2 Weighted Residual Methods

Size: px
Start display at page:

Download "2 Weighted Residual Methods"

Transcription

1 2 Weighed Residua Mehods Fundamena equaions Consider he probem governed by he differenia equaion: Γu = f in. (83) The above differenia equaion is soved by using he boundary condiions given as foows: u = ū on u (84) Bu = on = \. (85) where he boundary consiss of u and. The boundary condiions given in eqs.(84) and (85) are caed rigid and naura boundary condiions, or iriche and Neumann boundary condiions, respecivey. In mos engineering probems, Γ and B are differenia operaors in he forms of Γ = Σ and B = n Σ, where Σ is anoher differenia operaor and n is he norma vecor on. For he Lapace probem, he governing equaion is given by 2 u = f in, (86) and he Neumann boundary condiion on is given as = n u =. Then he differenia operaors Γ, B and Σ are defined by Γ = 2, B = n and Σ =, respecivey. Tria funcions uppose ha u is approximaed by ria funcion ũ of ũ(x) = N J (x) (87) where are coefficiens and N J (x) are ineary independen funcions caed ria bases, es funcions or shape funcions. Weighed residua ince he ria funcion ũ does no saisfy he governing equaion and he boundary condiion rigorousy, he residuas defined in he foowing are nonzero R (x) = {Γũ(x) + f(x) = in (88) R (x) = ũ ū(x) on u, or Bũ(x) (x) on. (89) The probem is o find ũ o make zero he residuas weighed by he appropriae funcion w(x) as foows: w(x) R (x)dv + w(x) R (x)d = (9) where w(x) is caed he weigh funcion. Eq.(9) is aso caed a weak form o he origina differenira equaion (83), caed a srong form, because he souion ha saisfies eq.(9) does no aways saisfy he origina differenia equaion (83) and he boundary condiion (85). ubsiuion of eq.(87) ino eq.(9) yieds he foowing equaion: w I R dv + w I R d = w I (x) ( ΓN J (x) f(x))dv + w I (x) (N J (x) ū(x))d + w I (x) (BN J (x) (x))d u { = w I (x) ΓN J (x)dv + w I (x)n J (x)d + w I (x) BN J (x)d u {{ { w I (x) f(x)dv + w I (x)ū(x)d + w I (x) (x)d u {{ = (91) 13

2 or =. (92) where M independen weigh funcions w I (I = 1, 2,..., M) are chosen. This equaion can be soved for. As shown in he seque, here are severa residua mehods depending on he seecion of weigh funcions. I is no difficu o find ria funcions ũ saisfying he boundary condiion ũ = ū on u. In such a case, no residua exiss on u and he inegras on u disappear in eq.(91). In he foowing secions, i is assumed ha ria funcions ũ saisfy ũ = ū on u. 2.1 Poin coocaion mehod In he poin coocaion mehod, we seec a eas he same number of coocaion poins as he unknown parameers and deermine he parameers such ha he residua is zero a he seeced poins. The coocaion mehod is equivaen o he residua mehod in which he weigh funcion is chosen as w I = 1δ(x x I ) (93) where 1 denoes he uni marix and δ(x) is he irac dea funcion saisfying he equaions δ(x x I )R(x)dV = R(x I ), for x I (94) or δ(x x I )R(x)d = R(x I ), for x I (95) In his case, he marix and he vecor in eq.(92) can be expressed by 2.2 Leas squares mehod = ΓN J (x I ) or BN J (x I ), = f(x I ) or (x I ) (96) In he eas squares mehod, he sum of he squares of he residuas defined by I = R 2 dv + R 2 d (97) is minimized. The necessary condiion o minimize I is yieding he sysem of equaions: or I =, I = 1, 2,... (98) I û R R dv + R R d = (99) û I û I [ ] ΓN I (x) ΓN J (x)dv + BN I (x) BN J (x)d {{ [ ] ΓN I (x) f(x)dv + BN I (x) (x)d {{ = (1) As shown in he above equaion, he eas squares mehod is considered as a weighed residua mehod wih he weigh funcions ΓN I (x) in he domain and BN I (x) on he boundary. 14

3 2.3 Cassica Gaerkin mehod If ony he domain inegra in eq.(91) is aken ino accoun and he shape funcions N I (x) are used as he weigh funcions w I, where are arbirary coefficiens, hen we have { 2.4 Gaerkin mehod { N I (x)γn J (x)dv {{ N I (x) f(x)dv = (11) {{ In he cassica Gaerkin mehod, he boundary condiion is no considered. Therefore, he cassica Gaerkin mehod is no convenien for pracica use. Here he Gaerkin mehod aking accoun of he boundary condiion is formuaed. Consider he weighed residua as foows: w(x)( Γũ(x) f(x))dv + w(x)(bũ(x) (x))d =. (12) Here we assume ha w is a weighed funcion saisfying w = on u and ũ saisfies he boundary condiion ũ = ū on u. ince Γ = Σ, he firs inegra in eq.(12) is wrien as w(x)γũ(x)dv = w(x) Σũ(x)dV = w(x)n Σũ(x)d w(x) Σũ(x)dV = w(x)bũ(x)d w(x) Σũ(x)dV (13) where he divergence heorem is used. Noe ha in he above equaion, he inegra on u vanishes due o w = on u. Then eq.(12) becomes w(x) Σũ(x)dV w(x) f(x)dv w(x) (x)d =. (14) This equaion has he weak form which invoves he Neumann boundary condiion on, which can be soved under he iriche boundary condiion ũ = ū and he consrain condiion w = on u. Now i is assumed ha he ria funcion ũ is expressed by ũ(x) = N J (x) + N (x)ū (15) where N J (x) and N (x) are he shape funcions equa o zero and one on he boundary u, respecivey. Aso he weigh funcion w is seeced as w(x) = N I (x) (16) where N I (x) is he same shape funcion used in eq.(15). Then he condiions u = û and w = on u are saisfied. ubsiuion of eqs.(15) and (16) ino eq.(14) yieds N I (x) ΣN J (x)dv {{ ( N I (x) f(x)dv N I (x) ΣN (x)dv ū + ) N I (x) (x)d =. (17) {{ 15

4 Exampe 2.1 Consider he souion u saisfying he equaion subjeced o he boundary condiions dx 2 + f = x (18) u = a x =, du/dx = f a x =. (19) The exac souion for he above probem is u(x) = f x(2 x/2) and he vaue a x = /2, u(/2), is obained as u(/2) = f /2(2 x/4) = f 7 2 /8. Now he boundary vaue probem menioned above is soved by means of boh he cassica Gaerkin mehod and he Gaerkin mehod assuming ha he souion is approximaed by ũ(x) = N 1 (x)û 1, where N 1 (x) = x(2 x). Noe ha he approximaed funcion is sighy differen from he exac souion. Cassica Gaerkin mehod For N 1 (x) = x(2 x) and ΓN 1 (x) = d 2 N 1 (x)/dx 2 = 2, eq.(11) becomes x(2 x)( 2)dxû 1 + x(2 x) f dx = (11) From eq.(11), we obained û 1 = f /2. The souion ũ(x) is obained by ũ(x) = f x(2 x)/2. A x = /2, ũ(/2) = 3/8 f 2, which is much differen from he exac souion u(/2) = 7/8 f 2. Gaerkin mehod From eq.(17), he foowing equaion based on he Gaerkin mehod is formuaed. ( ) dn 1 dn 1 dx dx dxû1 N 1 (x) f dx + N 1 (1) f = (111) ubsiuion of N 1 (x) = x(2 x) ino he above equaion yieds ( ) 2( x)2( x)dxû 1 (2x x 2 ) f dx + (2 ) f =, (112) from which û 1 = 5 f /4. Hence, ũ(x) = 5 f x(2 x)/4. Aso a x = /2, ũ(/2) = 15/16 f 2. Thus we can concude ha he Gaerkin mehod wih he boundary condiion gives a vaue coser o he exac souion han he cassica Gaerkin mehod, in which no boundary condiion is considered. Exampe 2.2 ove he governing equaion dx = x 1 (113) by using he Gaerkin mehod wih he ria funcion u(x) = 2 N J (x), where N J (x) = x J. The boundary condiions are given by u() = and du/dx(1) = 2. The Gaerkin mehod yieds he foowing equaion for he above menioned probem: ( 1 1 dn I dn J dx dx dx {{ 1 N I (x) fdx dn I dn ) dx dx dxū + N I (1) = (114) {{ where f = 1, ū =, = 2, M = 2, N 1 (x) = x and N 2 (x) = x 2. The cacuaion of he marix and he vecor eads o he equaions [ ] { { 1 1 û /3 û 2 = (115) 3 which can be soved for (J = 1, 2). 16

5 Probem 2.1 Consider he governing equaion dx 2 u = x 1 (116) subjeced o he boundary condiion u() = and du/dx(1) = 2. ove he probem by using he Gaerkin mehod wih he ria funcion u(x) = 2 N J (x), where N J (x) = x J. Probem 2.2 erive he weak form based on he Gaerkin mehod for he mui-dimensiona Lapace probem, for which he governing equaion is given by and he boundary condiions are as foows. u = f in (117) u = ū on u (118) n u = on = \ u (119) Probem 2.3 ove he same probem as Probem using he weak form. 17

Introduction to Simulation - Lecture 16. Methods for Computing Periodic Steady-State - Part II Jacob White

Introduction to Simulation - Lecture 16. Methods for Computing Periodic Steady-State - Part II Jacob White Inroducion o Simuaion - ecure 6 Mehods for Compuing Periodic Seady-Sae - Par II Jacob Whie hanks o Deepak Ramaswamy, Micha Rewienski, and Karen Veroy Ouine hree Mehods so far ime inegraion uni seady-sae

More information

dy dx = xey (a) y(0) = 2 (b) y(1) = 2.5 SOLUTION: See next page

dy dx = xey (a) y(0) = 2 (b) y(1) = 2.5 SOLUTION: See next page Assignmen 1 MATH 2270 SOLUTION Please wrie ou complee soluions for each of he following 6 problems (one more will sill be added). You may, of course, consul wih your classmaes, he exbook or oher resources,

More information

Lecture 20: Riccati Equations and Least Squares Feedback Control

Lecture 20: Riccati Equations and Least Squares Feedback Control 34-5 LINEAR SYSTEMS Lecure : Riccai Equaions and Leas Squares Feedback Conrol 5.6.4 Sae Feedback via Riccai Equaions A recursive approach in generaing he marix-valued funcion W ( ) equaion for i for he

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions MA 14 Calculus IV (Spring 016) Secion Homework Assignmen 1 Soluions 1 Boyce and DiPrima, p 40, Problem 10 (c) Soluion: In sandard form he given firs-order linear ODE is: An inegraing facor is given by

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Research Article Developing a Series Solution Method of q-difference Equations

Research Article Developing a Series Solution Method of q-difference Equations Appied Mahemaics Voume 2013, Arice ID 743973, 4 pages hp://dx.doi.org/10.1155/2013/743973 Research Arice Deveoping a Series Souion Mehod of q-difference Equaions Hsuan-Ku Liu Deparmen of Mahemaics and

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

System of Linear Differential Equations

System of Linear Differential Equations Sysem of Linear Differenial Equaions In "Ordinary Differenial Equaions" we've learned how o solve a differenial equaion for a variable, such as: y'k5$e K2$x =0 solve DE yx = K 5 2 ek2 x C_C1 2$y''C7$y

More information

Math Final Exam Solutions

Math Final Exam Solutions Mah 246 - Final Exam Soluions Friday, July h, 204 () Find explici soluions and give he inerval of definiion o he following iniial value problems (a) ( + 2 )y + 2y = e, y(0) = 0 Soluion: In normal form,

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

Lie Derivatives operator vector field flow push back Lie derivative of

Lie Derivatives operator vector field flow push back Lie derivative of Lie Derivaives The Lie derivaive is a mehod of compuing he direcional derivaive of a vecor field wih respec o anoher vecor field We already know how o make sense of a direcional derivaive of real valued

More information

t 2 B F x,t n dsdt t u x,t dxdt

t 2 B F x,t n dsdt t u x,t dxdt Evoluion Equaions For 0, fixed, le U U0, where U denoes a bounded open se in R n.suppose ha U is filled wih a maerial in which a conaminan is being ranspored by various means including diffusion and convecion.

More information

Convergence of the Neumann series in higher norms

Convergence of the Neumann series in higher norms Convergence of he Neumann series in higher norms Charles L. Epsein Deparmen of Mahemaics, Universiy of Pennsylvania Version 1.0 Augus 1, 003 Absrac Naural condiions on an operaor A are given so ha he Neumann

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

Stochastic Differential Equations and Inclusions with Mean Derivatives relative to the Past

Stochastic Differential Equations and Inclusions with Mean Derivatives relative to the Past Inernaiona Journa of Difference Equaions ISSN973-669, Voume4, Number 1, pp.27 41 (29 hp://campus.ms.edu/ijde Sochasic Differenia Equaions and Incusions wih Mean Derivaives reaive o he Pas Sveana V. Azarina

More information

Math 334 Test 1 KEY Spring 2010 Section: 001. Instructor: Scott Glasgow Dates: May 10 and 11.

Math 334 Test 1 KEY Spring 2010 Section: 001. Instructor: Scott Glasgow Dates: May 10 and 11. 1 Mah 334 Tes 1 KEY Spring 21 Secion: 1 Insrucor: Sco Glasgow Daes: Ma 1 and 11. Do NOT wrie on his problem saemen bookle, excep for our indicaion of following he honor code jus below. No credi will be

More information

DYNAMIC ECONOMETRIC MODELS vol NICHOLAS COPERNICUS UNIVERSITY - TORUŃ Józef Stawicki and Joanna Górka Nicholas Copernicus University

DYNAMIC ECONOMETRIC MODELS vol NICHOLAS COPERNICUS UNIVERSITY - TORUŃ Józef Stawicki and Joanna Górka Nicholas Copernicus University DYNAMIC ECONOMETRIC MODELS vol.. - NICHOLAS COPERNICUS UNIVERSITY - TORUŃ 996 Józef Sawicki and Joanna Górka Nicholas Copernicus Universiy ARMA represenaion for a sum of auoregressive processes In he ime

More information

Solving the Inverse Problems of Wave Equation by a Boundary Functional Method

Solving the Inverse Problems of Wave Equation by a Boundary Functional Method Journa of Shipping and Ocean Engineering 6 (7) 33-49 doi.765/59-5879/7.6. D DAVID PUBLISHING Soving he Inverse Probems of Wave Equaion by a Boundary Funciona Mehod Chein-Shan Liu and Yung-Wei Chen 3. Cener

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Differential Equations

Differential Equations Mah 21 (Fall 29) Differenial Equaions Soluion #3 1. Find he paricular soluion of he following differenial equaion by variaion of parameer (a) y + y = csc (b) 2 y + y y = ln, > Soluion: (a) The corresponding

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

EXERCISES FOR SECTION 1.5

EXERCISES FOR SECTION 1.5 1.5 Exisence and Uniqueness of Soluions 43 20. 1 v c 21. 1 v c 1 2 4 6 8 10 1 2 2 4 6 8 10 Graph of approximae soluion obained using Euler s mehod wih = 0.1. Graph of approximae soluion obained using Euler

More information

MATH 128A, SUMMER 2009, FINAL EXAM SOLUTION

MATH 128A, SUMMER 2009, FINAL EXAM SOLUTION MATH 28A, SUMME 2009, FINAL EXAM SOLUTION BENJAMIN JOHNSON () (8 poins) [Lagrange Inerpolaion] (a) (4 poins) Le f be a funcion defined a some real numbers x 0,..., x n. Give a defining equaion for he Lagrange

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordinary Differenial Equaions 5. Examples of linear differenial equaions and heir applicaions We consider some examples of sysems of linear differenial equaions wih consan coefficiens y = a y +... + a

More information

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation:

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation: M ah 5 7 Fall 9 L ecure O c. 4, 9 ) Hamilon- J acobi Equaion: Weak S oluion We coninue he sudy of he Hamilon-Jacobi equaion: We have shown ha u + H D u) = R n, ) ; u = g R n { = }. ). In general we canno

More information

Online Appendix to Solution Methods for Models with Rare Disasters

Online Appendix to Solution Methods for Models with Rare Disasters Online Appendix o Soluion Mehods for Models wih Rare Disasers Jesús Fernández-Villaverde and Oren Levinal In his Online Appendix, we presen he Euler condiions of he model, we develop he pricing Calvo block,

More information

DISCRETE GRONWALL LEMMA AND APPLICATIONS

DISCRETE GRONWALL LEMMA AND APPLICATIONS DISCRETE GRONWALL LEMMA AND APPLICATIONS JOHN M. HOLTE MAA NORTH CENTRAL SECTION MEETING AT UND 24 OCTOBER 29 Gronwall s lemma saes an inequaliy ha is useful in he heory of differenial equaions. Here is

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

Lecture 24. Calderon-Zygmund Decomposition Technique: Cube decomposition

Lecture 24. Calderon-Zygmund Decomposition Technique: Cube decomposition Lecure 24 May 3 h, 2004 Our moivaion for his as ecure in he course is o show a resu using our reguariy heory which is oherwise unprovabe using cassica echniques. This is he previous Theorem, and in paricuar

More information

Undetermined coefficients for local fractional differential equations

Undetermined coefficients for local fractional differential equations Available online a www.isr-publicaions.com/jmcs J. Mah. Compuer Sci. 16 (2016), 140 146 Research Aricle Undeermined coefficiens for local fracional differenial equaions Roshdi Khalil a,, Mohammed Al Horani

More information

Week #13 - Integration by Parts & Numerical Integration Section 7.2

Week #13 - Integration by Parts & Numerical Integration Section 7.2 Week #3 - Inegraion by Pars & Numerical Inegraion Secion 7. From Calculus, Single Variable by Hughes-Halle, Gleason, McCallum e. al. Copyrigh 5 by John Wiley & Sons, Inc. This maerial is used by permission

More information

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model Modal idenificaion of srucures from roving inpu daa by means of maximum likelihood esimaion of he sae space model J. Cara, J. Juan, E. Alarcón Absrac The usual way o perform a forced vibraion es is o fix

More information

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013 IMPLICI AND INVERSE FUNCION HEOREMS PAUL SCHRIMPF 1 OCOBER 25, 213 UNIVERSIY OF BRIISH COLUMBIA ECONOMICS 526 We have exensively sudied how o solve sysems of linear equaions. We know how o check wheher

More information

Stochastic Model for Cancer Cell Growth through Single Forward Mutation

Stochastic Model for Cancer Cell Growth through Single Forward Mutation Journal of Modern Applied Saisical Mehods Volume 16 Issue 1 Aricle 31 5-1-2017 Sochasic Model for Cancer Cell Growh hrough Single Forward Muaion Jayabharahiraj Jayabalan Pondicherry Universiy, jayabharahi8@gmail.com

More information

Some new classes of generalized Lagrange-based Apostol type Hermite polynomials

Some new classes of generalized Lagrange-based Apostol type Hermite polynomials Preprins www.preprins.org NOT PEER-REVIEWED Posed: 19 Juy 2018 Some new casses of generaized Lagrange-based Aposo ype Hermie poynomias Waseem A. Khan 1 and Nisar K S 2 1 Deparmen of Mahemaics, Facuy of

More information

Second Order Linear Differential Equations

Second Order Linear Differential Equations Second Order Linear Differenial Equaions Second order linear equaions wih consan coefficiens; Fundamenal soluions; Wronskian; Exisence and Uniqueness of soluions; he characerisic equaion; soluions of homogeneous

More information

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations IOSR Journal of Mahemaics (IOSR-JM) e-issn: 2278-5728, p-issn: 2319-765X. Volume 1, Issue 6 Ver. II (Nov - Dec. 214), PP 48-54 Variaional Ieraion Mehod for Solving Sysem of Fracional Order Ordinary Differenial

More information

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec

More information

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004 ODEs II, Lecure : Homogeneous Linear Sysems - I Mike Raugh March 8, 4 Inroducion. In he firs lecure we discussed a sysem of linear ODEs for modeling he excreion of lead from he human body, saw how o ransform

More information

f t te e = possesses a Laplace transform. Exercises for Module-III (Transform Calculus)

f t te e = possesses a Laplace transform. Exercises for Module-III (Transform Calculus) Exercises for Module-III (Transform Calculus) ) Discuss he piecewise coninuiy of he following funcions: =,, +, > c) e,, = d) sin,, = ) Show ha he funcion ( ) sin ( ) f e e = possesses a Laplace ransform.

More information

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t Exercise 7 C P = α + β R P + u C = αp + βr + v (a) (b) C R = α P R + β + w (c) Assumpions abou he disurbances u, v, w : Classical assumions on he disurbance of one of he equaions, eg. on (b): E(v v s P,

More information

On a Class of Two Dimensional Twisted q-tangent Numbers and Polynomials

On a Class of Two Dimensional Twisted q-tangent Numbers and Polynomials Inernaiona Maheaica Foru, Vo 1, 17, no 14, 667-675 HIKARI Ld, www-hikarico hps://doiorg/11988/if177647 On a Cass of wo Diensiona wised -angen Nubers and Poynoias C S Ryoo Deparen of Maheaics, Hanna Universiy,

More information

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k Challenge Problems DIS 03 and 0 March 6, 05 Choose one of he following problems, and work on i in your group. Your goal is o convince me ha your answer is correc. Even if your answer isn compleely correc,

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

After the completion of this section the student. Theory of Linear Systems of ODEs. Autonomous Systems. Review Questions and Exercises

After the completion of this section the student. Theory of Linear Systems of ODEs. Autonomous Systems. Review Questions and Exercises Chaper V ODE V.5 Sysems of Ordinary Differenial Equaions 45 V.5 SYSTEMS OF FIRST ORDER LINEAR ODEs Objecives: Afer he compleion of his secion he suden - should recall he definiion of a sysem of linear

More information

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3. Mah Rahman Exam Review Soluions () Consider he IVP: ( 4)y 3y + 4y = ; y(3) = 0, y (3) =. (a) Please deermine he longes inerval for which he IVP is guaraneed o have a unique soluion. Soluion: The disconinuiies

More information

2 Some Property of Exponential Map of Matrix

2 Some Property of Exponential Map of Matrix Soluion Se for Exercise Session No8 Course: Mahemaical Aspecs of Symmeries in Physics, ICFP Maser Program for M 22nd, January 205, a Room 235A Lecure by Amir-Kian Kashani-Poor email: kashani@lpensfr Exercise

More information

The expectation value of the field operator.

The expectation value of the field operator. The expecaion value of he field operaor. Dan Solomon Universiy of Illinois Chicago, IL dsolom@uic.edu June, 04 Absrac. Much of he mahemaical developmen of quanum field heory has been in suppor of deermining

More information

Introduction to Probability and Statistics Slides 4 Chapter 4

Introduction to Probability and Statistics Slides 4 Chapter 4 Inroducion o Probabiliy and Saisics Slides 4 Chaper 4 Ammar M. Sarhan, asarhan@mahsa.dal.ca Deparmen of Mahemaics and Saisics, Dalhousie Universiy Fall Semeser 8 Dr. Ammar Sarhan Chaper 4 Coninuous Random

More information

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx.

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx. . Use Simpson s rule wih n 4 o esimae an () +. Soluion: Since we are using 4 seps, 4 Thus we have [ ( ) f() + 4f + f() + 4f 3 [ + 4 4 6 5 + + 4 4 3 + ] 5 [ + 6 6 5 + + 6 3 + ]. 5. Our funcion is f() +.

More information

Optimized Self Scheduling of Power Producers in a Restructured Power Market

Optimized Self Scheduling of Power Producers in a Restructured Power Market Research Journa of Appied Sciences, Engineering and echnoogy 4(6): 58-586, 0 ISSN: 040-7467 Maxwe Scienific Organizaiona, 0 Submied: Sepember 3, 0 Acceped: Ocober 4, 0 Pubished: March 5, 0 Opimized Sef

More information

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018 MATH 5720: Gradien Mehods Hung Phan, UMass Lowell Ocober 4, 208 Descen Direcion Mehods Consider he problem min { f(x) x R n}. The general descen direcions mehod is x k+ = x k + k d k where x k is he curren

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

Vanishing Viscosity Method. There are another instructive and perhaps more natural discontinuous solutions of the conservation law

Vanishing Viscosity Method. There are another instructive and perhaps more natural discontinuous solutions of the conservation law Vanishing Viscosiy Mehod. There are anoher insrucive and perhaps more naural disconinuous soluions of he conservaion law (1 u +(q(u x 0, he so called vanishing viscosiy mehod. This mehod consiss in viewing

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2) Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

Distance Between Two Ellipses in 3D

Distance Between Two Ellipses in 3D Disance Beween Two Ellipses in 3D David Eberly Magic Sofware 6006 Meadow Run Cour Chapel Hill, NC 27516 eberly@magic-sofware.com 1 Inroducion An ellipse in 3D is represened by a cener C, uni lengh axes

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x . 1 Mah 211 Homework #3 February 2, 2001 2.4.3. y + (2/x)y = (cos x)/x 2 Answer: Compare y + (2/x) y = (cos x)/x 2 wih y = a(x)x + f(x)and noe ha a(x) = 2/x. Consequenly, an inegraing facor is found wih

More information

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow KEY Mah 334 Miderm III Winer 008 secion 00 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

Research Article Asymptotic Method of Solution for a Problem of Construction of Optimal Gas-Lift Process Modes

Research Article Asymptotic Method of Solution for a Problem of Construction of Optimal Gas-Lift Process Modes Hindawi Pubishing Corporaion Mahemaica Probems in Engineering Voume 21, Arice ID 19153, 1 pages doi:1.1155/21/19153 Research Arice Asympoic Mehod of Souion for a Probem of Consrucion of Opima Gas-Lif Process

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

A SOLUTION TO THE WATERMARK DETECTION PROBLEM BASED ON BAYESIAN ESTIMATION AND EM ALGORITHM

A SOLUTION TO THE WATERMARK DETECTION PROBLEM BASED ON BAYESIAN ESTIMATION AND EM ALGORITHM 7h European Signa Processing Conference (EUSIPCO 2009) Gasgow, Scoand, Augus 24-28, 2009 A SOLUTION TO THE WATERMARK DETECTION PROBLEM BASED ON BAYESIAN ESTIMATION AND EM ALGORITHM Akio Miyazaki Facuy

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD HAN XIAO 1. Penalized Leas Squares Lasso solves he following opimizaion problem, ˆβ lasso = arg max β R p+1 1 N y i β 0 N x ij β j β j (1.1) for some 0.

More information

MTH Feburary 2012 Final term PAPER SOLVED TODAY s Paper

MTH Feburary 2012 Final term PAPER SOLVED TODAY s Paper MTH401 7 Feburary 01 Final erm PAPER SOLVED TODAY s Paper Toal Quesion: 5 Mcqz: 40 Subjecive quesion: 1 4 q of 5 marks 4 q of 3 marks 4 q of marks Guidelines: Prepare his file as I included all pas papers

More information

An Invariance for (2+1)-Extension of Burgers Equation and Formulae to Obtain Solutions of KP Equation

An Invariance for (2+1)-Extension of Burgers Equation and Formulae to Obtain Solutions of KP Equation Commun Theor Phys Beijing, China 43 2005 pp 591 596 c Inernaional Academic Publishers Vol 43, No 4, April 15, 2005 An Invariance for 2+1-Eension of Burgers Equaion Formulae o Obain Soluions of KP Equaion

More information

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2.

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2. THE BERNOULLI NUMBERS The Bernoulli numbers are defined here by he exponenial generaing funcion ( e The firs one is easy o compue: (2 and (3 B 0 lim 0 e lim, 0 e ( d B lim 0 d e +e e lim 0 (e 2 lim 0 2(e

More information

Ann. Funct. Anal. 2 (2011), no. 2, A nnals of F unctional A nalysis ISSN: (electronic) URL:

Ann. Funct. Anal. 2 (2011), no. 2, A nnals of F unctional A nalysis ISSN: (electronic) URL: Ann. Func. Anal. 2 2011, no. 2, 34 41 A nnals of F uncional A nalysis ISSN: 2008-8752 elecronic URL: www.emis.de/journals/afa/ CLASSIFICAION OF POSIIVE SOLUIONS OF NONLINEAR SYSEMS OF VOLERRA INEGRAL EQUAIONS

More information

Math 333 Problem Set #2 Solution 14 February 2003

Math 333 Problem Set #2 Solution 14 February 2003 Mah 333 Problem Se #2 Soluion 14 February 2003 A1. Solve he iniial value problem dy dx = x2 + e 3x ; 2y 4 y(0) = 1. Soluion: This is separable; we wrie 2y 4 dy = x 2 + e x dx and inegrae o ge The iniial

More information

4.6 One Dimensional Kinematics and Integration

4.6 One Dimensional Kinematics and Integration 4.6 One Dimensional Kinemaics and Inegraion When he acceleraion a( of an objec is a non-consan funcion of ime, we would like o deermine he ime dependence of he posiion funcion x( and he x -componen of

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

FINM 6900 Finance Theory

FINM 6900 Finance Theory FINM 6900 Finance Theory Universiy of Queensland Lecure Noe 4 The Lucas Model 1. Inroducion In his lecure we consider a simple endowmen economy in which an unspecified number of raional invesors rade asses

More information

Optimal Path Planning for Flexible Redundant Robot Manipulators

Optimal Path Planning for Flexible Redundant Robot Manipulators 25 WSEAS In. Conf. on DYNAMICAL SYSEMS and CONROL, Venice, Ialy, November 2-4, 25 (pp363-368) Opimal Pah Planning for Flexible Redundan Robo Manipulaors H. HOMAEI, M. KESHMIRI Deparmen of Mechanical Engineering

More information

A generalization of the Burg s algorithm to periodically correlated time series

A generalization of the Burg s algorithm to periodically correlated time series A generalizaion of he Burg s algorihm o periodically correlaed ime series Georgi N. Boshnakov Insiue of Mahemaics, Bulgarian Academy of Sciences ABSTRACT In his paper periodically correlaed processes are

More information

t + t sin t t cos t sin t. t cos t sin t dt t 2 = exp 2 log t log(t cos t sin t) = Multiplying by this factor and then integrating, we conclude that

t + t sin t t cos t sin t. t cos t sin t dt t 2 = exp 2 log t log(t cos t sin t) = Multiplying by this factor and then integrating, we conclude that ODEs, Homework #4 Soluions. Check ha y ( = is a soluion of he second-order ODE ( cos sin y + y sin y sin = 0 and hen use his fac o find all soluions of he ODE. When y =, we have y = and also y = 0, so

More information

Second quantization and gauge invariance.

Second quantization and gauge invariance. 1 Second quanizaion and gauge invariance. Dan Solomon Rauland-Borg Corporaion Moun Prospec, IL Email: dsolom@uic.edu June, 1. Absrac. I is well known ha he single paricle Dirac equaion is gauge invarian.

More information

ENGI 9420 Engineering Analysis Assignment 2 Solutions

ENGI 9420 Engineering Analysis Assignment 2 Solutions ENGI 940 Engineering Analysis Assignmen Soluions 0 Fall [Second order ODEs, Laplace ransforms; Secions.0-.09]. Use Laplace ransforms o solve he iniial value problem [0] dy y, y( 0) 4 d + [This was Quesion

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence MATH 433/533, Fourier Analysis Secion 6, Proof of Fourier s Theorem for Poinwise Convergence Firs, some commens abou inegraing periodic funcions. If g is a periodic funcion, g(x + ) g(x) for all real x,

More information

Solutions of Sample Problems for Third In-Class Exam Math 246, Spring 2011, Professor David Levermore

Solutions of Sample Problems for Third In-Class Exam Math 246, Spring 2011, Professor David Levermore Soluions of Sample Problems for Third In-Class Exam Mah 6, Spring, Professor David Levermore Compue he Laplace ransform of f e from is definiion Soluion The definiion of he Laplace ransform gives L[f]s

More information

Hamilton Jacobi equations

Hamilton Jacobi equations Hamilon Jacobi equaions Inoducion o PDE The rigorous suff from Evans, mosly. We discuss firs u + H( u = 0, (1 where H(p is convex, and superlinear a infiniy, H(p lim p p = + This by comes by inegraion

More information

Robust estimation based on the first- and third-moment restrictions of the power transformation model

Robust estimation based on the first- and third-moment restrictions of the power transformation model h Inernaional Congress on Modelling and Simulaion, Adelaide, Ausralia, 6 December 3 www.mssanz.org.au/modsim3 Robus esimaion based on he firs- and hird-momen resricions of he power ransformaion Nawaa,

More information

BEng (Hons) Telecommunications. Examinations for / Semester 2

BEng (Hons) Telecommunications. Examinations for / Semester 2 BEng (Hons) Telecommunicaions Cohor: BTEL/14/FT Examinaions for 2015-2016 / Semeser 2 MODULE: ELECTROMAGNETIC THEORY MODULE CODE: ASE2103 Duraion: 2 ½ Hours Insrucions o Candidaes: 1. Answer ALL 4 (FOUR)

More information

Second Order Linear Differential Equations

Second Order Linear Differential Equations Second Order Linear Differenial Equaions Second order linear equaions wih consan coefficiens; Fundamenal soluions; Wronskian; Exisence and Uniqueness of soluions; he characerisic equaion; soluions of homogeneous

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Homogenization of random Hamilton Jacobi Bellman Equations

Homogenization of random Hamilton Jacobi Bellman Equations Probabiliy, Geomery and Inegrable Sysems MSRI Publicaions Volume 55, 28 Homogenizaion of random Hamilon Jacobi Bellman Equaions S. R. SRINIVASA VARADHAN ABSTRACT. We consider nonlinear parabolic equaions

More information

14 Autoregressive Moving Average Models

14 Autoregressive Moving Average Models 14 Auoregressive Moving Average Models In his chaper an imporan parameric family of saionary ime series is inroduced, he family of he auoregressive moving average, or ARMA, processes. For a large class

More information

Homework 10 (Stats 620, Winter 2017) Due Tuesday April 18, in class Questions are derived from problems in Stochastic Processes by S. Ross.

Homework 10 (Stats 620, Winter 2017) Due Tuesday April 18, in class Questions are derived from problems in Stochastic Processes by S. Ross. Homework (Sas 6, Winer 7 Due Tuesday April 8, in class Quesions are derived from problems in Sochasic Processes by S. Ross.. A sochasic process {X(, } is said o be saionary if X(,..., X( n has he same

More information

ABOUT THE DESIGN OF PRESTRESSED FRAMES WITH THE INFINITELY RIGID BEAM, SUBJECTED TO HORIZONTAL FORCES

ABOUT THE DESIGN OF PRESTRESSED FRAMES WITH THE INFINITELY RIGID BEAM, SUBJECTED TO HORIZONTAL FORCES NTERNTONL SCENTFC CONFERENCE CBv 00 November 00, Braşov BOUT THE DESGN OF PRESTRESSED FRES WTH THE NFNTELY RGD BE, SUBJECTED TO HORZONTL FORCES Dan PRECUPNU*, Codrin PRECUPNU** *Prof., Universiy G. saci

More information

Morning Time: 1 hour 30 minutes Additional materials (enclosed):

Morning Time: 1 hour 30 minutes Additional materials (enclosed): ADVANCED GCE 78/0 MATHEMATICS (MEI) Differenial Equaions THURSDAY JANUARY 008 Morning Time: hour 30 minues Addiional maerials (enclosed): None Addiional maerials (required): Answer Bookle (8 pages) Graph

More information

SUFFICIENT CONDITIONS FOR EXISTENCE SOLUTION OF LINEAR TWO-POINT BOUNDARY PROBLEM IN MINIMIZATION OF QUADRATIC FUNCTIONAL

SUFFICIENT CONDITIONS FOR EXISTENCE SOLUTION OF LINEAR TWO-POINT BOUNDARY PROBLEM IN MINIMIZATION OF QUADRATIC FUNCTIONAL HE PUBLISHING HOUSE PROCEEDINGS OF HE ROMANIAN ACADEMY, Series A, OF HE ROMANIAN ACADEMY Volume, Number 4/200, pp 287 293 SUFFICIEN CONDIIONS FOR EXISENCE SOLUION OF LINEAR WO-POIN BOUNDARY PROBLEM IN

More information

ln 2 1 ln y x c y C x

ln 2 1 ln y x c y C x Lecure 14 Appendi B: Some sample problems from Boas Here are some soluions o he sample problems assigned for Chaper 8 8: 6 Soluion: We wan o find he soluion o he following firs order equaion using separaion

More information

Math 23 Spring Differential Equations. Final Exam Due Date: Tuesday, June 6, 5pm

Math 23 Spring Differential Equations. Final Exam Due Date: Tuesday, June 6, 5pm Mah Spring 6 Differenial Equaions Final Exam Due Dae: Tuesday, June 6, 5pm Your name (please prin): Insrucions: This is an open book, open noes exam. You are free o use a calculaor or compuer o check your

More information