of a differential equation. Closed form: since finite algebraic combination of. converges for x x0

Honors Calculus Homework 13 Solutions, due 12/8/5

U8L1: Sec Equations of Lines in R 2

Chapter 10: Power Series

Coordinate Systems. Things to think about:

Subject: Differential Equations & Mathematical Modeling-III

Chapter 9: Numerical Differentiation

Maximum and Minimum Values

Approximation of the Likelihood Ratio Statistics in Competing Risks Model Under Informative Random Censorship From Both Sides

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

PHYS-3301 Lecture 9. CHAPTER 5 Wave Properties of Matter and Quantum Mechanics I. 5.3: Electron Scattering. Bohr s Quantization Condition

Find a formula for the exponential function whose graph is given , 1 2,16 1, 6

SOLUTION SET VI FOR FALL [(n + 2)(n + 1)a n+2 a n 1 ]x n = 0,

Chapter 2 The Solution of Numerical Algebraic and Transcendental Equations

f t dt. Write the third-degree Taylor polynomial for G

CHAPTER 10 INFINITE SEQUENCES AND SERIES

It is often useful to approximate complicated functions using simpler ones. We consider the task of approximating a function by a polynomial.

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.

Transcription:

EE 84 Matematical Metods i Egieerig Partial Differetial Eqatios Followig are some classical partial differetial eqatios were is assmed to be a fctio of two or more variables t (time) ad y (spatial coordiates). oe dimesioal wave eqatio c two dimesioal wave eqatio c oe dimesioal eat eqatio c two dimesioal eat eqatio c two dimesioal aplace eqatio two dimesioal Poisso eqatio f ( y) Te epressio ad its iger dimesioal aalogs are ow as te aplacia of ad deoted by Δ or. Te order of a partial differetial eqatio (PDE) is te igest order of derivative wic appears. A PDE is called liear if te ow fctio ad te partial derivatives are of te first degree ad at most oe of tese appears i ay give term. Oterwise te eqatio is called oliear. I may cases sbscripts are sed to deote partial derivatives. For eample y ad y. A geeral liear PDE of order two i two variables ca be epressed as A B y C yy D E y F G were A B C D E F ad G are fctios of ad y. Te eqatio is called omogeeos if G. PDEs are classified ito tree grops: Elliptic PDE: if B 4AC < Parabolic PDE: if B 4AC Hyperbolic: B 4AC > Page of

EE 84 Matematical Metods i Egieerig Te modelig of a pysical problem is ofte doe wit a PDE ad a set of oter eqatios tat describe te beavior of te soltio o te bodary of te regio der cosideratio. Te eqatios are called bodary coditios. Iitial coditios may also be sed to describe te pysical peomeo. A PDE alog wit te bodary ad iitial coditios is called ad iitial-bodary vale problem or simply a bodary vale problem. Teorem : Sperpositio Priciple If ad are soltios of a liear omogeeos partial differetial eqatio te ay liear combiatio c c were c ad c are costats is also a soltio. If i additio ad satisfy a liear omogeeos bodary coditio te so will c c. Eample: Cosider te two dimesioal aplace eqatio. It is liear secod order ad omogeeos. Te fctios y y y y l( y ) e si y are all soltios to te aplace y eqatio. Ay liear combiatio of te above fctios will also satisfy te aplace eqatio. Before sperposig soltios cec tat te PDE i qestio is liear ad omogeeos. Soltio of PDEs: Metod of Separatio of Variables Oe dimesioal wave eqatio et s cosider a oe dimesioal wave eqatio of a vibratig strig. Cosider a strig is fasteed at ad at. Te strig is free to vibrate i a fied plae. ( t) deotes te positio of te poit o te strig at time t. satisfies te oe dimesioal wave eqatio c () Te bodary coditios are: ( t) ad ( t) Te iitial coditios are: ( ) f ( ) ad ( ) g() for all t >. for < <. Te bodary coditios state tat te eds of te strig are eld fied at all time. Te iitial coditios give te iitial positio (sape) of te strig f ( ) ad its iitial velocity g. ( ) Page of

EE 84 Matematical Metods i Egieerig Figre : Iitial sape of a stretced strig. et s assme tat ( t) ca be epressed as a prodct of two fctios. ( t) X ( ) T (t) () were X ( ) is a fctio of aloe ad T ( t) is a fctio of t aloe. Te problem terefore becomes fidig X ( ) ad T ( t). Differetiatig ( t) X ( ) T (t ) wit respect to ad t we get X T ad XT Sbstittig tese to te wave eqatio we get X T c X T. Dividig by c XT we get T X (3) c T X Te variables are separated i te sese tat te left side of Eq. (3) is a fctio of t aloe ad te rigt side is a fctio of aloe. Sice te variables t ad are idepedet of eac oter te oly way to get eqality is to ave te fctios o bot sides of Eq. (3) are costat ad eqal. T X ad were is a arbitrary costat ad called te separatio c T X costat. T c T X X We ave to separate te variables i te bodary coditios sig Eq. (). X ( ) T ( t) ad X ( ) T ( t) for all t >. If X ( ) or X ( ) te T ( t) mst be zero for all t ad terefore is zero. To avoid tis trivial soltio we set X ( ) ad X ( ). Te bodary vale problem i X becomes X X X ad X ( ) ( ) Solve te bodary vale problem i X First assme is positive say μ wit μ >. Terefore X μ X ad its μ geeral soltio is: X c e c e ( ) μ Page 3 of 3

EE 84 Matematical Metods i Egieerig It is owever easy to verify tat te oly way to satisfy te coditio X( ) is to tae c c. Terefore discard μ. X ( ) ad Now cec if μ. Te eqatio for X becomes X μ X wit te geeral soltio X ( ) c cosμ c siμ. Te coditio X ( ) implies tat c ad ece X ( ) siμ. Te coditio X( ) implies tat si μ. π si μ i tr implies tat μ were is ay iteger. π Terefore X ( ) X si 3 Wit π μ we ow ave to solve for T. π T c T Te geeral soltio of tis eqatio is π π T( t) acosc t bsi c t were T a cos λ t b si λ t were 3 π λ c ad 3 Combiig te soltios of X ad T we obtai a ifiite set of prodct soltios of () all satisfyig te correspodig bodary coditios: π t a t b t ( ) si ( cos λ si λ ) 3 Ay liear combiatio of te above will satisfy () ad te bodary coditios. Terefore by sperpositio priciple try a ifiite liear combiatio as a possible soltio tat will satisfy () te bodary coditios ad te iitial coditios. π t a t b t ( ) si ( cos λ si λ ) We mst ow determie te ow coefficiets a ad b sc tat te fctio ( t) satisfies te iitial coditios. At t we get π ( ) f ( ) a si < < (4) Epressio (4) is te Forier series of ( ) f valid betwee < < (called alf-rage epasio). Terefore te coefficiets a are te sie coefficiets ad ca be determied by Page 4 of 4

EE 84 Matematical Metods i Egieerig π a f ( ) si d 3 Te secod iitial coditio ca be sed to determie ( t) term by term wit respect to t b. Differetiate te series for π si a si t b cos t Now set t ( λ λ λ λt) π g ( ) λ b si t t π b g si d Sice tis is te alf-rage epasio of g ( ) λ ( ) 3 π b g si λ d Terefore ( ) π b g ( ) si λ d were π λ c as determied before. π b g ( ) si d 3 cπ Oe dimesioal eat eqatio Cosider temperatre distribtio i a iform bar of legt wit islated lateral srface ad o iteral sorces of eat sbect to certai bodary ad iitial coditios. ( t) o o Figre : Islated bar wit eds ept at zero degree. et ( t) represet te temperatre at poit of te bar at time t. Te eds of te bar are eld at costat temperatre. Te iitial temperatre distribtio of te bar is ( ) f (). Fid ( t) for < < t > were satisfies te oe dimesioal eat eqatio Page 5 of 5

EE 84 Matematical Metods i Egieerig c (5) Te bodary coditios are: ( t) ad ( t) Te iitial coditios are: ( ) f ( ) for < <. for all t >. et s assme tat ( t) ca be epressed as a prodct of two fctios. ( t) X ( ) T (t) were X ( ) is a fctio of aloe ad T ( t) is a fctio of t aloe. Sbstitte ( t) X ( ) T ( t) i te eat eqatio. X T c X T T X c T X Terefore to old te eqality costat. T c T ad X X Separatig variables i te bodary coditios we get ( ) ( ) ( ) ( ) X T t ad X T t for all t >. T X ad were is te separatio c T X X ( ) ad ( ) I order to avoid trivial soltios we eed X problem i X is: X X X ( ) ad X ( ) Tis part was solved i te oe dimesioal wave eqatio. π μ 3 π X si ad ( ) X 3 Sbstittig te vale of i te differetial eqatio for T we get π T c T (6) Te geeral soltio of (6) is T ( t) b e λ t 3. Te bodary vale π were λ c 3 λ ( ) t π Terefore te prodct soltio is t be si 3 Page 6 of 6

EE 84 Matematical Metods i Egieerig Eac is a soltio of te eat eqatio ad te give bodary coditios. Usig sperpositio priciple we ca write λ ( t) b e t π si Te coefficiet b ca be obtaied tilizig te iitial coditio. Set t. π f ( ) ( ) b si π b f si d 3 Terefore ( ) Fiite Differece Metod for te Heat Eqatio Or oe dimesioal eat eqatio ad te bodary ad iitial coditios for te islated bar wit eds eld at temperatre zero are agai c < < t > Te bodary coditios are: ( t) ad ( t) Te iitial coditios are: ( ) f ( ) for < <. for all t >. Fiite differece metod ca be tilized to approimate te vales of te ow fctio at discrete itervals. Te process begis by dividig te idepedet variables ito a discrete grid strctre. et s divide (positio) ito parts wit a step size of. Similarly divide t (time) ito m parts wit a step size of. i i i 3 t i 3 m Or obective is to approimate te vales i ( i ) were < i < ad represets te vale of at te grid poit ( i ). i Page 7 of 7

EE 84 Matematical Metods i Egieerig t i t i- i i i - t t i lim lim ( t ) ( t) Figre 3: Grid poits i te t-plae. ( t ) ad ( t) ( t) ( t) ( t) If ad are sfficietly small we ca write t ( t) ( t) ( t ) ( t) ad ( t) ( t) ( t) Note: Te approimate epressio for te secod derivative ca be obtaied sig Taylor s epasio. At te grid poit ( i ) we ave te followig approimatios wit respect to te first derivative ad te secod derivative. ( ) ( i ) ( i ) t i ( i i ) Page 8 of 8

EE 84 Matematical Metods i Egieerig ( i ) ( ) i i i Sbstittig tese discrete approimatios ito te eat eqatio we get c ( ) ( ) i i i i c i ( ) i i i i i c were s. ( s) s( ) i i i i Te bodary ad iitial coditios ave to be discretized as well. ( t) ( ) ad t for all t > ( ) ad ( ) ( ) f ( ) for < < ( i ) f (i i ) i > To compte we eed te tree vales ad as sow i Figre 4. i i i i i i- i i Figre 4: Movig forward i time step. et s cosider a merical eample. A ti bar of it legt is placed i boilig water. After reacig C trogot te bar is removed from te boilig water. Wit te lateral sides ept islated sddely at time t te eds are immersed i a medim wit costat temperatre C. Use te fiite differece metod to approimate te soltio to tis problem at t. sec. Tae c /. Divide te legt ito eqal parts ad ece.. Tae a time step of.. c s ( / ) (. ) (. ) 4 Page 9 of 9

( s) i s( i i ) ( ( 4) ) i ( )( i i ) ( ) 4 i i 4 i i i i / Bodary coditios: (. ) ad (. ) Iitial coditios: (. i ) f (. ) i > i i ( )/ 4 ( * ) 4 ( )/ 4 ( * ) 4 / 3 / 3 4 5 8 9 6 EE 84 Matematical Metods i Egieerig 7 ( )/ 4 ( * ) 4 75 ( )/ 4 ( * ) 4 / 3 / 3 4 5 75 8 9 6 7 3 ( )/ 4 ( * 75 ) / 4 6 5 ( )/ 4 ( * 75) / 4 93 75 3. 3 3. 3 3 4 3 5 3 93 75 6 5 8 3. 9 3. 6 3 7 3 Fiite Differece Metod for te Wave Eqatio et s tilize te oe dimesioal wave eqatio already cosidered i te earlier sectio. c < < t > tt Page of

EE 84 Matematical Metods i Egieerig Te bodary coditios are: ( t) ad ( t) Te iitial coditios are: ( ) f ( ) ad t ( ) g( ) for all t >. for. As before let deote step size i ad deote step size i t. Or obective is to approimate te vales i ( i ) were i ad represets te vale of at te grid poit ( ) i i. i i- i i i - i t Figre 5: Grid poits i te t plae. i i ( i ) ( ) i i i yy ( i ) ( ) i i i Sbstittig tese ito te wave eqatio we get Page of

EE 84 Matematical Metods i Egieerig ( s) i s( i i ) i i () c were s. Figre 6: Steppig forward i time. Now we ave to discretize te bodary ad iitial coditios. ( t) ( ) ad t for all t > ( ) ad ( ) ( ) f () ad t ( ) g() ( i ) f (i > for. i ) i () We ow se te iitial data f ad g to obtai te discrete form of te secod iitial coditio. Usig te cetered first differece approimatio ( t ) ( t ) t ( t) Settig t we get ( ) ( ) g( ) t ( ) ( ) ( ) g() ( i ) ( i ) g(i) ( i) g () i i Set i Eq. (). ( s) i s( i i ) i ( s) s( ) i i i i i i Page of

i ( s) f ( i) s[ f {( i ) } f {( i ) } ] i ( i) s[ f {( i ) } f ( i) f {( i ) } ] i i f (3) Add () ad (3) ad divide by. s f ( i) g( i) [ f {( i ) } f ( i) f {( i ) } ] (4) i Eample: 6 c f ( ) if < < 3 g ( ) oterwise Use ad. Terefore s ad 6. Wit s epressio () becomes i i i i (5) ( i ) f (i i ) i () s f ( i) g( i) [ f {( i ) } f ( i) f {( i ) } ] (4) i EE 84 Matematical Metods i Egieerig Usig () ad (4) related to te bodary coditios we get te followig. 3 4 5 6 3 4 5 6 Now we ca se (5) to geerate reslts for te remaiig grid poits. 3 3 4 3 5 6 4 5 4 5 3 5 6 3 3 3 3 3 3 4 3 5 3 6 4 5 4 3 5 3 4 6 3 Page 3 of 3