The following report makes use of the process from Chapter 2 in Dr. Cumming s thesis.

Similar documents
Chapter 2. First Order Scalar Equations

EXERCISES FOR SECTION 1.5

Predator - Prey Model Trajectories and the nonlinear conservation law

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

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

Two Coupled Oscillators / Normal Modes

Final Spring 2007

Differential Equations

CHAPTER 12 DIRECT CURRENT CIRCUITS

Chapter 3 Boundary Value Problem

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

8. Basic RL and RC Circuits

2. Nonlinear Conservation Law Equations

Math 334 Fall 2011 Homework 11 Solutions

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

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

ME 452 Fourier Series and Fourier Transform

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

Echocardiography Project and Finite Fourier Series

Some Basic Information about M-S-D Systems

Properties Of Solutions To A Generalized Liénard Equation With Forcing Term

Solutions to Assignment 1

10. State Space Methods

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

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Phys1112: DC and RC circuits

20. Applications of the Genetic-Drift Model

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

6.2 Transforms of Derivatives and Integrals.

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...

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

THE 2-BODY PROBLEM. FIGURE 1. A pair of ellipses sharing a common focus. (c,b) c+a ROBERT J. VANDERBEI

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

Solutionbank Edexcel AS and A Level Modular Mathematics

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

5.2. The Natural Logarithm. Solution

CHAPTER 2 Signals And Spectra

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

= ( ) ) or a system of differential equations with continuous parametrization (T = R

The motions of the celt on a horizontal plane with viscous friction

Unsteady Mass- Transfer Models

Chapter Three Systems of Linear Differential Equations

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures.

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

Math 333 Problem Set #2 Solution 14 February 2003

Linear Response Theory: The connection between QFT and experiments

The Brock-Mirman Stochastic Growth Model

Class Meeting # 10: Introduction to the Wave Equation

Oscillation of an Euler Cauchy Dynamic Equation S. Huff, G. Olumolode, N. Pennington, and A. Peterson

Chapter 6. Systems of First Order Linear Differential Equations

Math 115 Final Exam December 14, 2017

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

LAPLACE TRANSFORM AND TRANSFER FUNCTION

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

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

Chapter 7: Solving Trig Equations

INDEX. Transient analysis 1 Initial Conditions 1

ME 391 Mechanical Engineering Analysis

Circuit Variables. AP 1.1 Use a product of ratios to convert two-thirds the speed of light from meters per second to miles per second: 1 ft 12 in

Undetermined coefficients for local fractional differential equations

THE WAVE EQUATION. part hand-in for week 9 b. Any dilation v(x, t) = u(λx, λt) of u(x, t) is also a solution (where λ is constant).

6.003 Homework #8 Solutions

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

Math 10B: Mock Mid II. April 13, 2016

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

Y 0.4Y 0.45Y Y to a proper ARMA specification.

R =, C = 1, and f ( t ) = 1 for 1 second from t = 0 to t = 1. The initial charge on the capacitor is q (0) = 0. We have already solved this problem.

KINEMATICS IN ONE DIMENSION

Math Final Exam Solutions

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

Ordinary dierential equations

Note: For all questions, answer (E) NOTA means none of the above answers is correct.

Applications of the Basic Equations Chapter 3. Paul A. Ullrich

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

Matlab and Python programming: how to get started

ln 2 1 ln y x c y C x

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1

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

CERTAIN CLASSES OF SOLUTIONS OF LAGERSTROM EQUATIONS

5.1 - Logarithms and Their Properties

Position, Velocity, and Acceleration

Math 2214 Solution Test 1A Spring 2016

Physics 1402: Lecture 22 Today s Agenda

IMPACT OF AN OBLIQUE BREAKING WAVE ON A WALL

Linear Surface Gravity Waves 3., Dispersion, Group Velocity, and Energy Propagation

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.

Solution of Integro-Differential Equations by Using ELzaki Transform

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

Basic Circuit Elements Professor J R Lucas November 2001

A Necessary and Sufficient Condition for the Solutions of a Functional Differential Equation to Be Oscillatory or Tend to Zero

EE100 Lab 3 Experiment Guide: RC Circuits

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

arxiv: v1 [math.ca] 15 Nov 2016

Transcription:

Zaleski 1 Joseph Zaleski Mah 451H Final Repor Conformal Mapping Mehods and ZST Hele Shaw Flow Inroducion The Hele Shaw problem has been sudied using linear sabiliy analysis and numerical mehods, bu a novel advanage of conformal mapping mehods is ha exac soluions are obainable. However much of he heory which deals wih conformal mapping is concerned wih he zero surface ension problem; as summarized in he end he non-zst problem is much more inracable. My main goal his semeser was o obain an undersanding of why he ZST soluions are no necessarily relevan, and surface ension plays a role in he problem. The following repor makes use of he process from Chaper in Dr. Cumming s hesis. Basic Equaions Using he process oulined in chaper one of Cummings (1996) we have he basic equaions for one phase and Hele-Shaw flow: p 0 in ( ) (1), where p is pressure, and is he varying fluid domain. Surface Tension BC: p Ton ( ) (), where T is surface ension and is curvaure Kinemaic BC: vn on ( ) (3) n However, under he assumpion ha curvaure is small (ha is, he fluid domain () is smooh and nowhere of order 1/T), and surface ension is negligible, we migh conjecure ha seing he righ side of eq. () equal o zero is a valid approximaion o he problem. Thus we have he zero surface ension boundary condiion: p 0 on ( ) (4) Polubarinova/Galin Mehod Nex, I ouline wha I will call he P-G approach. The crucial facor which allows his mehod o be used is ha equaion (1) says pressure p is harmonic on he fluid domain. Complex variables heory herefore implies ha p is he real or imaginary par of some complex funcion which is analyic. The key idea o his mehod is mapping a known region (in his repor, we use he uni disc as his region, bu for channel flows, he righ half plane may be more convenien) ino he evolving fluid domain via a ime dependan conformal map. We are a he libery o choose he region and mapping, bu for simpliciy, mapping he origin o he pressure source is convenien. If he fluid domain is simply conneced, he exisence of he map is known, by he Riemann mapping heorem (for his reason we also enforce ha he map be univalen, which prevens he border of he fluid domain from crossing iself). Furhermore, assuming ha he derivaive is real and posiive gives us a unique map. I define his map as w z(, ), where i are poins in he uni disc.

Zaleski 1 fig.1, Cummings (1996) Nex, on he fluid domain in he z=x+iy plane we will define he complex poenial of he flow o be: ( z, ) f ( z, ) i g( z, ), s.. analyic wihin Ω() (excep a sink/driving poins) and p { ( z, )} (5) Nex, we describe he asympoic behavior of he problem near singulariies in he fluid domain by making assumpions abou he behavior a he source or sink of he pressure field (or where fluid is injeced or sucked from, in he problem). Common assumpions for he sucion or blowing problem 1/ include: p ~ log ( x y ), as ( x, y) (0, 0), where 0 sands for source/sink srengh Clearly pressure blows up as we near origin, maching he physical naure of he problem. From his assumpion and using he definiion of he complex poenial, we can now obain he following relaion: { ( z)} p ~ log r. To saisfy his and have he correc singulariy, we can ake: ( z) ~ log z ( 5), since log z log r i. Wha we nex consider below, is complex poenial in he plane, and we define his funcion assuming ha he behavior near origin in he plane is idenical o ha in he z plane:

Zaleski 3 (, ) ( z(, )) log (6) Noe ha he ZST condiion says ha { ( z(, ))} 0 for z on, which corresponds o (, ) vanishing on he uni disc, 1. (hus he ZST condiion is saisfied in boh planes) Moving on, we wrie he KBC (3) as: KBC: n v, n where n / and vn / n n vn ( / ) ( / ) p p on ( ) (i) To reduce he above expression, on boundary =1, we have: '( ) px py '( z) w( ) w( ) 4 w( ) (ii) and p { ( ) } { } (iii) To calculae : w z w(, ) 0 w w (iv) w Now noe ha ( i) ( iii) ( ii) : 4 w( ) w( ) { } { } w and herefore ( iv) { } w w( ) Polubarinova-Galin eq: { w'( ) w ( )} on 1, ( 7) To summarize, we now have a relaion which mappings mus saisfy o be soluions o he ZST problem.

Zaleski 4 Examples The P-G equaion involves guessing he general form of a map, bu a variey of mappings exis. Ex 1: Take our iniial guess for he mapping o be he quadraic map, where a1, aare real valued funcions. z w a (, ) a1( ) ( ), i Subsiuing ino (7), and aking ino accoun ha he P-G eq. applies on 1, or in polar form e, we ge: i w'( ) a ( ) a ( ) a ( ) a ( ) e, 1 1 w ( ) a e a e w ( ) a e a e i i i i 1 1 P-G: { w'( ) w ( )}, i i i i i i i i { e ( a1( ) a( ) e )( a1 e ae )} { e ( a1a1 e a1a e aa1 aae )} i i { a1a1 a1a e aa1 e aa} { a1a1 aa a1a cos( ) aa1 cos i(...)} a1a1 aa ( a1a aa1 )cos And lasly we ge he following sysem of ODEs, by noing ha he erms mus vanish o mach he righ sid e: a1a1 aa a a a a 0 1 1 Using Malab and random iniial condiions, I solved his sysem (which can be manually inegraed):

Zaleski 5 1.5 uadraic map: soluions break down a a cusp 1 0.5 0-0.5-1 -1.5-1 -0.5 0 0.5 1 1.5 The previous plo shows behavior which makes he ZST problem no useful he soluions break down a he cusp poin (where he curvaure blows up, and he mapping is no longer univalen). I is also worh nohing ha various oher maps work, making an arbirary amoun of soluions possible, and also making he problem no really seem applicable o he real life case (see figure below, which displays a cusp problem on he lef from a polynomial map, and a logarihm map ha is a sli/finger model). The real life case also involves surface ension and unis, so of course i makes sense ha he ZST model may no accuraely predic resuls. The ZST problem is also ill posed, because as saed in one hesis I read, soluions wih close iniial condiions can eiher break down in finie or infinie ime. (Dallason, 013) Dallason, (013)

Zaleski 6 Conclusion To conclude, surface ension regularizes he Hele-Shaw problem, and makes i relevan using he mehod we oulined, i is possible o obain all sors of ineresing geomeric soluions, bu in realiy hese may no be useful. Surface ension also prevens cusps from forming in experimens. Oher complex variables mehods for analyzing he Hele Shaw problem (boh he ZST and NZST cases), such as he Schwarz funcion exis, bu I have no included hem, as hey are much more involved. However, hey confirm ha he NZST problem is generally much less easy o solve han he ZST problem. Furher research on he NZST problem is useful, because surface ension is wha keeps he problem from being undeermined. References Linda Cummings, Phd hesis, Oxford, 1996 Michael Dallason, Phd hesis, ueensland U. of Technology, 013 Code funcion Capsone1 clc clear all inegraionspan=[0,0.6] ICs=[1,0.1] [,P]=ode15s(@SysemofEqs,inegraionSpan,ICs); a1=p(:,1); a=p(:,); s=size(a) i=0:*pi/(s(1)-1):(*pi); q=size(i) circle=ranspose(i); x1=cos(circle); y1=sin(circle); for k=1:1:38 plo(a1(k).*x1+a(k).*(x1.^-y1.^),*a(k).*x1.*y1+a1(k).*y1,'r') hold on end ile 'uadraic map: soluions break down a a cusp' funcion aprime=sysemofeqs(,a) =5; a1=a(1);a=a(); aprime=[(-1*a1*/(*pi))/(a1^-4*(a^)); -*a*(-1*/(*pi))/(a1^-4*(a^))];

Zaleski 7