Introduction to PDEs and Numerical Methods Lecture 1: Introduction

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Platzhalter für Bild, Bild auf Titelfolie hinter das Logo einsetzen Introduction to PDEs and Numerical Methods Lecture 1: Introduction Dr. Noemi Friedman, 28.10.2015.

Basic information on the course Course Title: Lecturer: Introduction to PDEs and Numerical Methods Noémi Friedman n.friedman@tu-bs.de Mühlenpfordtstr. 23, 8th floor Room: 819 Assistant (exercises): Jaroslav Vondřejc j.vondrejc@tu-bs.de Mühlenpfordtstr. 23, 8th floor Room: 822 Assistant2 (small tutorials): Stephan Lenz (CSE student) 28. 10. 2015. PDE lecture Seite 2

Basic information on the course Credits and work load: 5 credits: 6-7 hours/week Pre-requisits: Requisits: Differential operators, elementary knowledge of PDEs, basics of linear algebra, basic MATLAB coding skills Weekly assignments in group of two or three (min 50%) Written exam: 29.2.2016., 10:30-12:00, room ZI 24.1 Script, recommended literature: See webpage: https://www.tu-braunschweig.de/wire/lehre/ws15/pde1 Software used: MATLAB, FEniCS (Python interface) 28. 10. 2015. PDE lecture Seite 3

Information about the assignments Homework assignments in groups (max. group of three) Submission of homework Consultation: Written homework Submit on the beginning of the tutorial (include cover sheet with subject name (PDE1), names and matriculation number of students, assignment number) For program codes: e-mail: wire.pde@gmail.com subject: assignment# NAMES (#: number of the assignment, NAMES: names of students) (e.g.: assignment1 J. Smith, K. Park) Homework is due to the beginning of the tutorials Noemi Friedman (after the lecture, office hours by arrangement, please, take appointment first by e-mail: n.friedman@tu-bs.de) Jaroslav Vondřejc (will be assigned on the tutorial 28. 10. 2015. PDE lecture Seite 4

Definition: ODEs PDEs Partial differential equation: Equation specifying a relation between the partial derivative(s) of an unkown multivariable function and maybe the function itself: F u x, y, z, t, u x, y, z, t, u x, y, z, t y, 2 u x, y, z, t y, = f(x, y, z, t) Ordinary differential equation: Equation specifying a relation between the derivative(s) of an unkown univariable function and maybe the function itself: F u t, du t t, d 2 u t dt 2, = f(t) Boundary Value Problem (BVP), Initial Boundary Value Problem (IBVP): PDE with initial/boundary conditions 28. 10. 2015. PDE lecture Seite 5

Motivation simulation of planets 28. 10. 2015. PDE lecture Seite 6

Motivation heat convection computed surface temperatures due to convective and radiative heat transfer from the exhaust manifold to surrounding objects Source: ANSYS http://www.ansys.com/staticassets/ansys/staticassets/product/16-highlights/underhood-simulation-surface-temps-heattransfer-manifold-2.jpg 28. 10. 2015. PDE lecture Seite 7

Motivation structural analysis 28. 10. 2015. PDE lecture Seite 8 Source: ANSYS http://wildeanalysis.co.uk/system/photos/838/preview/ansys_ex plicit_str.png?1273430962

Motivation flow problems The Stokes equation u(x) u + p I = f in Ω u = 0 in Ω p(x) Source: FENICS documentation: http://fenicsproject.org/documentation/dolfin/1.6.0/python/demo/documented/stokes-taylor-hood/python/documentation.html 28. 10. 2015. PDE lecture Seite 9

Motivation flow problems Source: TU Braunschweig SFB 880 Source: https://33463d8ba37cd0a930f1- eb07ed6f28ab61e35047cec42359baf1.ssl.cf5.rackcdn.com/ugc/entry/5 44867a78ef07-133981577813387476428_0129_fast15.jpg 28. 10. 2015. PDE lecture Seite 10

Motivation highly coupled systems 28. 10. 2015. PDE lecture Seite 11

Overview of the course Introduction (definition of PDEs, classification, basic math, introductory examples of PDEs) Analitical solution of elementary PDEs (Fourier series/transform, seperation of variables, Green s function) Numerical solutions of PDEs: Finite difference method Finite element method 28. 10. 2015. PDE lecture Seite 12

Overview of this lecture Basic definitions, motivation Differential operators: basic notations, divergence, Laplace, curl, grad Classification of PDEs Introductory example: heat flow in a bar 28. 10. 2015. PDE lecture Seite 13

Differential operators partial derivative φ(x, y, z, t) Example: Partial derivative: z = f(x, y) = x 2 + xy + y 2 φ, xφ, φ x, φ, φ,x, (φ ) φ = 2x + y φ t = φ φ x=1,y=1 = 3 (Image source: Wikipedia) 28. 10. 2015. PDE lecture Seite 14

Example: Differential operators mixed derivative φ(x, y) Mixed derivative: f(x, y, z) = xy 2 cos(z) 2 φ y = 2 φ y f = y2 cos(z) 2 φ y = 2ycos(z) f y = 2xy cos(z) 2 φ y = 2ycos(z) 28. 10. 2015. PDE lecture Seite 15

Differential operators total derivative φ r = φ x, y, z, t Total derivative: dφ dt = φ dt t dt + φ dx dt + φ dy y dt + φ dz z dt Total differential (differential change of f): dφ = dφ dt + φ φ φ dx + dy + y z dz Example: φ x, y = x 2 + 2y y x = x φ = 2x dφ dx = φ dx dx + φ dy y dx = 2x + 2 partial derivative total derivative 28. 10. 2015. PDE lecture Seite 16

Differential operators gradient φ r = φ x, y, z : R 3 R (vector-scalar function) Nabla operator: Gradient: = y z direction: greatest rate of increase of the function magnitude: the slope of the function in that direction Example: 28. 10. 2015. PDE lecture Seite 17

Differential operators directional derivative φ r = φ x, y, z : R 3 R (vector-scalar function) Directional derivative: D v f r = lim h 0 φ r + hv φ r h (normalised): = v f r = v T f r = v x v y v z D v f r = lim h 0 f r + hv f r h v = v v f r φ x, y, z φ x, y, z y φ x, y, z z Example 1: x u t What is the differential equation to define a wave traveling with speed c? In the direction x ct u is constant directional derivative is zero: D v u x, t = v v u x, t = 0 (v u x, t = 0) 28. 10. 2015. PDE lecture Seite 18

Differential operators directional derivative x u v = c t 1 v u x, t = 0 v u x, t = v T u x, t = c 1 u u t = 0 Transport equation: u t + cu x = 0 Example 2: Let s suppose u = sin(x ct) is a solution of the transport equation. What is its directional derivative in the direction: v = c 1 v u x, t = v T cos(x ct) u x, t = c 1 c cos(x ct = 0 28. 10. 2015. PDE lecture Seite 19

Differential operators - divergence Divergence: of g(x, y, z): R 3 R 3 ( (of a vector field): g x, y, z = g x (x, y, z) g y (x, y, z) g z (x, y, z) = g x g y g z divg x, y, z = g x, y, z = y z g x g y g z = g x + g y y + g z z Example: 28. 10. 2015. PDE lecture Seite 20

Differential operators - Laplace Laplace operator: Example: 28. 10. 2015. PDE lecture Seite 21

Differential operators rotation (curl) Rotation (curl): of g(x, y, z): R 3 R 3 ( (of a vector field): g x, y, z = rotg x, y, z = g x, y, z = det direction: axis of rotation magnitude: magnitude of rotation g x (x, y, z) g y (x, y, z) g z (x, y, z) = g x g y g z i j k = y z g x g y g z g z y g y z g x z g z g y g x y Example: 28. 10. 2015. PDE lecture Seite 22

Classification of PDEs Constant/variable coefficients Stationary/instationary (not time dependent/time dependent) Linear/nonlinear linearity condition: order order of the highest derivative homogeneous/inhomogenous inhomogeneous: additive terms which do not depend on unknown function homogenous: u = 0 is a solution of the equation elliptic/parabolic/hyperbolic (only for second order PDEs) Au xx + 2Bu xy + Cu yy + lower order derivatives = 0 AC B 2 = 0 parabolic AC B 2 < 0 hyperbolic AC B 2 > 0 elliptic 28. 10. 2015. PDE lecture Seite 23

Classification of PDEs, examples of PDEs Wave equation u tt c 2 u xx = 0 Laplace equation u xx + u yy = 0 Heat equation u t u xx = 0 Order 2 2 2 Constant coefficient? yes yes yes Linear? yes yes yes Homogenous? yes yes yes Class A=1, B=0, C= c 2 AC B 2 = c 2 Hyperbolic A=1, B=0, C=1 AC B 2 =1 Elliptic A=-1, B=0, C=0 AC B 2 = 0 Parabolic 28. 10. 2015. PDE lecture Seite 24

Classification of PDEs, examples of PDEs Linearity: 28. 10. 2015. PDE lecture Seite 25

Classification of PDEs, examples of PDEs 28. 10. 2015. PDE lecture Seite 26

Introductory example: heat flow in a bar Basic assumptions: Uniform cross-section Temperature varies only in the longitudinal direction Relationship between heat energy and temperature is linear c J gk : cpecific heat capacity Energy [J] cj energy is required to raise the tempreture by 1K of 1g material Homogenous material properties along the bar (ρ and c are constants along the bar) ρ[ g m3]: density of the material of the bar Problem description u x, t =? (temparature) q(0, t) x A q(l, t) 0 x x + x l 28. 10. 2015. PDE lecture Seite 27

Introductory example: heat flow in a bar Total energy in the bar section of length x is: E tot = E 0 + E 0 + x+ x x x x+ x Aρcu s, t ds Aρc(u s, t T 0 ))ds = x+ x x AρcT 0 ds x AρcT 0 ds But I m only interested in: x+ x Aρcu s, t ds = t x x x+ x Aρc u s, t t ds A q(0, t) q(l, t) x 0 x x + x l 28. 10. 2015. PDE lecture Seite 28

Introductory example: heat flow in a bar Change of heat energy by time in the section of length x t x x+ x Aρcu s, t ds = x x+ x Aρc u s, t t ds q(x, t) x q(x + x, t) Change of energy by time in the section of length x from heat flux: q x, t J m 2 s : heat flux Fundamental theorem of calculus: Aq x + x, t Aq x, t = Conservation of energy: x x+ x A q s, t ds x x+ x A q s, t ds = x x+ x Aρc u s, t t ds x x+ x A q s, t + Aρc u s, t t ds = 0 28. 10. 2015. PDE lecture Seite 29

Introductory example: heat flow in a bar x x+ x A q s, t + Aρc u s, t t ds = 0 q(x, t) x q(x + x, t) q x, t + ρc u x, t t = 0 0 < x < l u x,t : change of temperature with increasing x Assumption: Fourier s law of heat conduction: q x, t = κ u x, t Heat equation ρc u x, t t κ 2 u x, t 2 = 0 (for homogenous material properties) ρ(x)c(x) u x, t t κ(x) u x, t = 0 (for inhomogenous material properties) 28. 10. 2015. PDE lecture Seite 30

Introductory example: heat flow in a bar The heat equation with source or sink (inhomogenous heat equation) x x+ x A q s, t + Aρc u s, t t ds = x x+ x Af(s, t) ds q(x, t) x q(x + x, t) q x, t Heat equation + ρc u x, t t = f(x, t) 0 < x < l ρc u x, t t κ 2 u x, t 2 = f(x, t) (for homogenous material properties) u x, t ρ(x)c(x) t κ(x) u x, t = f(x, t) (for inhomogenous material properties) 28. 10. 2015. PDE lecture Seite 31

Introductory example: heat flow in a bar q(0, t) A q(l, t) 0 l ρc u x, t t κ 2 u x, t 2 = f(x, t) Boundary conditions: a) Perfect isolation at the end (flux across the boundaries is zero): u 0, t u l, t κ = 0 κ = 0 t b) Perfect thermal contact: u 0, t = 0 u l, t = 0 t 28. 10. 2015. PDE lecture Seite 32