Do not turn over until you are told to do so by the Invigilator.

Size: px
Start display at page:

Download "Do not turn over until you are told to do so by the Invigilator."

Transcription

1 UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination INTRODUCTION TO NUMERICAL ANALYSIS MTHE612B Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. Notes are not permitted in this examination. Do not turn over until you are told to do so by the Invigilator. MTHE612B Module Contact: Dr. Jennifer Ryan, MTH Copyright of the University of East Anglia Version: 2

2 The Lagrange interpolating polynomial of degree two is given by p 2 (x) = f(x )L,2 (x) + f(x 1 )L 1,2 (x) + f(x 2 )L 2,2 (x) where L k,2 (x) = 2 j=, j k x x j x k x j. (i) Given the data points x =, x 1 =.6, x 2 =.9, determine the Lagrange interpolating polynomial of degree two for the functions f(x) = cos(x) and f(x) = 1 + x. (ii) Use the interpolants in 1(i) to approximate the actual value of the functions at x =.45, determine actual error at that point and give a bound on the error in the interval (,.9). (iii) Assume the error bound is given by e h3 3! max ξ (,.9) f (3) (ξ). Determine what the spacing between the data should be to obtain an error of e 1 4 of the two functions. for each [1 marks MTHE612B Version: 2

3 Consider the two point Gauss Quadrature rule 1 1 f(x) dx = w 1 f(x 1 ) + w 2 f(x 2 ) such that the nodes x 1, x 2 and weights w 1, w 2 are given by w 1 (x 1 ) m + w 2 (x 2 ) m = 1 m + 1 [1 ( 1)m+1, m =,..., 3. (1) (i) Use Equation (1) and the fact that w 1 = w 2 and x 1 = x 2 to determine the nodes and weights in the Gauss Quadrature formula. [8 marks (ii) Notice the above formula is for integrating a function over ( 1, 1). Transform this formula to apply to integrating a function over the general interval (a, b). That is, determine the formula that applies to b a f(x) dx. (iii) Consider the integral 1 x m dx. (a) For which values of m is the two-point Gauss Quadrature rule is exact? (b) Evaluate the exact integral. For the values of m = 3, 4, approximate the integral using the Gauss quadrature rule and determine the error. [7 marks MTHE612B PLEASE TURN OVER Version: 2

4 We seek a difference formula for the first derivative of a function f(x) at x = of the form such that Q(h) = 1 h ( ( α f h ) ) + α 1 f() + α 2 f(h) 2 f () Q(h) = O(h 2 ). (2) (i) Give the first four terms for the Taylor expansions of f( h ), f(), f(h) around 2 zero. (ii) Use the results from (i) and Equation (2) to show that the coefficients α, α 1 and α 2 satisfy the system /2 1 1/8 1/2 α α 1 α 2 = 1 and that the solution is therefore α = 4 3, α 1 = 1, α 2 = 1 3. [6 marks (iii) Use the information in Table 1 along with Richardson s method which assumes that the form of the error is f () Q(h) = Kh 2 to give an estimate of the error f () Q(1/5) and determine the constant, K. [9 marks x f(x) Table 1: The values of a function, f(x), for a given x. MTHE612B Version: 2

5 Suppose that we are given the nonlinear equation f(x) =. (i) Let p be a fixed point of a function f(x) such that f has a continuous derivative. Consider the fixed point iteration p k+1 = g(p k ) = p k f(p k) α, α R. Show that this always converges to a fixed point of f(x) if < f (p) < α and p sufficiently close to p by first stating the Convergence theorem. [15 marks (ii) Consider the Newton-Raphson method p n+1 = p n f(p n) f (p n ). (a) Determine p 1 using the Newton-Raphson method for f(x) = x 2 2x 2 with p = 1. (b) Can p = 1 be used as the beginning value? Why or why not? MTHE612B PLEASE TURN OVER Version: 2

6 For the numerical integration of the first order differential equation y = f(t, y), y() = y, we use the modified Euler method w n+1 =w n + hf(t n, w n ), w n+1 =w n + h 2 (f(t n, w n ) + f(t n+1, w n+1)), (3) where h denotes the timestep and w n represents the numerical solution at time t n. (i) By using the general form of the equation, y = f(t, y), show that the local truncation error is of order O(h 2 ). [1 marks (ii) Consider the initial value problem d dt [ x1 x 2 [ x1 x 2 [ 1 = 3 4 = [ 1 2. [ x1 x 2 [ + cos(t), Calculate one step with the modified Euler method, in which h = 1 1 and t = using the given initial conditions. (iii) Determine the amplification factor. MTHE612B Version: 2

7 For the numerical solution of the differential equation y = f(t, y) with y() = y, we use the fourth order Runge-Kutta method (RK4): k 1 = hf(t n, w n ), k 3 = hf(t n +.5h, w n +.5k 2 ), k 2 = hf(t n +.5h, w n +.5k 1 ), k 4 = hf(t n + h, w n + k 3 ), w n+1 = w n (k 1 + 2(k 2 + k 3 ) + k 4 ). and consider the equation [ [ d x1 = dt x [ x1 x 2 [ + cos(t). (4) Figure 1: The stability region for RK4. (i) Find the eigenvalues of the matrix in Equation (4). (ii) Use the illustration in Figure 1 to give an approximate stability condition. (iii) Derive the amplification factor for RK4. (iv) Use the fact that y(t n+1 ) = e hλ y(t n ) holds for the exact solution of y = λy to show that the RK4 method solves the homogeneous test equation with a local truncation error of O(h 4 ). MTHE612B PLEASE TURN OVER Version: 2

8 - 8 - END OF PAPER MTHE612B Version: 2

9 MTHE612B/MTHE712B Exam Feedback Overall students did well on the exams, especially students that performed all coursework and laboratory exercises during the semester. Q1: This question was overall done well. The difficulties were: MTHE712B: The definition of conservative scheme and why a finite volume approximation is needed appeared to be lacking. MTHE612B: Overall students did well on this problem, but some had difficulty obtaining an error bound. Q2: The majority of the students did well. The only difficulty seemed to be in evaluating the integral and determining for which values of m the quadrature rule is exact. Q3: The majority of the students did well. However, some had difficulty in deriving the equations that determine the coefficients. Q4: Those that chose to do this problem did well. Q5: The difficulties encountered on this question were: (i) not performing the correct expansion for the modified Euler method; and (ii) neglecting to apply the method to the system of equations. Q5: The main difficulty of this question was not identifying the stability region of the 4th order Runge-Kutta method to be 2.8 λ. 1

Do not turn over until you are told to do so by the Invigilator.

Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 216 17 INTRODUCTION TO NUMERICAL ANALYSIS MTHE712B Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions.

More information

(f(x) P 3 (x)) dx. (a) The Lagrange formula for the error is given by

(f(x) P 3 (x)) dx. (a) The Lagrange formula for the error is given by 1. QUESTION (a) Given a nth degree Taylor polynomial P n (x) of a function f(x), expanded about x = x 0, write down the Lagrange formula for the truncation error, carefully defining all its elements. How

More information

Consistency and Convergence

Consistency and Convergence Jim Lambers MAT 77 Fall Semester 010-11 Lecture 0 Notes These notes correspond to Sections 1.3, 1.4 and 1.5 in the text. Consistency and Convergence We have learned that the numerical solution obtained

More information

Fourth Order RK-Method

Fourth Order RK-Method Fourth Order RK-Method The most commonly used method is Runge-Kutta fourth order method. The fourth order RK-method is y i+1 = y i + 1 6 (k 1 + 2k 2 + 2k 3 + k 4 ), Ordinary Differential Equations (ODE)

More information

Jim Lambers MAT 460/560 Fall Semester Practice Final Exam

Jim Lambers MAT 460/560 Fall Semester Practice Final Exam Jim Lambers MAT 460/560 Fall Semester 2009-10 Practice Final Exam 1. Let f(x) = sin 2x + cos 2x. (a) Write down the 2nd Taylor polynomial P 2 (x) of f(x) centered around x 0 = 0. (b) Write down the corresponding

More information

Do not turn over until you are told to do so by the Invigilator.

Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2013 14 CALCULUS AND MULTIVARIABLE CALCULUS MTHA4005Y Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions.

More information

Numerical Methods for Ordinary Differential Equations

Numerical Methods for Ordinary Differential Equations Numerical Methods for Ordinary Differential Equations Answers of the exercises C Vuik, S van Veldhuizen and S van Loenhout 08 Delft University of Technology Faculty Electrical Engineering, Mathematics

More information

Math 128A Spring 2003 Week 12 Solutions

Math 128A Spring 2003 Week 12 Solutions Math 128A Spring 2003 Week 12 Solutions Burden & Faires 5.9: 1b, 2b, 3, 5, 6, 7 Burden & Faires 5.10: 4, 5, 8 Burden & Faires 5.11: 1c, 2, 5, 6, 8 Burden & Faires 5.9. Higher-Order Equations and Systems

More information

Euler s Method, cont d

Euler s Method, cont d Jim Lambers MAT 461/561 Spring Semester 009-10 Lecture 3 Notes These notes correspond to Sections 5. and 5.4 in the text. Euler s Method, cont d We conclude our discussion of Euler s method with an example

More information

Department of Applied Mathematics and Theoretical Physics. AMA 204 Numerical analysis. Exam Winter 2004

Department of Applied Mathematics and Theoretical Physics. AMA 204 Numerical analysis. Exam Winter 2004 Department of Applied Mathematics and Theoretical Physics AMA 204 Numerical analysis Exam Winter 2004 The best six answers will be credited All questions carry equal marks Answer all parts of each question

More information

Review. Numerical Methods Lecture 22. Prof. Jinbo Bi CSE, UConn

Review. Numerical Methods Lecture 22. Prof. Jinbo Bi CSE, UConn Review Taylor Series and Error Analysis Roots of Equations Linear Algebraic Equations Optimization Numerical Differentiation and Integration Ordinary Differential Equations Partial Differential Equations

More information

Exam in TMA4215 December 7th 2012

Exam in TMA4215 December 7th 2012 Norwegian University of Science and Technology Department of Mathematical Sciences Page of 9 Contact during the exam: Elena Celledoni, tlf. 7359354, cell phone 48238584 Exam in TMA425 December 7th 22 Allowed

More information

5. Hand in the entire exam booklet and your computer score sheet.

5. Hand in the entire exam booklet and your computer score sheet. WINTER 2016 MATH*2130 Final Exam Last name: (PRINT) First name: Student #: Instructor: M. R. Garvie 19 April, 2016 INSTRUCTIONS: 1. This is a closed book examination, but a calculator is allowed. The test

More information

Numerical Methods for Differential Equations

Numerical Methods for Differential Equations Numerical Methods for Differential Equations Chapter 2: Runge Kutta and Linear Multistep methods Gustaf Söderlind and Carmen Arévalo Numerical Analysis, Lund University Textbooks: A First Course in the

More information

Numerical Methods - Initial Value Problems for ODEs

Numerical Methods - Initial Value Problems for ODEs Numerical Methods - Initial Value Problems for ODEs Y. K. Goh Universiti Tunku Abdul Rahman 2013 Y. K. Goh (UTAR) Numerical Methods - Initial Value Problems for ODEs 2013 1 / 43 Outline 1 Initial Value

More information

Lecture Notes to Accompany. Scientific Computing An Introductory Survey. by Michael T. Heath. Chapter 9

Lecture Notes to Accompany. Scientific Computing An Introductory Survey. by Michael T. Heath. Chapter 9 Lecture Notes to Accompany Scientific Computing An Introductory Survey Second Edition by Michael T. Heath Chapter 9 Initial Value Problems for Ordinary Differential Equations Copyright c 2001. Reproduction

More information

8.1 Introduction. Consider the initial value problem (IVP):

8.1 Introduction. Consider the initial value problem (IVP): 8.1 Introduction Consider the initial value problem (IVP): y dy dt = f(t, y), y(t 0)=y 0, t 0 t T. Geometrically: solutions are a one parameter family of curves y = y(t) in(t, y)-plane. Assume solution

More information

Scientific Computing: An Introductory Survey

Scientific Computing: An Introductory Survey Scientific Computing: An Introductory Survey Chapter 9 Initial Value Problems for Ordinary Differential Equations Prof. Michael T. Heath Department of Computer Science University of Illinois at Urbana-Champaign

More information

Jim Lambers MAT 772 Fall Semester Lecture 21 Notes

Jim Lambers MAT 772 Fall Semester Lecture 21 Notes Jim Lambers MAT 772 Fall Semester 21-11 Lecture 21 Notes These notes correspond to Sections 12.6, 12.7 and 12.8 in the text. Multistep Methods All of the numerical methods that we have developed for solving

More information

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University Part 6 Chapter 20 Initial-Value Problems PowerPoints organized by Dr. Michael R. Gustafson II, Duke University All images copyright The McGraw-Hill Companies, Inc. Permission required for reproduction

More information

Numerical Analysis Preliminary Exam 10 am to 1 pm, August 20, 2018

Numerical Analysis Preliminary Exam 10 am to 1 pm, August 20, 2018 Numerical Analysis Preliminary Exam 1 am to 1 pm, August 2, 218 Instructions. You have three hours to complete this exam. Submit solutions to four (and no more) of the following six problems. Please start

More information

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University Part 5 Chapter 21 Numerical Differentiation PowerPoints organized by Dr. Michael R. Gustafson II, Duke University 1 All images copyright The McGraw-Hill Companies, Inc. Permission required for reproduction

More information

Numerical Analysis Preliminary Exam 10.00am 1.00pm, January 19, 2018

Numerical Analysis Preliminary Exam 10.00am 1.00pm, January 19, 2018 Numerical Analysis Preliminary Exam 0.00am.00pm, January 9, 208 Instructions. You have three hours to complete this exam. Submit solutions to four (and no more) of the following six problems. Please start

More information

9.6 Predictor-Corrector Methods

9.6 Predictor-Corrector Methods SEC. 9.6 PREDICTOR-CORRECTOR METHODS 505 Adams-Bashforth-Moulton Method 9.6 Predictor-Corrector Methods The methods of Euler, Heun, Taylor, and Runge-Kutta are called single-step methods because they use

More information

ASSIGNMENT BOOKLET. Numerical Analysis (MTE-10) (Valid from 1 st July, 2011 to 31 st March, 2012)

ASSIGNMENT BOOKLET. Numerical Analysis (MTE-10) (Valid from 1 st July, 2011 to 31 st March, 2012) ASSIGNMENT BOOKLET MTE-0 Numerical Analysis (MTE-0) (Valid from st July, 0 to st March, 0) It is compulsory to submit the assignment before filling in the exam form. School of Sciences Indira Gandhi National

More information

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF MATHEMATICS ACADEMIC YEAR / EVEN SEMESTER QUESTION BANK

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF MATHEMATICS ACADEMIC YEAR / EVEN SEMESTER QUESTION BANK KINGS COLLEGE OF ENGINEERING MA5-NUMERICAL METHODS DEPARTMENT OF MATHEMATICS ACADEMIC YEAR 00-0 / EVEN SEMESTER QUESTION BANK SUBJECT NAME: NUMERICAL METHODS YEAR/SEM: II / IV UNIT - I SOLUTION OF EQUATIONS

More information

Part IB Numerical Analysis

Part IB Numerical Analysis Part IB Numerical Analysis Definitions Based on lectures by G. Moore Notes taken by Dexter Chua Lent 206 These notes are not endorsed by the lecturers, and I have modified them (often significantly) after

More information

Lösning: Tenta Numerical Analysis för D, L. FMN011,

Lösning: Tenta Numerical Analysis för D, L. FMN011, Lösning: Tenta Numerical Analysis för D, L. FMN011, 090527 This exam starts at 8:00 and ends at 12:00. To get a passing grade for the course you need 35 points in this exam and an accumulated total (this

More information

Numerical Differential Equations: IVP

Numerical Differential Equations: IVP Chapter 11 Numerical Differential Equations: IVP **** 4/16/13 EC (Incomplete) 11.1 Initial Value Problem for Ordinary Differential Equations We consider the problem of numerically solving a differential

More information

Bindel, Spring 2012 Intro to Scientific Computing (CS 3220) Week 12: Monday, Apr 16. f(x) dx,

Bindel, Spring 2012 Intro to Scientific Computing (CS 3220) Week 12: Monday, Apr 16. f(x) dx, Panel integration Week 12: Monday, Apr 16 Suppose we want to compute the integral b a f(x) dx In estimating a derivative, it makes sense to use a locally accurate approximation to the function around the

More information

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University

PowerPoints organized by Dr. Michael R. Gustafson II, Duke University Part 6 Chapter 20 Initial-Value Problems PowerPoints organized by Dr. Michael R. Gustafson II, Duke University All images copyright The McGraw-Hill Companies, Inc. Permission required for reproduction

More information

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science ANSWERS OF THE TEST NUMERICAL METHODS FOR DIFFERENTIAL EQUATIONS (WI097 TU) Thursday January 014, 18:0-1:0

More information

Graded Project #1. Part 1. Explicit Runge Kutta methods. Goals Differential Equations FMN130 Gustaf Söderlind and Carmen Arévalo

Graded Project #1. Part 1. Explicit Runge Kutta methods. Goals Differential Equations FMN130 Gustaf Söderlind and Carmen Arévalo 2008-11-07 Graded Project #1 Differential Equations FMN130 Gustaf Söderlind and Carmen Arévalo This homework is due to be handed in on Wednesday 12 November 2008 before 13:00 in the post box of the numerical

More information

MecE 390 Final examination, Winter 2014

MecE 390 Final examination, Winter 2014 MecE 390 Final examination, Winter 2014 Directions: (i) a double-sided 8.5 11 formula sheet is permitted, (ii) no calculators are permitted, (iii) the exam is 80 minutes in duration; please turn your paper

More information

Initial value problems for ordinary differential equations

Initial value problems for ordinary differential equations Initial value problems for ordinary differential equations Xiaojing Ye, Math & Stat, Georgia State University Spring 2019 Numerical Analysis II Xiaojing Ye, Math & Stat, Georgia State University 1 IVP

More information

Examination paper for TMA4215 Numerical Mathematics

Examination paper for TMA4215 Numerical Mathematics Department of Mathematical Sciences Examination paper for TMA425 Numerical Mathematics Academic contact during examination: Trond Kvamsdal Phone: 93058702 Examination date: 6th of December 207 Examination

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions.

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 SETS, NUMBERS AND PROBABILITY MTHA4001Y Time allowed: 2 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. penalised

More information

You may not use your books, notes; calculators are highly recommended.

You may not use your books, notes; calculators are highly recommended. Math 301 Winter 2013-14 Midterm 1 02/06/2014 Time Limit: 60 Minutes Name (Print): Instructor This exam contains 8 pages (including this cover page) and 6 problems. Check to see if any pages are missing.

More information

Unit I (Testing of Hypothesis)

Unit I (Testing of Hypothesis) SUBJECT NAME : Statistics and Numerical Methods SUBJECT CODE : MA645 MATERIAL NAME : Part A questions REGULATION : R03 UPDATED ON : November 07 (Upto N/D 07 Q.P) Unit I (Testing of Hypothesis). State level

More information

Finite Differences for Differential Equations 28 PART II. Finite Difference Methods for Differential Equations

Finite Differences for Differential Equations 28 PART II. Finite Difference Methods for Differential Equations Finite Differences for Differential Equations 28 PART II Finite Difference Methods for Differential Equations Finite Differences for Differential Equations 29 BOUNDARY VALUE PROBLEMS (I) Solving a TWO

More information

NUMERICAL METHODS. x n+1 = 2x n x 2 n. In particular: which of them gives faster convergence, and why? [Work to four decimal places.

NUMERICAL METHODS. x n+1 = 2x n x 2 n. In particular: which of them gives faster convergence, and why? [Work to four decimal places. NUMERICAL METHODS 1. Rearranging the equation x 3 =.5 gives the iterative formula x n+1 = g(x n ), where g(x) = (2x 2 ) 1. (a) Starting with x = 1, compute the x n up to n = 6, and describe what is happening.

More information

Introduction to Numerical Analysis

Introduction to Numerical Analysis Introduction to Numerical Analysis S. Baskar and S. Sivaji Ganesh Department of Mathematics Indian Institute of Technology Bombay Powai, Mumbai 400 076. Introduction to Numerical Analysis Lecture Notes

More information

NUMERICAL ANALYSIS STUDY GUIDE. Topic # Rootfinding

NUMERICAL ANALYSIS STUDY GUIDE. Topic # Rootfinding NUMERICAL ANALYSIS STUDY GUIDE BRYON ARAGAM These are notes compiled during the Summer of 2010 while studying for the UCLA Numerical Analysis qualifying exam. Not all topics listed below are covered, which

More information

Math 216 Final Exam 14 December, 2012

Math 216 Final Exam 14 December, 2012 Math 216 Final Exam 14 December, 2012 This sample exam is provided to serve as one component of your studying for this exam in this course. Please note that it is not guaranteed to cover the material that

More information

ECE257 Numerical Methods and Scientific Computing. Ordinary Differential Equations

ECE257 Numerical Methods and Scientific Computing. Ordinary Differential Equations ECE257 Numerical Methods and Scientific Computing Ordinary Differential Equations Today s s class: Stiffness Multistep Methods Stiff Equations Stiffness occurs in a problem where two or more independent

More information

Introductory Numerical Analysis

Introductory Numerical Analysis Introductory Numerical Analysis Lecture Notes December 16, 017 Contents 1 Introduction to 1 11 Floating Point Numbers 1 1 Computational Errors 13 Algorithm 3 14 Calculus Review 3 Root Finding 5 1 Bisection

More information

CS 450 Numerical Analysis. Chapter 9: Initial Value Problems for Ordinary Differential Equations

CS 450 Numerical Analysis. Chapter 9: Initial Value Problems for Ordinary Differential Equations Lecture slides based on the textbook Scientific Computing: An Introductory Survey by Michael T. Heath, copyright c 2018 by the Society for Industrial and Applied Mathematics. http://www.siam.org/books/cl80

More information

x x2 2 + x3 3 x4 3. Use the divided-difference method to find a polynomial of least degree that fits the values shown: (b)

x x2 2 + x3 3 x4 3. Use the divided-difference method to find a polynomial of least degree that fits the values shown: (b) Numerical Methods - PROBLEMS. The Taylor series, about the origin, for log( + x) is x x2 2 + x3 3 x4 4 + Find an upper bound on the magnitude of the truncation error on the interval x.5 when log( + x)

More information

CS 257: Numerical Methods

CS 257: Numerical Methods CS 57: Numerical Methods Final Exam Study Guide Version 1.00 Created by Charles Feng http://www.fenguin.net CS 57: Numerical Methods Final Exam Study Guide 1 Contents 1 Introductory Matter 3 1.1 Calculus

More information

you expect to encounter difficulties when trying to solve A x = b? 4. A composite quadrature rule has error associated with it in the following form

you expect to encounter difficulties when trying to solve A x = b? 4. A composite quadrature rule has error associated with it in the following form Qualifying exam for numerical analysis (Spring 2017) Show your work for full credit. If you are unable to solve some part, attempt the subsequent parts. 1. Consider the following finite difference: f (0)

More information

MATHEMATICAL PROBLEM SOLVING, MECHANICS AND MODELLING MTHA4004Y

MATHEMATICAL PROBLEM SOLVING, MECHANICS AND MODELLING MTHA4004Y UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2014 2015 MATHEMATICAL PROBLEM SOLVING, MECHANICS AND MODELLING MTHA4004Y Time allowed: 2 Hours Attempt QUESTIONS 1 AND 2 and

More information

Numerical Integra/on

Numerical Integra/on Numerical Integra/on Applica/ons The Trapezoidal Rule is a technique to approximate the definite integral where For 1 st order: f(a) f(b) a b Error Es/mate of Trapezoidal Rule Truncation error: From Newton-Gregory

More information

Virtual University of Pakistan

Virtual University of Pakistan Virtual University of Pakistan File Version v.0.0 Prepared For: Final Term Note: Use Table Of Content to view the Topics, In PDF(Portable Document Format) format, you can check Bookmarks menu Disclaimer:

More information

Module 6 : Solving Ordinary Differential Equations - Initial Value Problems (ODE-IVPs) Section 1 : Introduction

Module 6 : Solving Ordinary Differential Equations - Initial Value Problems (ODE-IVPs) Section 1 : Introduction Module 6 : Solving Ordinary Differential Equations - Initial Value Problems (ODE-IVPs) Section 1 : Introduction 1 Introduction In this module, we develop solution techniques for numerically solving ordinary

More information

Ordinary differential equations - Initial value problems

Ordinary differential equations - Initial value problems Education has produced a vast population able to read but unable to distinguish what is worth reading. G.M. TREVELYAN Chapter 6 Ordinary differential equations - Initial value problems In this chapter

More information

Review Higher Order methods Multistep methods Summary HIGHER ORDER METHODS. P.V. Johnson. School of Mathematics. Semester

Review Higher Order methods Multistep methods Summary HIGHER ORDER METHODS. P.V. Johnson. School of Mathematics. Semester HIGHER ORDER METHODS School of Mathematics Semester 1 2008 OUTLINE 1 REVIEW 2 HIGHER ORDER METHODS 3 MULTISTEP METHODS 4 SUMMARY OUTLINE 1 REVIEW 2 HIGHER ORDER METHODS 3 MULTISTEP METHODS 4 SUMMARY OUTLINE

More information

MATHEMATICAL MODELLING, MECHANICS AND MOD- ELLING MTHA4004Y

MATHEMATICAL MODELLING, MECHANICS AND MOD- ELLING MTHA4004Y UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 MATHEMATICAL MODELLING, MECHANICS AND MOD- ELLING MTHA4004Y Time allowed: 2 Hours Attempt QUESTIONS 1 and 2, and ONE other

More information

MATHEMATICAL METHODS INTERPOLATION

MATHEMATICAL METHODS INTERPOLATION MATHEMATICAL METHODS INTERPOLATION I YEAR BTech By Mr Y Prabhaker Reddy Asst Professor of Mathematics Guru Nanak Engineering College Ibrahimpatnam, Hyderabad SYLLABUS OF MATHEMATICAL METHODS (as per JNTU

More information

AM205: Assignment 3 (due 5 PM, October 20)

AM205: Assignment 3 (due 5 PM, October 20) AM25: Assignment 3 (due 5 PM, October 2) For this assignment, first complete problems 1, 2, 3, and 4, and then complete either problem 5 (on theory) or problem 6 (on an application). If you submit answers

More information

Ordinary Differential Equations II

Ordinary Differential Equations II Ordinary Differential Equations II CS 205A: Mathematical Methods for Robotics, Vision, and Graphics Justin Solomon CS 205A: Mathematical Methods Ordinary Differential Equations II 1 / 33 Almost Done! Last

More information

LECTURE 16 GAUSS QUADRATURE In general for Newton-Cotes (equispaced interpolation points/ data points/ integration points/ nodes).

LECTURE 16 GAUSS QUADRATURE In general for Newton-Cotes (equispaced interpolation points/ data points/ integration points/ nodes). CE 025 - Lecture 6 LECTURE 6 GAUSS QUADRATURE In general for ewton-cotes (equispaced interpolation points/ data points/ integration points/ nodes). x E x S fx dx hw' o f o + w' f + + w' f + E 84 f 0 f

More information

Ordinary Differential Equations II

Ordinary Differential Equations II Ordinary Differential Equations II CS 205A: Mathematical Methods for Robotics, Vision, and Graphics Justin Solomon CS 205A: Mathematical Methods Ordinary Differential Equations II 1 / 29 Almost Done! No

More information

Chap. 20: Initial-Value Problems

Chap. 20: Initial-Value Problems Chap. 20: Initial-Value Problems Ordinary Differential Equations Goal: to solve differential equations of the form: dy dt f t, y The methods in this chapter are all one-step methods and have the general

More information

School of Sciences Indira Gandhi National Open University Maidan Garhi, New Delhi (For January 2012 cycle)

School of Sciences Indira Gandhi National Open University Maidan Garhi, New Delhi (For January 2012 cycle) MTE-0 ASSIGNMENT BOOKLET Bachelor's Degree Programme Numerical Analysis (MTE-0) (Valid from st January, 0 to st December, 0) School of Sciences Indira Gandhi National Open University Maidan Garhi, New

More information

Department of Applied Mathematics Preliminary Examination in Numerical Analysis August, 2013

Department of Applied Mathematics Preliminary Examination in Numerical Analysis August, 2013 Department of Applied Mathematics Preliminary Examination in Numerical Analysis August, 013 August 8, 013 Solutions: 1 Root Finding (a) Let the root be x = α We subtract α from both sides of x n+1 = x

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions.

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 FERMAT S LAST THEOREM MTHD6024B Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. penalised

More information

Numerical Analysis Solution of Algebraic Equation (non-linear equation) 1- Trial and Error. 2- Fixed point

Numerical Analysis Solution of Algebraic Equation (non-linear equation) 1- Trial and Error. 2- Fixed point Numerical Analysis Solution of Algebraic Equation (non-linear equation) 1- Trial and Error In this method we assume initial value of x, and substitute in the equation. Then modify x and continue till we

More information

Numerical Analysis: Interpolation Part 1

Numerical Analysis: Interpolation Part 1 Numerical Analysis: Interpolation Part 1 Computer Science, Ben-Gurion University (slides based mostly on Prof. Ben-Shahar s notes) 2018/2019, Fall Semester BGU CS Interpolation (ver. 1.00) AY 2018/2019,

More information

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science ANSWERS OF THE TEST NUMERICAL METHODS FOR DIFFERENTIAL EQUATIONS ( WI3097 TU AESB0 ) Thursday April 6

More information

FLUID DYNAMICS, THEORY AND COMPUTATION MTHA5002Y

FLUID DYNAMICS, THEORY AND COMPUTATION MTHA5002Y UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 FLUID DYNAMICS, THEORY AND COMPUTATION MTHA5002Y Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions.

More information

Section 7.4 Runge-Kutta Methods

Section 7.4 Runge-Kutta Methods Section 7.4 Runge-Kutta Methods Key terms: Taylor methods Taylor series Runge-Kutta; methods linear combinations of function values at intermediate points Alternatives to second order Taylor methods Fourth

More information

Janacek statistics tables (2009 edition) are available on your desk. Do not turn over until you are told to do so by the Invigilator.

Janacek statistics tables (2009 edition) are available on your desk. Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2016 17 CALCULUS AND PROBABILITY MTHB4006Y Time allowed: 2 Hours Attempt THREE questions. Janacek statistics tables (2009 edition)

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions.

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 SETS, NUMBERS AND PROBABILITY MTHA4001Y Time allowed: 2 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. penalised

More information

NUMERICAL ANALYSIS PROBLEMS

NUMERICAL ANALYSIS PROBLEMS NUMERICAL ANALYSIS PROBLEMS JAMES KEESLING The problems that follow illustrate the methods covered in class. They are typical of the types of problems that will be on the tests.. Solving Equations Problem.

More information

Contents. I Basic Methods 13

Contents. I Basic Methods 13 Preface xiii 1 Introduction 1 I Basic Methods 13 2 Convergent and Divergent Series 15 2.1 Introduction... 15 2.1.1 Power series: First steps... 15 2.1.2 Further practical aspects... 17 2.2 Differential

More information

The family of Runge Kutta methods with two intermediate evaluations is defined by

The family of Runge Kutta methods with two intermediate evaluations is defined by AM 205: lecture 13 Last time: Numerical solution of ordinary differential equations Today: Additional ODE methods, boundary value problems Thursday s lecture will be given by Thomas Fai Assignment 3 will

More information

Notes on Numerical Analysis

Notes on Numerical Analysis Notes on Numerical Analysis Alejandro Cantarero This set of notes covers topics that most commonly show up on the Numerical Analysis qualifying exam in the Mathematics department at UCLA. Each section

More information

USHA RAMA COLLEGE OF ENGINEERING & TECHNOLOGY

USHA RAMA COLLEGE OF ENGINEERING & TECHNOLOGY Code No: R007/R0 Set No. I B.Tech I Semester Supplementary Examinations, Feb/Mar 04 MATHEMATICAL METHODS ( Common to Civil Engineering, Electrical & Electronics Engineering, Computer Science & Engineering,

More information

TABLE OF CONTENTS INTRODUCTION, APPROXIMATION & ERRORS 1. Chapter Introduction to numerical methods 1 Multiple-choice test 7 Problem set 9

TABLE OF CONTENTS INTRODUCTION, APPROXIMATION & ERRORS 1. Chapter Introduction to numerical methods 1 Multiple-choice test 7 Problem set 9 TABLE OF CONTENTS INTRODUCTION, APPROXIMATION & ERRORS 1 Chapter 01.01 Introduction to numerical methods 1 Multiple-choice test 7 Problem set 9 Chapter 01.02 Measuring errors 11 True error 11 Relative

More information

Lecture 4: Numerical solution of ordinary differential equations

Lecture 4: Numerical solution of ordinary differential equations Lecture 4: Numerical solution of ordinary differential equations Department of Mathematics, ETH Zürich General explicit one-step method: Consistency; Stability; Convergence. High-order methods: Taylor

More information

Exam 2. Average: 85.6 Median: 87.0 Maximum: Minimum: 55.0 Standard Deviation: Numerical Methods Fall 2011 Lecture 20

Exam 2. Average: 85.6 Median: 87.0 Maximum: Minimum: 55.0 Standard Deviation: Numerical Methods Fall 2011 Lecture 20 Exam 2 Average: 85.6 Median: 87.0 Maximum: 100.0 Minimum: 55.0 Standard Deviation: 10.42 Fall 2011 1 Today s class Multiple Variable Linear Regression Polynomial Interpolation Lagrange Interpolation Newton

More information

Numerical Methods for Engineers. and Scientists. Applications using MATLAB. An Introduction with. Vish- Subramaniam. Third Edition. Amos Gilat.

Numerical Methods for Engineers. and Scientists. Applications using MATLAB. An Introduction with. Vish- Subramaniam. Third Edition. Amos Gilat. Numerical Methods for Engineers An Introduction with and Scientists Applications using MATLAB Third Edition Amos Gilat Vish- Subramaniam Department of Mechanical Engineering The Ohio State University Wiley

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator.

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2016 17 SEMIGROUP THEORY MTHE6011A Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. Notes are not permitted

More information

Module Contact: Dr Steven Hayward, CMP Copyright of the University of East Anglia Version 1

Module Contact: Dr Steven Hayward, CMP Copyright of the University of East Anglia Version 1 UNIVERSITY OF EAST ANGLIA School of Computing Sciences Main Series UG Examination 2016-17 MATHEMATICS FOR COMPUTING B CMP-4005Y Time allowed: 2 hours Answer ANY SIX questions out of SEVEN. Notes are not

More information

Numerical Analysis. A Comprehensive Introduction. H. R. Schwarz University of Zürich Switzerland. with a contribution by

Numerical Analysis. A Comprehensive Introduction. H. R. Schwarz University of Zürich Switzerland. with a contribution by Numerical Analysis A Comprehensive Introduction H. R. Schwarz University of Zürich Switzerland with a contribution by J. Waldvogel Swiss Federal Institute of Technology, Zürich JOHN WILEY & SONS Chichester

More information

Do not turn over until you are told to do so by the Invigilator.

Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2012 2013 MECHANICS AND MODELLING MTH-1C32 Time allowed: 2 Hours Attempt QUESTIONS 1 AND 2 and THREE other questions. Notes are

More information

Multistage Methods I: Runge-Kutta Methods

Multistage Methods I: Runge-Kutta Methods Multistage Methods I: Runge-Kutta Methods Varun Shankar January, 0 Introduction Previously, we saw that explicit multistep methods (AB methods) have shrinking stability regions as their orders are increased.

More information

Numerical Analysis Comprehensive Exam Questions

Numerical Analysis Comprehensive Exam Questions Numerical Analysis Comprehensive Exam Questions 1. Let f(x) = (x α) m g(x) where m is an integer and g(x) C (R), g(α). Write down the Newton s method for finding the root α of f(x), and study the order

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator.

Attempt QUESTIONS 1 and 2, and THREE other questions. Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2016 17 SEMIGROUP THEORY WITH ADVANCED TOPICS MTHE7011A Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions.

More information

Chapter 11 ORDINARY DIFFERENTIAL EQUATIONS

Chapter 11 ORDINARY DIFFERENTIAL EQUATIONS Chapter 11 ORDINARY DIFFERENTIAL EQUATIONS The general form of a first order differential equations is = f(x, y) with initial condition y(a) = y a We seek the solution y = y(x) for x > a This is shown

More information

Numerical Analysis. Introduction to. Rostam K. Saeed Karwan H.F. Jwamer Faraidun K. Hamasalh

Numerical Analysis. Introduction to. Rostam K. Saeed Karwan H.F. Jwamer Faraidun K. Hamasalh Iraq Kurdistan Region Ministry of Higher Education and Scientific Research University of Sulaimani Faculty of Science and Science Education School of Science Education-Mathematics Department Introduction

More information

Physics 584 Computational Methods

Physics 584 Computational Methods Physics 584 Computational Methods Introduction to Matlab and Numerical Solutions to Ordinary Differential Equations Ryan Ogliore April 18 th, 2016 Lecture Outline Introduction to Matlab Numerical Solutions

More information

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions.

Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt additional questions. UNIVERSITY OF EAST ANGLIA School of Mathematics Main Series UG Examination 2017 18 CRYPTOGRAPHY MTHD6025A Time allowed: 3 Hours Attempt QUESTIONS 1 and 2, and THREE other questions. penalised if you attempt

More information

NUMERICAL METHODS FOR ENGINEERING APPLICATION

NUMERICAL METHODS FOR ENGINEERING APPLICATION NUMERICAL METHODS FOR ENGINEERING APPLICATION Second Edition JOEL H. FERZIGER A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York / Chichester / Weinheim / Brisbane / Singapore / Toronto

More information

Math 113 (Calculus 2) Exam 4

Math 113 (Calculus 2) Exam 4 Math 3 (Calculus ) Exam 4 November 0 November, 009 Sections 0, 3 7 Name Student ID Section Instructor In some cases a series may be seen to converge or diverge for more than one reason. For such problems

More information

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Matematics and Computer Science. ANSWERS OF THE TEST NUMERICAL METHODS FOR DIFFERENTIAL EQUATIONS (WI3097 TU) Tuesday January 9 008, 9:00-:00

More information

Applied Math for Engineers

Applied Math for Engineers Applied Math for Engineers Ming Zhong Lecture 15 March 28, 2018 Ming Zhong (JHU) AMS Spring 2018 1 / 28 Recap Table of Contents 1 Recap 2 Numerical ODEs: Single Step Methods 3 Multistep Methods 4 Method

More information

Ordinary Differential Equations

Ordinary Differential Equations CHAPTER 8 Ordinary Differential Equations 8.1. Introduction My section 8.1 will cover the material in sections 8.1 and 8.2 in the book. Read the book sections on your own. I don t like the order of things

More information

Checking the Radioactive Decay Euler Algorithm

Checking the Radioactive Decay Euler Algorithm Lecture 2: Checking Numerical Results Review of the first example: radioactive decay The radioactive decay equation dn/dt = N τ has a well known solution in terms of the initial number of nuclei present

More information

Solving scalar IVP s : Runge-Kutta Methods

Solving scalar IVP s : Runge-Kutta Methods Solving scalar IVP s : Runge-Kutta Methods Josh Engwer Texas Tech University March 7, NOTATION: h step size x n xt) t n+ t + h x n+ xt n+ ) xt + h) dx = ft, x) SCALAR IVP ASSUMED THROUGHOUT: dt xt ) =

More information