Change of Variables. f(x, y) da = (1) If the transformation T hasn t already been given, come up with the transformation to use.

Size: px
Start display at page:

Download "Change of Variables. f(x, y) da = (1) If the transformation T hasn t already been given, come up with the transformation to use."

Transcription

1 MATH 2Q Spring 26 Daid Nichols Change of Variables Change of ariables in mltiple integrals is complicated, bt it can be broken down into steps as follows. The starting point is a doble integral in & y. f(, y) da () If the transformation T hasn t already been gien, come p with the transformation to se. (2) Figre ot both directions of the transformation. (3) Fill in the following information in any order: f(, y) da = S f((, ), y(, )) (, ) d d (a) change to S Note that depending on the problem yo might se either order of integration, d d or d d. Eample Use the transformation = 4 ( + ), y = 4 ( 3) to ealate the integral (4 + 8y) da, where is the parallelogram with ertices (, 3), (, 3), (3, ), and (, 5). I hae already been gien the transformation. 2 To get & in terms of & y, I sole for and in the system I was gien (notice that I e distribted ot the 4 in each eqation): = () y = (2) Sbtracting (2) from () gies me = y, and adding three times () to (2) gies me = 3 + y. 3(a) This is nearly always the hardest step, and it can reqire a lot of work. In order to figre ot S, I first need to nderstand what looks like. So I m going to draw a pictre. It isn t strictly necessary to draw a pictre, bt I find that if I hae a pictre to work with, the rest of the problem gets easier. The problem statement has told me that is a parallelogram with certain corners, so the first step to draw is to mark the corner points I was gien. The reslt appears on the net page. We need to know how to get (, y) from (, ) to calclate the Jacobian, and we need to know how to get (, ) from (, y) to figre ot the region of integration.

2 y (, 5) (, 3) (3, ) (, 3) Then I connect the dots to draw : y (, 5) (, 3) (3, ) (, 3) The point of drawing this pictre of (the region of integration on the, y side of the transformation) was so that I cold figre ot S (the region of integration oer on the, side of the transformation). To figre ot S, all I hae to do is figre ot the bondary and then eerything else will fill itself in. In fact, all I hae to is figre ot either (i) what the transformation does to each of the 4 sides of, or else (ii) what the transformation does to each of the 4 corners of. Once I do either of those, the rest of S will fill itself in. I know from step (2) that = y, = 3 + y. So plgging in the for corner points of gies me the corners of S: (, y) (, ) Corner : (, 3) (, ) Corner 2: (, 3) (4, ) Corner 3: (3, ) (4, 8) Corner 4: (, 5) (, 8)

3 Now I can mark the corners of S... (, 8) (4, 8) (, ) (4, )...and fill in the rest. (, 8) (4, 8) S (, ) (4, ) I e now got the hardest part ot of the way, and I can fill in part of the integral: (4 + 8y) da = f((, ), y(, )) (, ) d d (a) change to S 3(b) Since I already know what & y are as fnctions of &, I can jst plg in that information: [ ] [ ] 4 + 8y = 4[(, )] + 8[y(, )] = 4 ( + ) + 8 ( 3) =

4 Now I can fill in another part of the integral: (4 + 8y) da = (3 5) (, ) d d (a) change to S 3(c) The last ingredient I need for the change of ariables is the Jacobian. Since I know what & y are as fnctions of &, I can take the deriaties and plg them in to get the Jacobian: [ ] [ ] (, ) = det /4 /4 = det = 3/4 / = 4. This is the last part of the integral that I need to fill in: (4 + 8y) da = (3 5) 4 d d (a) change to S Now that I m done with the change of ariables, I can ealate the integral in the sal way: (4 + 8y) da = (3 5) 4 d d = 4 = 4 = 4 = (3 5) d d (factor ot the /4) [ ] =8 d = (inside integral first) (96 4) d (plg in limits) [ ] 4 (now the integral) = 92 (plg in limits)

5 Eample 2 Make an appropriate change of ariables to ealate the integral ( + y)e2 y 2 da, where is the rectangle enclosed by the lines y =, y = 2, + y =, and + y = 3. I need to come p with a change of ariables that cold make this integral easier. There are two ways I cold approach this: I cold try to make the integrand nicer or I cold try to make the region of integration nicer. Alternatiely, I cold try to look at both the integrand and the region of integration while I try to come p with the transformation to se. After staring at the problem for a while, I start to notice some patterns. ( + y) shows p in a lot of places: it s mentioned twice in the description of, it appears in the integrand, and in fact if I write ( + y)e 2 y 2 = ( + y)e (+y)( y) then I notice that ( + y) shows p twice in the integrand. So I cold simplify a lot of pieces of the problem down to jst if I set = + y. That leaes me with e ( y) in the integral, so the natral choice of is = y, which trns the integrand into e. 2 I already know how to find & in terms of & y, so now I want to know how to find & y in terms of &. In other words, I need to sole this system for and y: Adding ()+(2) gies me + = 2, so = + y () = y (2) = ( + ), 2 and sbtracting () (2) gies me = 2y, so y = ( ). 2 3(a) In order to find S, I first need to nderstand. Once again, I ll draw a pictre since that s the easiest way for me to analyze the information that I hae. The problem describes based on 4 lines, so the first thing I m going to do to make a pictre of is draw those lines: y + y = 3 y = y = 2 + y =

6 The problem statement tells me that is the rectangle enclosed by those lines: y y = + y = 3 + y = y = 2 Since I know how to trn & y into &, I can now apply the transformation to each of the sides of in order to get the sides of S. Now I can draw the sides of S..., y, y = = y = 2 = 2 + y = = + y = 3 = 3 = 2 = = = 3...and fill in the rest. S With the hardest part ot of the way, and I can fill in part of the integral: ( + y)e 2 y 2 da = f((, ), y(, )) (, ) d d (a) change to S

7 3(b) I already saw how the integrand is transformed back when I was coming p with the transformation to se: ( + y)e 2 y 2 = ( + y)e 2 y 2 = ( + y)e (+y)( y) = e. Ths ( + y)e 2 y 2 da = e (, ) d d (a) change to S 3(c) I know what & y are as fnctions of &, so I can take the deriaties and plg them in to get the Jacobian: [ ] [ ] (, ) = det /2 /2 = det = /2 /2 4 4 = 2. This is the last part of the integral that I need to fill in: ( + y)e 2 y 2 da = e 2 d d (a) change to S Now that I m done with the change of ariables, I can ealate the integral in the sal way: 2 3 ( + y)e 2 y 2 da = e 2 d d = 2 = e d d [e ] =2 d = = (e 2 ) d 2 = [ ] e2 = ( 2 2 e = e6 7 4 )

Change of Variables. (f T) JT. f = U

Change of Variables. (f T) JT. f = U Change of Variables 4-5-8 The change of ariables formla for mltiple integrals is like -sbstittion for single-ariable integrals. I ll gie the general change of ariables formla first, and consider specific

More information

3.3 Operations With Vectors, Linear Combinations

3.3 Operations With Vectors, Linear Combinations Operations With Vectors, Linear Combinations Performance Criteria: (d) Mltiply ectors by scalars and add ectors, algebraically Find linear combinations of ectors algebraically (e) Illstrate the parallelogram

More information

Lecture 3. (2) Last time: 3D space. The dot product. Dan Nichols January 30, 2018

Lecture 3. (2) Last time: 3D space. The dot product. Dan Nichols January 30, 2018 Lectre 3 The dot prodct Dan Nichols nichols@math.mass.ed MATH 33, Spring 018 Uniersity of Massachsetts Janary 30, 018 () Last time: 3D space Right-hand rle, the three coordinate planes 3D coordinate system:

More information

MAT389 Fall 2016, Problem Set 6

MAT389 Fall 2016, Problem Set 6 MAT389 Fall 016, Problem Set 6 Trigonometric and hperbolic fnctions 6.1 Show that e iz = cos z + i sin z for eer comple nmber z. Hint: start from the right-hand side and work or wa towards the left-hand

More information

Section 7.4: Integration of Rational Functions by Partial Fractions

Section 7.4: Integration of Rational Functions by Partial Fractions Section 7.4: Integration of Rational Fnctions by Partial Fractions This is abot as complicated as it gets. The Method of Partial Fractions Ecept for a few very special cases, crrently we have no way to

More information

1 The space of linear transformations from R n to R m :

1 The space of linear transformations from R n to R m : Math 540 Spring 20 Notes #4 Higher deriaties, Taylor s theorem The space of linear transformations from R n to R m We hae discssed linear transformations mapping R n to R m We can add sch linear transformations

More information

EE2 Mathematics : Functions of Multiple Variables

EE2 Mathematics : Functions of Multiple Variables EE2 Mathematics : Fnctions of Mltiple Variables http://www2.imperial.ac.k/ nsjones These notes are not identical word-for-word with m lectres which will be gien on the blackboard. Some of these notes ma

More information

Linear Strain Triangle and other types of 2D elements. By S. Ziaei Rad

Linear Strain Triangle and other types of 2D elements. By S. Ziaei Rad Linear Strain Triangle and other tpes o D elements B S. Ziaei Rad Linear Strain Triangle (LST or T6 This element is also called qadratic trianglar element. Qadratic Trianglar Element Linear Strain Triangle

More information

Unfortunately the derivative of a product is not the product of the derivatives. For example, if

Unfortunately the derivative of a product is not the product of the derivatives. For example, if Prodct Rle Unortnately te deriatie o a prodct is not te prodct o te deriaties. For eample, i Ten p So is p bt 11 1, and tey are not eal in general. Tat [ is not ] in general To compte te deriatie o a prodct

More information

MATH2715: Statistical Methods

MATH2715: Statistical Methods MATH275: Statistical Methods Exercises III (based on lectres 5-6, work week 4, hand in lectre Mon 23 Oct) ALL qestions cont towards the continos assessment for this modle. Q. If X has a niform distribtion

More information

ANOVA INTERPRETING. It might be tempting to just look at the data and wing it

ANOVA INTERPRETING. It might be tempting to just look at the data and wing it Introdction to Statistics in Psychology PSY 2 Professor Greg Francis Lectre 33 ANalysis Of VAriance Something erss which thing? ANOVA Test statistic: F = MS B MS W Estimated ariability from noise and mean

More information

Graphs and Networks Lecture 5. PageRank. Lecturer: Daniel A. Spielman September 20, 2007

Graphs and Networks Lecture 5. PageRank. Lecturer: Daniel A. Spielman September 20, 2007 Graphs and Networks Lectre 5 PageRank Lectrer: Daniel A. Spielman September 20, 2007 5.1 Intro to PageRank PageRank, the algorithm reportedly sed by Google, assigns a nmerical rank to eery web page. More

More information

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2 MATH 307 Vectors in Rn Dr. Neal, WKU Matrices of dimension 1 n can be thoght of as coordinates, or ectors, in n- dimensional space R n. We can perform special calclations on these ectors. In particlar,

More information

CS 450: COMPUTER GRAPHICS VECTORS SPRING 2016 DR. MICHAEL J. REALE

CS 450: COMPUTER GRAPHICS VECTORS SPRING 2016 DR. MICHAEL J. REALE CS 45: COMPUTER GRPHICS VECTORS SPRING 216 DR. MICHEL J. RELE INTRODUCTION In graphics, we are going to represent objects and shapes in some form or other. First, thogh, we need to figre ot how to represent

More information

10.2 Solving Quadratic Equations by Completing the Square

10.2 Solving Quadratic Equations by Completing the Square . Solving Qadratic Eqations b Completing the Sqare Consider the eqation ( ) We can see clearl that the soltions are However, What if the eqation was given to s in standard form, that is 6 How wold we go

More information

STEP Support Programme. STEP III Hyperbolic Functions: Solutions

STEP Support Programme. STEP III Hyperbolic Functions: Solutions STEP Spport Programme STEP III Hyperbolic Fnctions: Soltions Start by sing the sbstittion t cosh x. This gives: sinh x cosh a cosh x cosh a sinh x t sinh x dt t dt t + ln t ln t + ln cosh a ln ln cosh

More information

5.5 U-substitution. Solution. Z

5.5 U-substitution. Solution. Z CHAPTER 5. THE DEFINITE INTEGRAL 22 5.5 U-sbstittion Eample. (a) Fin the erivative of sin( 2 ). (b) Fin the anti-erivative cos( 2 ). Soltion. (a) We se the chain rle: sin(2 )=cos( 2 )( 2 ) 0 =cos( 2 )2

More information

The Brauer Manin obstruction

The Brauer Manin obstruction The Braer Manin obstrction Martin Bright 17 April 2008 1 Definitions Let X be a smooth, geometrically irredcible ariety oer a field k. Recall that the defining property of an Azmaya algebra A is that,

More information

Lesson 81: The Cross Product of Vectors

Lesson 81: The Cross Product of Vectors Lesson 8: The Cross Prodct of Vectors IBHL - SANTOWSKI In this lesson yo will learn how to find the cross prodct of two ectors how to find an orthogonal ector to a plane defined by two ectors how to find

More information

Chapter 6 Momentum Transfer in an External Laminar Boundary Layer

Chapter 6 Momentum Transfer in an External Laminar Boundary Layer 6. Similarit Soltions Chapter 6 Momentm Transfer in an Eternal Laminar Bondar Laer Consider a laminar incompressible bondar laer with constant properties. Assme the flow is stead and two-dimensional aligned

More information

A Blue Lagoon Function

A Blue Lagoon Function Downloaded from orbit.dt.dk on: Oct 11, 2018 A Ble Lagoon Fnction Markorsen, Steen Pblication date: 2007 Link back to DTU Orbit Citation (APA): Markorsen, S., (2007). A Ble Lagoon Fnction General rights

More information

Reduction of over-determined systems of differential equations

Reduction of over-determined systems of differential equations Redction of oer-determined systems of differential eqations Maim Zaytse 1) 1, ) and Vyachesla Akkerman 1) Nclear Safety Institte, Rssian Academy of Sciences, Moscow, 115191 Rssia ) Department of Mechanical

More information

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n 12.4 The Cross Prodct 873 12.4 The Cross Prodct In stdying lines in the plane, when we needed to describe how a line was tilting, we sed the notions of slope and angle of inclination. In space, we want

More information

Note: Please use the actual date you accessed this material in your citation.

Note: Please use the actual date you accessed this material in your citation. MIT OpenCourseWare http://ocw.mit.edu 18.02 Multivariable Calculus, Fall 2007 Please use the following citation format: Denis Auroux. 18.02 Multivariable Calculus, Fall 2007. (Massachusetts Institute of

More information

6.4 VECTORS AND DOT PRODUCTS

6.4 VECTORS AND DOT PRODUCTS 458 Chapter 6 Additional Topics in Trigonometry 6.4 VECTORS AND DOT PRODUCTS What yo shold learn ind the dot prodct of two ectors and se the properties of the dot prodct. ind the angle between two ectors

More information

We automate the bivariate change-of-variables technique for bivariate continuous random variables with

We automate the bivariate change-of-variables technique for bivariate continuous random variables with INFORMS Jornal on Compting Vol. 4, No., Winter 0, pp. 9 ISSN 09-9856 (print) ISSN 56-558 (online) http://dx.doi.org/0.87/ijoc.046 0 INFORMS Atomating Biariate Transformations Jeff X. Yang, John H. Drew,

More information

ECON3120/4120 Mathematics 2, spring 2009

ECON3120/4120 Mathematics 2, spring 2009 University of Oslo Department of Economics Arne Strøm ECON3/4 Mathematics, spring 9 Problem soltions for Seminar 4, 6 Febrary 9 (For practical reasons some of the soltions may inclde problem parts that

More information

LESSON 4: INTEGRATION BY PARTS (I) MATH FALL 2018

LESSON 4: INTEGRATION BY PARTS (I) MATH FALL 2018 LESSON 4: INTEGRATION BY PARTS (I) MATH 6 FALL 8 ELLEN WELD. Integration by Parts We introduce another method for ealuating integrals called integration by parts. The key is the following : () u d = u

More information

u P(t) = P(x,y) r v t=0 4/4/2006 Motion ( F.Robilliard) 1

u P(t) = P(x,y) r v t=0 4/4/2006 Motion ( F.Robilliard) 1 y g j P(t) P(,y) r t0 i 4/4/006 Motion ( F.Robilliard) 1 Motion: We stdy in detail three cases of motion: 1. Motion in one dimension with constant acceleration niform linear motion.. Motion in two dimensions

More information

Dynamics ( 동역학 ) Ch.2 Motion of Translating Bodies (2.1 & 2.2)

Dynamics ( 동역학 ) Ch.2 Motion of Translating Bodies (2.1 & 2.2) Dynamics ( 동역학 ) Ch. Motion of Translating Bodies (. &.) Motion of Translating Bodies This chapter is usually referred to as Kinematics of Particles. Particles: In dynamics, a particle is a body without

More information

UNDERSTAND MOTION IN ONE AND TWO DIMENSIONS

UNDERSTAND MOTION IN ONE AND TWO DIMENSIONS SUBAREA I. COMPETENCY 1.0 UNDERSTAND MOTION IN ONE AND TWO DIMENSIONS MECHANICS Skill 1.1 Calculating displacement, aerage elocity, instantaneous elocity, and acceleration in a gien frame of reference

More information

Mean Value Formulae for Laplace and Heat Equation

Mean Value Formulae for Laplace and Heat Equation Mean Vale Formlae for Laplace and Heat Eqation Abhinav Parihar December 7, 03 Abstract Here I discss a method to constrct the mean vale theorem for the heat eqation. To constrct sch a formla ab initio,

More information

TESTING MEANS. we want to test. but we need to know if 2 1 = 2 2 if it is, we use the methods described last time pooled estimate of variance

TESTING MEANS. we want to test. but we need to know if 2 1 = 2 2 if it is, we use the methods described last time pooled estimate of variance Introdction to Statistics in Psychology PSY Profess Greg Francis Lectre 6 Hypothesis testing f two sample case Planning a replication stdy TESTING MENS we want to test H : µ µ H a : µ µ 6 bt we need to

More information

ON THE PERFORMANCE OF LOW

ON THE PERFORMANCE OF LOW Monografías Matemáticas García de Galdeano, 77 86 (6) ON THE PERFORMANCE OF LOW STORAGE ADDITIVE RUNGE-KUTTA METHODS Inmaclada Higeras and Teo Roldán Abstract. Gien a differential system that inoles terms

More information

LECTURE 1: INTRODUCTION, VECTORS, AND DOT PRODUCTS

LECTURE 1: INTRODUCTION, VECTORS, AND DOT PRODUCTS LECTURE 1: INTRODUCTION, VECTORS, AND DOT PRODUCTS MA1111: LINEAR ALGEBRA I, MICHAELMAS 2016 1. Introduction Firstly, I want to point out that I am here to help, so if you hae a question about a lecture

More information

LECTURE 2: CROSS PRODUCTS, MULTILINEARITY, AND AREAS OF PARALLELOGRAMS

LECTURE 2: CROSS PRODUCTS, MULTILINEARITY, AND AREAS OF PARALLELOGRAMS LECTURE : CROSS PRODUCTS, MULTILINEARITY, AND AREAS OF PARALLELOGRAMS MA1111: LINEAR ALGEBRA I, MICHAELMAS 016 1. Finishing up dot products Last time we stated the following theorem, for which I owe you

More information

Integration of Basic Functions. Session 7 : 9/23 1

Integration of Basic Functions. Session 7 : 9/23 1 Integration o Basic Fnctions Session 7 : 9/3 Antiderivation Integration Deinition: Taking the antiderivative, or integral, o some nction F(), reslts in the nction () i ()F() Pt simply: i yo take the integral

More information

Diagonalization of Quadratic Forms. Recall in days past when you were given an equation which looked like

Diagonalization of Quadratic Forms. Recall in days past when you were given an equation which looked like Diagoalizatio of Qadratic Forms Recall i das past whe o were gie a eqatio which looked like ad o were asked to sketch the set of poits which satisf this eqatio. It was ecessar to complete the sqare so

More information

Numerical Model for Studying Cloud Formation Processes in the Tropics

Numerical Model for Studying Cloud Formation Processes in the Tropics Astralian Jornal of Basic and Applied Sciences, 5(2): 189-193, 211 ISSN 1991-8178 Nmerical Model for Stdying Clod Formation Processes in the Tropics Chantawan Noisri, Dsadee Skawat Department of Mathematics

More information

PhysicsAndMathsTutor.com

PhysicsAndMathsTutor.com C Integration - By sbstittion PhysicsAndMathsTtor.com. Using the sbstittion cos +, or otherwise, show that e cos + sin d e(e ) (Total marks). (a) Using the sbstittion cos, or otherwise, find the eact vale

More information

DEFINITE INTEGRALS & NUMERIC INTEGRATION

DEFINITE INTEGRALS & NUMERIC INTEGRATION DEFINITE INTEGRALS & NUMERIC INTEGRATION Calculus answers two very important questions. The first, how to find the instantaneous rate of change, we answered with our study of the derivative. We are now

More information

Logarithmic, Exponential and Other Transcendental Functions

Logarithmic, Exponential and Other Transcendental Functions Logarithmic, Eponential an Other Transcenental Fnctions 5: The Natral Logarithmic Fnction: Differentiation The Definition First, yo mst know the real efinition of the natral logarithm: ln= t (where > 0)

More information

1. Linear Motion. Table of Contents. 1.1 Linear Motion: Velocity Time Graphs (Multi Stage) 1.2 Linear Motion: Velocity Time Graphs (Up and Down)

1. Linear Motion. Table of Contents. 1.1 Linear Motion: Velocity Time Graphs (Multi Stage) 1.2 Linear Motion: Velocity Time Graphs (Up and Down) . LINEAR MOTION www.mathspoints.ie. Linear Motion Table of Contents. Linear Motion: Velocity Time Graphs (Multi Stage). Linear Motion: Velocity Time Graphs (Up and Down).3 Linear Motion: Common Initial

More information

Chapter 4: Techniques of Circuit Analysis

Chapter 4: Techniques of Circuit Analysis Chapter 4: Techniques of Circuit Analysis This chapter gies us many useful tools for soling and simplifying circuits. We saw a few simple tools in the last chapter (reduction of circuits ia series and

More information

Math 144 Activity #9 Introduction to Vectors

Math 144 Activity #9 Introduction to Vectors 144 p 1 Math 144 ctiity #9 Introduction to Vectors Often times you hear people use the words speed and elocity. Is there a difference between the two? If so, what is the difference? Discuss this with your

More information

MATH 12 CLASS 23 NOTES, NOV Contents 1. Change of variables: the Jacobian 1

MATH 12 CLASS 23 NOTES, NOV Contents 1. Change of variables: the Jacobian 1 MATH 12 CLASS 23 NOTES, NOV 11 211 Contents 1. Change of variables: the Jacobian 1 1. Change of variables: the Jacobian So far, we have seen three examples of situations where we change variables to help

More information

SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT1101 UNIT III FUNCTIONS OF SEVERAL VARIABLES. Jacobians

SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT1101 UNIT III FUNCTIONS OF SEVERAL VARIABLES. Jacobians SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT0 UNIT III FUNCTIONS OF SEVERAL VARIABLES Jacobians Changing ariable is something e come across er oten in Integration There are man reasons or changing

More information

Derivation of 2D Power-Law Velocity Distribution Using Entropy Theory

Derivation of 2D Power-Law Velocity Distribution Using Entropy Theory Entrop 3, 5, -3; doi:.339/e54 Article OPEN ACCESS entrop ISSN 99-43 www.mdpi.com/jornal/entrop Deriation of D Power-Law Velocit Distribtion Using Entrop Theor Vija P. Singh,, *, stao Marini 3 and Nicola

More information

Momentum Equation. Necessary because body is not made up of a fixed assembly of particles Its volume is the same however Imaginary

Momentum Equation. Necessary because body is not made up of a fixed assembly of particles Its volume is the same however Imaginary Momentm Eqation Interest in the momentm eqation: Qantification of proplsion rates esign strctres for power generation esign of pipeline systems to withstand forces at bends and other places where the flow

More information

4 Exact laminar boundary layer solutions

4 Exact laminar boundary layer solutions 4 Eact laminar bondary layer soltions 4.1 Bondary layer on a flat plate (Blasis 1908 In Sec. 3, we derived the bondary layer eqations for 2D incompressible flow of constant viscosity past a weakly crved

More information

Direct linearization method for nonlinear PDE s and the related kernel RBFs

Direct linearization method for nonlinear PDE s and the related kernel RBFs Direct linearization method for nonlinear PDE s and the related kernel BFs W. Chen Department of Informatics, Uniersity of Oslo, P.O.Box 1080, Blindern, 0316 Oslo, Norway Email: wenc@ifi.io.no Abstract

More information

Visualisations of Gussian and Mean Curvatures by Using Mathematica and webmathematica

Visualisations of Gussian and Mean Curvatures by Using Mathematica and webmathematica Visalisations of Gssian and Mean Cratres by Using Mathematica and webmathematica Vladimir Benić, B. sc., (benic@grad.hr), Sonja Gorjanc, Ph. D., (sgorjanc@grad.hr) Faclty of Ciil Engineering, Kačićea 6,

More information

BROWN UNIVERSITY PROBLEM SET 9 INSTRUCTOR: SAMUEL S. WATSON DUE: 17 NOVEMBER 2017

BROWN UNIVERSITY PROBLEM SET 9 INSTRUCTOR: SAMUEL S. WATSON DUE: 17 NOVEMBER 2017 BROWN UNIVERSITY PROBLEM SET 9 INSTRUCTOR: SAMUEL S. WATSON DUE: 7 NOVEMBER 7 Print out these pages, including the additional space at the end, and complete the problems by hand. Then use Gradescope to

More information

QUADRATIC FUNCTIONS. ( x 7)(5x 6) = 2. Exercises: 1 3x 5 Sum: 8. We ll expand it by using the distributive property; 9. Let s use the FOIL method;

QUADRATIC FUNCTIONS. ( x 7)(5x 6) = 2. Exercises: 1 3x 5 Sum: 8. We ll expand it by using the distributive property; 9. Let s use the FOIL method; QUADRATIC FUNCTIONS A. Eercises: 1.. 3. + = + = + + = +. ( 1)(3 5) (3 5) 1(3 5) 6 10 3 5 6 13 5 = = + = +. ( 7)(5 6) (5 6) 7(5 6) 5 6 35 4 5 41 4 3 5 6 10 1 3 5 Sum: 6 + 10+ 3 5 ( + 1)(3 5) = 6 + 13 5

More information

SECTION 6.7. The Dot Product. Preview Exercises. 754 Chapter 6 Additional Topics in Trigonometry. 7 w u 7 2 =?. 7 v 77w7

SECTION 6.7. The Dot Product. Preview Exercises. 754 Chapter 6 Additional Topics in Trigonometry. 7 w u 7 2 =?. 7 v 77w7 754 Chapter 6 Additional Topics in Trigonometry 115. Yo ant to fly yor small plane de north, bt there is a 75-kilometer ind bloing from est to east. a. Find the direction angle for here yo shold head the

More information

3 2D Elastostatic Problems in Cartesian Coordinates

3 2D Elastostatic Problems in Cartesian Coordinates D lastostatic Problems in Cartesian Coordinates Two dimensional elastostatic problems are discssed in this Chapter, that is, static problems of either plane stress or plane strain. Cartesian coordinates

More information

Primary dependent variable is fluid velocity vector V = V ( r ); where r is the position vector

Primary dependent variable is fluid velocity vector V = V ( r ); where r is the position vector Chapter 4: Flids Kinematics 4. Velocit and Description Methods Primar dependent ariable is flid elocit ector V V ( r ); where r is the position ector If V is known then pressre and forces can be determined

More information

Formal Methods for Deriving Element Equations

Formal Methods for Deriving Element Equations Formal Methods for Deriving Element Eqations And the importance of Shape Fnctions Formal Methods In previos lectres we obtained a bar element s stiffness eqations sing the Direct Method to obtain eact

More information

Conservation of Energy Thermodynamic Energy Equation

Conservation of Energy Thermodynamic Energy Equation Conseration of Energy Thermodynamic Energy Equation The reious two sections dealt with conseration of momentum (equations of motion) and the conseration of mass (continuity equation). This section addresses

More information

PHASE PLANE DIAGRAMS OF DIFFERENCE EQUATIONS. 1. Introduction

PHASE PLANE DIAGRAMS OF DIFFERENCE EQUATIONS. 1. Introduction PHASE PLANE DIAGRAMS OF DIFFERENCE EQUATIONS TANYA DEWLAND, JEROME WESTON, AND RACHEL WEYRENS Abstract. We will be determining qalitatie featres of a discrete dynamical system of homogeneos difference

More information

MA 1128: Lecture 08 03/02/2018. Linear Equations from Graphs And Linear Inequalities

MA 1128: Lecture 08 03/02/2018. Linear Equations from Graphs And Linear Inequalities MA 1128: Lecture 08 03/02/2018 Linear Equations from Graphs And Linear Inequalities Linear Equations from Graphs Given a line, we would like to be able to come up with an equation for it. I ll go over

More information

Principal Component Analysis (PCA) The Gaussian in D dimensions

Principal Component Analysis (PCA) The Gaussian in D dimensions Prinipal Component Analysis (PCA) im ars, Cognitie Siene epartment he Gassian in dimensions What does a set of eqiprobable points loo lie for a Gassian? In, it s an ellipse. In dimensions, it s an ellipsoid.

More information

Viscous Dissipation and Heat Absorption effect on Natural Convection Flow with Uniform Surface Temperature along a Vertical Wavy Surface

Viscous Dissipation and Heat Absorption effect on Natural Convection Flow with Uniform Surface Temperature along a Vertical Wavy Surface Aailable at htt://am.ed/aam Al. Al. Math. ISSN: 93-966 Alications and Alied Mathematics: An International Jornal (AAM) Secial Isse No. (Ma 6),. 8 8th International Mathematics Conference, March,, IUB Cams,

More information

Physics 2A Chapter 3 - Motion in Two Dimensions Fall 2017

Physics 2A Chapter 3 - Motion in Two Dimensions Fall 2017 These notes are seen pages. A quick summary: Projectile motion is simply horizontal motion at constant elocity with ertical motion at constant acceleration. An object moing in a circular path experiences

More information

Pulses on a Struck String

Pulses on a Struck String 8.03 at ESG Spplemental Notes Plses on a Strck String These notes investigate specific eamples of transverse motion on a stretched string in cases where the string is at some time ndisplaced, bt with a

More information

MAE 320 Thermodynamics HW 4 Assignment

MAE 320 Thermodynamics HW 4 Assignment MAE 0 Thermodynamics HW 4 Assignment The homework is de Friday, October 7 th, 06. Each problem is worth the points indicated. Copying of the soltion from any sorce is not acceptable. (). Mltiple choice

More information

Complexity of the Cover Polynomial

Complexity of the Cover Polynomial Complexity of the Coer Polynomial Marks Bläser and Holger Dell Comptational Complexity Grop Saarland Uniersity, Germany {mblaeser,hdell}@cs.ni-sb.de Abstract. The coer polynomial introdced by Chng and

More information

Math 21a Homework 07 Solutions Spring, 2014

Math 21a Homework 07 Solutions Spring, 2014 Math a Homework 7 Solutions Spring, 4. valuate the iterated integral. a) Stewart.7 # 6 ) e d d d We perform the iterated integral: e d d d e d d e d [ e [ ] 4 e + 4e. Note that we ve twice done an integral

More information

Relativity II. The laws of physics are identical in all inertial frames of reference. equivalently

Relativity II. The laws of physics are identical in all inertial frames of reference. equivalently Relatiity II I. Henri Poincare's Relatiity Principle In the late 1800's, Henri Poincare proposed that the principle of Galilean relatiity be expanded to inclde all physical phenomena and not jst mechanics.

More information

Digital Image Processing. Lecture 8 (Enhancement in the Frequency domain) Bu-Ali Sina University Computer Engineering Dep.

Digital Image Processing. Lecture 8 (Enhancement in the Frequency domain) Bu-Ali Sina University Computer Engineering Dep. Digital Image Processing Lectre 8 Enhancement in the Freqenc domain B-Ali Sina Uniersit Compter Engineering Dep. Fall 009 Image Enhancement In The Freqenc Domain Otline Jean Baptiste Joseph Forier The

More information

Steve Smith Tuition: Maths Notes

Steve Smith Tuition: Maths Notes Maths Notes : Discrete Random Variables Version. Steve Smith Tuition: Maths Notes e iπ + = 0 a + b = c z n+ = z n + c V E + F = Discrete Random Variables Contents Intro The Distribution of Probabilities

More information

The Basic Definition of Flux

The Basic Definition of Flux The Basic Definition of Flux Imagine holding a rectangular wire loop of area A in front of a fan. The volume of air flowing through the loop each second depends on the angle between the loop and the direction

More information

Intro to path analysis Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised April 6, 2015

Intro to path analysis Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised April 6, 2015 Intro to path analysis Richard Williams, Uniersity of Notre Dame, https://3.nd.ed/~rilliam/ Last reised April 6, 05 Sorces. This discssion dras heaily from Otis Ddley Dncan s Introdction to Strctral Eqation

More information

Feature extraction: Corners and blobs

Feature extraction: Corners and blobs Featre etraction: Corners and blobs Wh etract featres? Motiation: panorama stitching We hae two images how do we combine them? Wh etract featres? Motiation: panorama stitching We hae two images how do

More information

Math 144 Activity #10 Applications of Vectors

Math 144 Activity #10 Applications of Vectors 144 p 1 Math 144 Actiity #10 Applications of Vectors In the last actiity, yo were introdced to ectors. In this actiity yo will look at some of the applications of ectors. Let the position ector = a, b

More information

Physics 111. Help sessions meet Sunday, 6:30-7:30 pm in CLIR Wednesday, 8-9 pm in NSC 098/099

Physics 111. Help sessions meet Sunday, 6:30-7:30 pm in CLIR Wednesday, 8-9 pm in NSC 098/099 ics Announcements day, ember 7, 2007 Ch 2: graphing - elocity s time graphs - acceleration s time graphs motion diagrams - acceleration Free Fall Kinematic Equations Structured Approach to Problem Soling

More information

EXERCISES WAVE EQUATION. In Problems 1 and 2 solve the heat equation (1) subject to the given conditions. Assume a rod of length L.

EXERCISES WAVE EQUATION. In Problems 1 and 2 solve the heat equation (1) subject to the given conditions. Assume a rod of length L. .4 WAVE EQUATION 445 EXERCISES.3 In Problems and solve the heat eqation () sbject to the given conditions. Assme a rod of length.. (, t), (, t) (, ),, > >. (, t), (, t) (, ) ( ) 3. Find the temperatre

More information

Line Integrals and Path Independence

Line Integrals and Path Independence Line Integrals and Path Independence We get to talk about integrals that are the areas under a line in three (or more) dimensional space. These are called, strangely enough, line integrals. Figure 11.1

More information

Honors Advanced Mathematics Determinants page 1

Honors Advanced Mathematics Determinants page 1 Determinants page 1 Determinants For every square matrix A, there is a number called the determinant of the matrix, denoted as det(a) or A. Sometimes the bars are written just around the numbers of the

More information

Microscopic Properties of Gases

Microscopic Properties of Gases icroscopic Properties of Gases So far we he seen the gas laws. These came from observations. In this section we want to look at a theory that explains the gas laws: The kinetic theory of gases or The kinetic

More information

INTEGRATION: THE FUNDAMENTAL THEOREM OF CALCULUS MR. VELAZQUEZ AP CALCULUS

INTEGRATION: THE FUNDAMENTAL THEOREM OF CALCULUS MR. VELAZQUEZ AP CALCULUS INTEGRATION: THE FUNDAMENTAL THEOREM OF CALCULUS MR. VELAZQUEZ AP CALCULUS RECALL: ANTIDERIVATIVES When we last spoke of integration, we examined a physics problem where we saw that the area under the

More information

Math 4A03: Practice problems on Multivariable Calculus

Math 4A03: Practice problems on Multivariable Calculus Mat 4A0: Practice problems on Mltiariable Calcls Problem Consider te mapping f, ) : R R defined by fx, y) e y + x, e x y) x, y) R a) Is it possible to express x, y) as a differentiable fnction of, ) near

More information

Math 53 Homework 7 Solutions

Math 53 Homework 7 Solutions Math 5 Homework 7 Solutions Section 5.. To find the mass of the lamina, we integrate ρ(x, y over the box: m a b a a + x + y dy y + x y + y yb y b + bx + b bx + bx + b x ab + a b + ab a b + ab + ab. We

More information

ENGINEERING COUNCIL DYNAMICS OF MECHANICAL SYSTEMS D225 TUTORIAL 2 LINEAR IMPULSE AND MOMENTUM

ENGINEERING COUNCIL DYNAMICS OF MECHANICAL SYSTEMS D225 TUTORIAL 2 LINEAR IMPULSE AND MOMENTUM ENGINEERING COUNCIL DYNAMICS OF MECHANICAL SYSTEMS D5 TUTORIAL LINEAR IMPULSE AND MOMENTUM On copletion of this ttorial yo shold be able to do the following. State Newton s laws of otion. Define linear

More information

Are You Ready? Find Area in the Coordinate Plane

Are You Ready? Find Area in the Coordinate Plane SKILL 38 Are You Read? Find Area in the Coordinate Plane Teaching Skill 38 Objective Find the areas of figures in the coordinate plane. Review with students the definition of area. Ask: Is the definition

More information

Geometry of Span (continued) The Plane Spanned by u and v

Geometry of Span (continued) The Plane Spanned by u and v Geometric Description of Span Geometr of Span (contined) 2 Geometr of Span (contined) 2 Span {} Span {, } 2 Span {} 2 Geometr of Span (contined) 2 b + 2 The Plane Spanned b and If a plane is spanned b

More information

MITOCW watch?v=pqkyqu11eta

MITOCW watch?v=pqkyqu11eta MITOCW watch?v=pqkyqu11eta The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for free. To

More information

VECTORS. Given two vectors! and! we can express the law of vector addition geometrically. + = Fig. 1 Geometrical definition of vector addition

VECTORS. Given two vectors! and! we can express the law of vector addition geometrically. + = Fig. 1 Geometrical definition of vector addition VECTORS Vectors in 2- D and 3- D in Euclidean space or flatland are easy compared to vectors in non- Euclidean space. In Cartesian coordinates we write a component of a vector as where the index i stands

More information

The New (2+1)-Dimensional Integrable Coupling of the KdV Equation: Auto-Bäcklund Transformation and Non-Travelling Wave Profiles

The New (2+1)-Dimensional Integrable Coupling of the KdV Equation: Auto-Bäcklund Transformation and Non-Travelling Wave Profiles MM Research Preprints, 36 3 MMRC, AMSS, Academia Sinica No. 3, December The New (+)-Dimensional Integrable Copling of the KdV Eqation: Ato-Bäcklnd Transformation and Non-Traelling Wae Profiles Zhena Yan

More information

Instruction register. Data. Registers. Register # Memory data register

Instruction register. Data. Registers. Register # Memory data register Where we are headed Single Cycle Problems: what if we had a more complicated instrction like floating point? wastefl of area One Soltion: se a smaller cycle time have different instrctions take different

More information

Chapters 4/5 Class Notes. Intermediate Algebra, MAT1033C. SI Leader Joe Brownlee. Palm Beach State College

Chapters 4/5 Class Notes. Intermediate Algebra, MAT1033C. SI Leader Joe Brownlee. Palm Beach State College Chapters 4/5 Class Notes Intermediate Algebra, MAT1033C Palm Beach State College Class Notes 4.1 Professor Burkett 4.1 Systems of Linear Equations in Two Variables A system of equations is a set of two

More information

A Contraction of the Lucas Polygon

A Contraction of the Lucas Polygon Western Washington University Western CEDAR Mathematics College of Science and Engineering 4 A Contraction of the Lcas Polygon Branko Ćrgs Western Washington University, brankocrgs@wwed Follow this and

More information

D = 10 m. = 30 and vf 8 m/s. Note that the final angle is fixed and cannot be moved, but we are NOT told that the speed should be 8 m/s!

D = 10 m. = 30 and vf 8 m/s. Note that the final angle is fixed and cannot be moved, but we are NOT told that the speed should be 8 m/s! Mars Probe Your group has been selected to sere on a citizen's panel to ealuate a new proposal to search or lie on Mars. On this unmanned mission, the lander will leae orbit around Mars alling through

More information

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions Chem 4501 Introdction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics Fall Semester 2017 Homework Problem Set Nmber 10 Soltions 1. McQarrie and Simon, 10-4. Paraphrase: Apply Eler s theorem

More information

Review of Matrices and Vectors 1/45

Review of Matrices and Vectors 1/45 Reiew of Matrices and Vectors /45 /45 Definition of Vector: A collection of comple or real numbers, generally put in a column [ ] T "! Transpose + + + b a b a b b a a " " " b a b a Definition of Vector

More information

Comments on Vertical Vorticity Advection

Comments on Vertical Vorticity Advection Comments on Vertical Vorticity Advection It shold be fairly intitive that ositive maima in vertical vorticity are associated with cyclones, and ths ositive cyclonic vorticity advection might be a sefl

More information

Essentials of optimal control theory in ECON 4140

Essentials of optimal control theory in ECON 4140 Essentials of optimal control theory in ECON 4140 Things yo need to know (and a detail yo need not care abot). A few words abot dynamic optimization in general. Dynamic optimization can be thoght of as

More information

To factor an expression means to write it as a product of factors instead of a sum of terms. The expression 3x

To factor an expression means to write it as a product of factors instead of a sum of terms. The expression 3x Factoring trinomials In general, we are factoring ax + bx + c where a, b, and c are real numbers. To factor an expression means to write it as a product of factors instead of a sum of terms. The expression

More information

Complex Tire-Ground Interaction Simulation: Recent Developments Of An Advanced Shell Theory Based Tire Model

Complex Tire-Ground Interaction Simulation: Recent Developments Of An Advanced Shell Theory Based Tire Model . ozdog and W. W. Olson Complex Tire-Grond Interaction Simlation: ecent eelopments Of n danced Shell Theory ased Tire odel EFEECE: ozdog. and Olson W. W. Complex Tire-Grond Interaction Simlation: ecent

More information

LESSON 21: DIFFERENTIALS OF MULTIVARIABLE FUNCTIONS MATH FALL 2018

LESSON 21: DIFFERENTIALS OF MULTIVARIABLE FUNCTIONS MATH FALL 2018 LESSON 21: DIFFERENTIALS OF MULTIVARIABLE FUNCTIONS MATH 16020 FALL 2018 ELLEN WELD 1. Quick Review of Differentials Ex 1. Consider the function f(x) x. We know that f(9) 9 3, but what is f(9.1) 9.1? Obviously,

More information