Handout 8 MATLAB Code for the Projection Method and BC Details for the Lid-Driven Cavity Problem

Size: px
Start display at page:

Download "Handout 8 MATLAB Code for the Projection Method and BC Details for the Lid-Driven Cavity Problem"

Transcription

1 Handout 8 MATLAB Code for the Projection Method and BC Details for the Lid-Driven Cavity Problem Let s simplify the equations of the last page of Handout 7 for the case h = Δx = Δy because the code given in the next page is written for this case. Also drop the body force term for simplicity. u i,j v i,j Simplified equations used in the code for h = Δx = Δy and no body force = u n i,j + Δt [ 1 h (u e u u u e u u w u u w + u u n v u n u u s v u s ) + μ n ρh 2 (u i+1,j + u i 1,j + u i,j+1 + u i,j 1 4u i,j )] = v n i,j + Δt [ 1 h (u e v v v e u v w v v w + v v n v v n v v s v v s ) + μ n ρh 2 (v i+1,j + v i 1,j + v i,j+1 + v i,j 1 4v i,j )] p i+1,j + p i 1,j + p i,j+1 + p i,j 1 4p i,j = ρh Δt (u i,j u i 1,j + v i,j u n+1 i,j = u i,j Δt (p i+1,j p i,j ) ρ h (20a) (20b) v i,j 1 ) (18) (21a) v n+1 i,j = v i,j Δt (p i,j+1 p i,j ) ρ h (21b) Boundary Conditions with Ghost Cells for the Lid-Driven Carvity Problem The code given at the of this handout is written specifically for the lid-driven cavity problem. Let s study the BCs of this problem first. y u T = U lid v T = 0 u L = 0 v L = 0 L u B = 0 v B = 0 u R = 0 v R = 0 x 1

2 Consider the following mesh of (Nx = 3) x (Ny = 3) p cells. Thick lines are the domain boundaries. All around the domain we placed ghost cells. For structured grids ghost cells provide an easy way to implement the BCs. There are (Nx+2) x (Ny+2) = 25 pressure nodes. There are (Nx+1) x (Ny+2) = 20 u-velocity nodes. There are (Nx+2) x (Ny+1) = 20 v-velocity nodes. 2

3 BCs for u: We need to calculate only 6 u values, the ones for the inner u-cells, i.e. u(2:nx, 2:Ny+1). u on the left and right boundaries are given as u L = 0 and u R = 0. Do not solve for them. To calculate ghost node values we use linear interpolation. For example for u 1,1 Or for u 3,5 u 1,1 + u 1,2 2 u 3,5 + u 3,4 2 = u B u 1,1 = 2u B u 1,2, where u B is the u at the bottom boundary = u T u 3,5 = 2u T u 3,4, where u T is the u at the top boundary After the (or beginning) of each time step ghost node values are updated using equations similar to these. 3

4 BCs for v: We need to calculate only 6 v values, the ones for the inner v-cells, i.e. v(2:nx+1, 1:Ny). v on the bottom and top boundaries are given as v B = 0 and v T = 0. Do not solve for them. To calculate ghost node values we use linear interpolation. For example for v 1,2 Or for v 5,3 v 1,2 + v 2,2 2 v 5,3 + v 4,3 2 = v L v 1,2 = 2v L v 2,2, where v L is the v at the left boundary = v R v 5,3 = 2v R v 4,3, where v R is the v at the right boundary After the (or beginning) of each time step ghost node values are updated using equations similar to these. 4

5 BCs for the PPE: We need to calculate 9 p values, i.e. p(2:nx+1, 2:Ny+1) For the p-cells at the boundaries we need to derive a special Eqn. (18). Consider cell p 2,2. Eqn. (16) for it is Eqn (15) for this p-cell becomes h ( u n+1 2,2 u 1,2 n+1 u L + v 2,2 n+1 n+1 v 2,1 ) = 0 (16 ) v B u n+1 2,2 = u i,j Δt (p 3,2 p 2,2 ) ρ h p 3,2 p 2,2 = ρh Δt (u 2,2 u n+1 2,2 ) (17a ) This is not necesary (17b ) 5

6 v n+1 2,2 = v 2,2 Δt (p 2,3 p 2,2 ) ρ h METU, Dept. of Mechanical Eng. p 2,3 p 2,2 = ρh Δt (v 2,2 v n+1 2,2 ) (17c ) This is not necesary (17d ) Add Eqn (17a*) and Eqn (17c*) p 3,2 + p 2,3 2p 2,2 = ρh Δt ( u 2,2 + v 2,2 Compared to the original Eqn (18) the changes are u 2,2 n+1 v 2,2 n+1 = u L v B according to Eqn (16 )) (18 ) Number of unknowns decreased from 5 to 3 on the left hand side. If we solve the system using Gauss- Seidel, this can be taken care automatically by setting ghost cell pressure values to zero and always keep them like that. That way the only difference of the left hand compared to the original Eqn (18) becomes the change of the coefficient of the center unknown, i.e. p 2,2 from -4 to 22. On the right hand side there seem to be a change, but actually not. Because in the code u L and v B will be seen as u 1,2 and u 2,1, making the right hand side of Eqn (18*) the same as the original Eqn (18), so no change is required. If we repeat this for a non-corner boundary cell, such as p 4,3, we ll see that the only difference compared to Eqn (18) will be the change of the coefficient of the center unknown from -4 to -3. To summarize, boundaries will affect Eqn (18) as follows Set the center coefficient of the corner cells to -3. Set the center coefficient of the non-corner cells to -2. In the meantime keep the ghost cell pressures at zero. 6

7 % 2D flow solver using the projection method. % It is design ed to solve the lid driven cavity problem. % Uses forward time and central space differencing. % Uses staggered mesh % Uses ghost cells for boundary conditions clc; clear all; close all; % Clear the command window % Clear previously defined variables % Close previously opened figure windows refsoln = load ('Ghia_Re1000_Uvel'); % u velocity variation along the vertical centerline % from Ghia's reference solution. The data is available % at 4 different Reynolds numbers (100, 1000, 3200 and % 5000). refsoln has 2 columns, y and u. L = 1; % Cavity size. Preferred value is 1. Nx = 40; % Number of pressure cells in x and y directions Ny = 40; % (not including ghost cells). % Provide an even value to avoid a possible error in % the post-processing part. rho = 1.0; % Density [kg/m^3] visc = 1/1000; % Dynamic viscosity [Pa s] dt = 0.02; % Time step nstep = 10000; % Maximum number of time levels maxgsiter = 1; % Maximum iteration value for the Gauss-Seidel solver u_top = 1.0; % Tangential velocities at the boundaries [m/s] u_bottom = 0.0; v_left = 0.0; v_right = 0.0; Be careful!!! h = L/Nx; % h is the cell size (=dx=dy). % Allocate memory. Note that staggered grid with ghost cells is being used. u = zeros(nx+1,ny+2); % x velocity values v = zeros(nx+2,ny+1); % y velocity values p = zeros(nx+2,ny+2); % Pressure values ustar = zeros(nx+1,ny+2); vstar = zeros(nx+2,ny+1); % Temporary x velocities % Temporary y velocities The mesh is staggered. %% % Initialize the solution %% u(:,:) = 0.0; v(:,:) = 0.0; p(:,:) = 0.0; uold = u; vold = v; % uold and vold are used to check steady state convergence 7

8 %% % Set the coefficient of the center unknown of the PPE %% METU, Dept. of Mechanical Eng. coefppe = zeros(nx+1,ny+1); for i = 2:Nx+1 for j = 2:Ny+1 if (i == 2 && j == 2) (i == Nx+1 && j == 2)... (i == 2 && j == Ny+1) (i == Nx+1 && j == Ny+1) coefppe(i,j) = -2; elseif (i == 2) (i == Nx+1) (j == 2) (j == Ny+1) coefppe(i,j) = -3; else coefppe(i,j) = -4; Set the coefficient of the center unknown of the PPE = -4 for non-boundary cells = -2 for corner cells = -3 for non-corner % Print the header for the data that'll be written on the screen fprintf(' n u at (0.5,0.5) v at (0.5,0.5)\n'); fprintf('=========================================\n'); for n = 1:nStep % Time loop % Calculate ghost cell velocities using linear interpolation for i = 1:Nx+1 u(i,1) = 2*u_BOTTOM - u(i,2); % Bottom boundary u(i,ny+2) = 2*u_TOP - u(i,ny+1); % Top boundary Calculate ghost cell velocities. for j = 1:Ny+1 v(1,j) = 2*v_LEFT - v(2,j); % Left boundary v(nx+2,j) = 2*v_RIGHT - v(nx+1,j); % Right boundary % STEP 1a. Calculate the temporary u velocities. Eqn (20a) of Handout 8 for i = 2:Nx for j = 2:Ny+1 ue = 0.5 * (u(i,j) + u(i+1,j)); uw = 0.5 * (u(i,j) + u(i-1,j)); un = 0.5 * (u(i,j) + u(i,j+1)); us = 0.5 * (u(i,j) + u(i,j-1)); Use central differencing to get face velocities vn = 0.5 * (v(i,j) + v(i+1,j)); vs = 0.5 * (v(i,j-1) + v(i+1,j-1)); ustar(i,j) = u(i,j) - dt / h * (ue*ue + un*vn - uw*uw - us*vs)... + dt * visc / rho / (h^2) * (u(i+1,j) + u(i,j+1)... + u(i-1,j) + u(i,j-1) - 4 * u(i,j)); Eqn (20a) of Handout 8 8

9 % STEP 1b. Calculate the temporary v velocities. Eqn (20b) of Handout 8 METU, Dept. of Mechanical Eng. for i = 2:Nx+1 for j = 2:Ny ve = 0.5 * (v(i,j) + v(i+1,j)); vw = 0.5 * (v(i,j) + v(i-1,j)); vn = 0.5 * (v(i,j) + v(i,j+1)); vs = 0.5 * (v(i,j) + v(i,j-1)); Use central differencing to get face velocities ue = 0.5 * (u(i,j) + u(i,j+1)); uw = 0.5 * (u(i-1,j) + u(i-1,j+1)); vstar(i,j) = v(i,j) - dt / h * (ve*ue + vn*vn - vw*uw - vs*vs)... + dt * visc / rho / (h^2) * (v(i+1,j) + v(i,j+1)... + v(i-1,j) + v(i,j-1) - 4 * v(i,j)); Eqn (20b) of Handout 8 % STEP 2. Solve the pressure Poisson equation (PPE) using Gauss-Seidel % Eqn (18) of Handout 8. % Calculate the RHS of the PPE system. for i = 2:Nx+1 for j = 2:Ny+1 rhsppe(i,j) = (rho*h/dt) * (ustar(i,j) - ustar(i-1,j) + vstar(i,j) - vstar(i,j-1)); % Gauss-Seidel loop for iter = 1:maxGSiter pold = p; for i = 2:Nx+1 for j = 2:Ny+1 p(i,j) = (rhsppe(i,j) - p(i+1,j) - p(i-1,j) - p(i,j+1) - p(i,j-1)) / coefppe(i,j); % Here we typically check the convergence of Gauss-Seidel. But for this steady % problem it is not very critical to solve the PPE accurately so we skipped % this check. Solve the PPE, i.e. Eqn (18) of Handout 8 using Gauss-Seidel. % STEP 3. Correct the temporary velocities. Eqn (21a-b) of Handout 8 % Correct u velocities for i = 2:Nx for j = 2:Ny+1 u(i,j) = ustar(i,j) - dt / (rho * h) * (p(i+1,j) - p(i,j)); Eqn (21a) of Handout 8 9

10 % Correct v velocities for i = 2:Nx+1 for j = 2:Ny v(i,j) = vstar(i,j) - dt / (rho * h) * (p(i,j+1) - p(i,j)); Eqn (21b) of Handout 8 % Write some results on the screen % Calculate u and v at (0.5,0.5) ucenter = u(nx/2+1, Ny/2+1); vcenter = u(nx/2+1, Ny/2+1); fprintf('%5d %8.3e %8.3e\n', n, ucenter, vcenter); uold = u; vold = v; % Plot the u velocity variation along the vertical centerline of the % cavity Postprocessing if mod(n,10) == 0 ycenter = h/2:h:1-h/2; ucenter = u(nx/2+1:nx/2+1, 2:Ny+1); plot(refsoln(:,2), refsoln(:,1), ucenter, ycenter, 'ko', 'MarkerFaceColor', 'k') axis([ ]); grid on xlabel('u [m/s]'); ylabel('y [m]'); title('u velocity component along the vertical centerline'); leg('current', 'Ghia', 'Location', 'NorthWest') drawnow; % End of time loop 10

Two-Dimensional Unsteady Flow in a Lid Driven Cavity with Constant Density and Viscosity ME 412 Project 5

Two-Dimensional Unsteady Flow in a Lid Driven Cavity with Constant Density and Viscosity ME 412 Project 5 Two-Dimensional Unsteady Flow in a Lid Driven Cavity with Constant Density and Viscosity ME 412 Project 5 Jingwei Zhu May 14, 2014 Instructor: Surya Pratap Vanka 1 Project Description The objective of

More information

LAB 1: MATLAB - Introduction to Programming. Objective:

LAB 1: MATLAB - Introduction to Programming. Objective: LAB 1: MATLAB - Introduction to Programming Objective: The objective of this laboratory is to review how to use MATLAB as a programming tool and to review a classic analytical solution to a steady-state

More information

ME469. Computational Methods in Fluid Mechanics. Handout #11 GI - W2015

ME469. Computational Methods in Fluid Mechanics. Handout #11 GI - W2015 ME469 Computational Methods in Fluid Mechanics Handout #11 GI - W2015 Thermally Driven Cavity The Problem δt/δn=0# g# T h# T c# δt/δn=0# Water in a heated cavity. What is the effect of gravity? What is

More information

Partial Differential Equations (PDEs) and the Finite Difference Method (FDM). An introduction

Partial Differential Equations (PDEs) and the Finite Difference Method (FDM). An introduction Page of 8 Partial Differential Equations (PDEs) and the Finite Difference Method (FDM). An introduction FILE:Chap 3 Partial Differential Equations-V6. Original: May 7, 05 Revised: Dec 9, 06, Feb 0, 07,

More information

Homework 4 in 5C1212; Part A: Incompressible Navier- Stokes, Finite Volume Methods

Homework 4 in 5C1212; Part A: Incompressible Navier- Stokes, Finite Volume Methods Homework 4 in 5C11; Part A: Incompressible Navier- Stokes, Finite Volume Methods Consider the incompressible Navier Stokes in two dimensions u x + v y = 0 u t + (u ) x + (uv) y + p x = 1 Re u + f (1) v

More information

HW4, Math 228A. Multigrid Solver. Fall 2010

HW4, Math 228A. Multigrid Solver. Fall 2010 HW4, Math 228A. Multigrid Solver Date due 11/30/2010 UC Davis, California Fall 2010 Nasser M. Abbasi Fall 2010 Compiled on January 20, 2019 at 4:13am [public] Contents 1 Problem 1 3 1.1 Restriction and

More information

Spatial discretization scheme for incompressible viscous flows

Spatial discretization scheme for incompressible viscous flows Spatial discretization scheme for incompressible viscous flows N. Kumar Supervisors: J.H.M. ten Thije Boonkkamp and B. Koren CASA-day 2015 1/29 Challenges in CFD Accuracy a primary concern with all CFD

More information

DUE: WEDS MARCH 26TH 2018

DUE: WEDS MARCH 26TH 2018 HOMEWORK # 2: FINITE DIFFERENCES MAPPING AND TWO DIMENSIONAL PROBLEMS DUE: WEDS MARCH 26TH 2018 NOTE: In this homework, you will choose ONE of the following three questions to perform and hand-in. Each

More information

The behaviour of high Reynolds flows in a driven cavity

The behaviour of high Reynolds flows in a driven cavity The behaviour of high Reynolds flows in a driven cavity Charles-Henri BRUNEAU and Mazen SAAD Mathématiques Appliquées de Bordeaux, Université Bordeaux 1 CNRS UMR 5466, INRIA team MC 351 cours de la Libération,

More information

Lattice Boltzmann Method Solver Documentation

Lattice Boltzmann Method Solver Documentation Lattice Boltzmann Method Solver Documentation Release 0.0.1 Sayop Kim May 03, 2016 Contents 1 Code Instruction 3 1.1 Quick instruction for running the simulation.............................. 3 2 Results

More information

Pressure-velocity correction method Finite Volume solution of Navier-Stokes equations Exercise: Finish solving the Navier Stokes equations

Pressure-velocity correction method Finite Volume solution of Navier-Stokes equations Exercise: Finish solving the Navier Stokes equations Today's Lecture 2D grid colocated arrangement staggered arrangement Exercise: Make a Fortran program which solves a system of linear equations using an iterative method SIMPLE algorithm Pressure-velocity

More information

Computation of Incompressible Flows: SIMPLE and related Algorithms

Computation of Incompressible Flows: SIMPLE and related Algorithms Computation of Incompressible Flows: SIMPLE and related Algorithms Milovan Perić CoMeT Continuum Mechanics Technologies GmbH milovan@continuummechanicstechnologies.de SIMPLE-Algorithm I - - - Consider

More information

Project 4: Navier-Stokes Solution to Driven Cavity and Channel Flow Conditions

Project 4: Navier-Stokes Solution to Driven Cavity and Channel Flow Conditions Project 4: Navier-Stokes Solution to Driven Cavity and Channel Flow Conditions R. S. Sellers MAE 5440, Computational Fluid Dynamics Utah State University, Department of Mechanical and Aerospace Engineering

More information

Explicit Incompressible Euler Solver

Explicit Incompressible Euler Solver Explicit Incompressible Euler Solver (Written In Matlab) R D Teja Aerospace Undergraduate IIT Madras Contents: 1. Abstract 2. Introduction 2.1 Euler equations 2.2 Artificial compressibility equations 2.3

More information

Lecture 17: Iterative Methods and Sparse Linear Algebra

Lecture 17: Iterative Methods and Sparse Linear Algebra Lecture 17: Iterative Methods and Sparse Linear Algebra David Bindel 25 Mar 2014 Logistics HW 3 extended to Wednesday after break HW 4 should come out Monday after break Still need project description

More information

DOING PHYSICS WITH MATLAB. ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S and LAPLACES S EQUATIONS

DOING PHYSICS WITH MATLAB. ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S and LAPLACES S EQUATIONS DOING PHYSICS WITH MATLAB ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S and LAPLACES S EQUATIONS Ian Cooper School of Physics, University of Sydney ian.cooper@sydney.edu.au DOWNLOAD DIRECTORY FOR MATLAB

More information

Chapter Two: Numerical Methods for Elliptic PDEs. 1 Finite Difference Methods for Elliptic PDEs

Chapter Two: Numerical Methods for Elliptic PDEs. 1 Finite Difference Methods for Elliptic PDEs Chapter Two: Numerical Methods for Elliptic PDEs Finite Difference Methods for Elliptic PDEs.. Finite difference scheme. We consider a simple example u := subject to Dirichlet boundary conditions ( ) u

More information

Module 3: BASICS OF CFD. Part A: Finite Difference Methods

Module 3: BASICS OF CFD. Part A: Finite Difference Methods Module 3: BASICS OF CFD Part A: Finite Difference Methods THE CFD APPROACH Assembling the governing equations Identifying flow domain and boundary conditions Geometrical discretization of flow domain Discretization

More information

Parabolic Flow in Parallel Plate Channel ME 412 Project 4

Parabolic Flow in Parallel Plate Channel ME 412 Project 4 Parabolic Flow in Parallel Plate Channel ME 412 Project 4 Jingwei Zhu April 12, 2014 Instructor: Surya Pratap Vanka 1 Project Description The objective of this project is to develop and apply a computer

More information

Lab 5: Post Processing and Solving Conduction Problems. Objective:

Lab 5: Post Processing and Solving Conduction Problems. Objective: Lab 5: Post Processing and Solving Conduction Problems Objective: The objective of this lab is to use the tools we have developed in MATLAB and SolidWorks to solve conduction heat transfer problems that

More information

Chapter 5. Methods for Solving Elliptic Equations

Chapter 5. Methods for Solving Elliptic Equations Chapter 5. Methods for Solving Elliptic Equations References: Tannehill et al Section 4.3. Fulton et al (1986 MWR). Recommended reading: Chapter 7, Numerical Methods for Engineering Application. J. H.

More information

ME Computational Fluid Mechanics Lecture 5

ME Computational Fluid Mechanics Lecture 5 ME - 733 Computational Fluid Mechanics Lecture 5 Dr./ Ahmed Nagib Elmekawy Dec. 20, 2018 Elliptic PDEs: Finite Difference Formulation Using central difference formulation, the so called five-point formula

More information

LAB 5. INTRODUCTION Finite Difference Method

LAB 5. INTRODUCTION Finite Difference Method LAB 5 In previous two computer labs, you have seen how the analytical techniques for solving electrostatic problems can be approximately solved using numerical methods. For example, you have approximated

More information

A Study on Numerical Solution to the Incompressible Navier-Stokes Equation

A Study on Numerical Solution to the Incompressible Navier-Stokes Equation A Study on Numerical Solution to the Incompressible Navier-Stokes Equation Zipeng Zhao May 2014 1 Introduction 1.1 Motivation One of the most important applications of finite differences lies in the field

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING CAMBRIDGE, MASSACHUSETTS NUMERICAL FLUID MECHANICS FALL 2011

MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING CAMBRIDGE, MASSACHUSETTS NUMERICAL FLUID MECHANICS FALL 2011 MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING CAMBRIDGE, MASSACHUSETTS 02139 2.29 NUMERICAL FLUID MECHANICS FALL 2011 QUIZ 2 The goals of this quiz 2 are to: (i) ask some general

More information

Study of Forced and Free convection in Lid driven cavity problem

Study of Forced and Free convection in Lid driven cavity problem MIT Study of Forced and Free convection in Lid driven cavity problem 18.086 Project report Divya Panchanathan 5-11-2014 Aim To solve the Navier-stokes momentum equations for a lid driven cavity problem

More information

ME 5302 Computational fluid mechanics

ME 5302 Computational fluid mechanics ME 5302 Computational fluid mechanics Assignment Part II Thursday, 23 April 2015 National University of Singapore ARAVIND BASKAR A0136344 Question 1 Solution: Problem Statement: Analysis: The conservative

More information

LEAST-SQUARES FINITE ELEMENT MODELS

LEAST-SQUARES FINITE ELEMENT MODELS LEAST-SQUARES FINITE ELEMENT MODELS General idea of the least-squares formulation applied to an abstract boundary-value problem Works of our group Application to Poisson s equation Application to flows

More information

Lecture 2: Fundamentals 2/3: Navier-Stokes Equation + Basics of Discretization

Lecture 2: Fundamentals 2/3: Navier-Stokes Equation + Basics of Discretization Lecture 2: Fundamentals 2/3: Navier-Stokes Equation Basics of Discretization V.Vuorinen Aalto University School of Engineering CFD Course, Spring 2018 January 15th 2018, Otaniemi ville.vuorinen@aalto.fi

More information

CHAPTER 2 LOAD FLOW ANALYSIS FOR RADIAL DISTRIBUTION SYSTEM

CHAPTER 2 LOAD FLOW ANALYSIS FOR RADIAL DISTRIBUTION SYSTEM 16 CHAPTER 2 LOAD FLOW ANALYSIS FOR RADIAL DISTRIBUTION SYSTEM 2.1 INTRODUCTION Load flow analysis of power system network is used to determine the steady state solution for a given set of bus loading

More information

A Front-tracking/Finite-Volume Navier-Stokes Solver for Direct Numerical Simulations of Multiphase Flows. Grétar Tryggvason

A Front-tracking/Finite-Volume Navier-Stokes Solver for Direct Numerical Simulations of Multiphase Flows. Grétar Tryggvason A Front-tracking/Finite-Volume Navier-Stokes Solver for Direct Numerical Simulations of Multiphase Flows Grétar Tryggvason April 3, 20 2 Contents Introduction 5. Problem Specification........................

More information

BTCS Solution to the Heat Equation

BTCS Solution to the Heat Equation BTCS Solution to the Heat Equation ME 448/548 Notes Gerald Recktenwald Portland State University Department of Mechanical Engineering gerry@mepdxedu ME 448/548: BTCS Solution to the Heat Equation Overview

More information

TECHNISCHE UNIVERSITÄT MÜNCHEN. Uncertainty Quantification in Fluid Flows via Polynomial Chaos Methodologies

TECHNISCHE UNIVERSITÄT MÜNCHEN. Uncertainty Quantification in Fluid Flows via Polynomial Chaos Methodologies TECHNISCHE UNIVERSITÄT MÜNCHEN Bachelor s Thesis in Engineering Science Uncertainty Quantification in Fluid Flows via Polynomial Chaos Methodologies Jan Sültemeyer DEPARTMENT OF INFORMATICS MUNICH SCHOOL

More information

Due Tuesday, November 23 nd, 12:00 midnight

Due Tuesday, November 23 nd, 12:00 midnight Due Tuesday, November 23 nd, 12:00 midnight This challenging but very rewarding homework is considering the finite element analysis of advection-diffusion and incompressible fluid flow problems. Problem

More information

Practical Course Scientific Computing and Visualization

Practical Course Scientific Computing and Visualization May 3, 24 Page 1 of 18 1 gridpoints for pressure p: j i p, p 1, p 2, p 3, p 4, p,1 p 1,1 p 2,1 p 3,1 p 4,1 p,2 p 1,2 p 2,2 p 3,2 p 4,2 p,3 p 1,3 p 2,3 p 3,3 p 4,3 p,4 p 1,4 p 2,4 p 3,4 p 4,4 Page 2 of

More information

Cholesky factorisations of linear systems coming from a finite difference method applied to singularly perturbed problems

Cholesky factorisations of linear systems coming from a finite difference method applied to singularly perturbed problems Cholesky factorisations of linear systems coming from a finite difference method applied to singularly perturbed problems Thái Anh Nhan and Niall Madden The Boundary and Interior Layers - Computational

More information

Solution of the Two-Dimensional Steady State Heat Conduction using the Finite Volume Method

Solution of the Two-Dimensional Steady State Heat Conduction using the Finite Volume Method Ninth International Conference on Computational Fluid Dynamics (ICCFD9), Istanbul, Turkey, July 11-15, 2016 ICCFD9-0113 Solution of the Two-Dimensional Steady State Heat Conduction using the Finite Volume

More information

The Poisson equa-on in projec-on methods for incompressible flows. Bérengère Podvin, Yann Fraigneau LIMSI- CNRS

The Poisson equa-on in projec-on methods for incompressible flows. Bérengère Podvin, Yann Fraigneau LIMSI- CNRS The Poisson equa-on in projec-on methods for incompressible flows Bérengère Podvin, Yann Fraigneau LIMSI- CNRS 1 Overview Origin of the Poisson equa-on for pressure Resolu-on methods for the Poisson equa-on

More information

Entropy stable schemes for compressible flows on unstructured meshes

Entropy stable schemes for compressible flows on unstructured meshes Entropy stable schemes for compressible flows on unstructured meshes Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore deep@math.tifrbng.res.in http://math.tifrbng.res.in/

More information

IMPLEMENTATION OF PRESSURE BASED SOLVER FOR SU2. 3rd SU2 Developers Meet Akshay.K.R, Huseyin Ozdemir, Edwin van der Weide

IMPLEMENTATION OF PRESSURE BASED SOLVER FOR SU2. 3rd SU2 Developers Meet Akshay.K.R, Huseyin Ozdemir, Edwin van der Weide IMPLEMENTATION OF PRESSURE BASED SOLVER FOR SU2 3rd SU2 Developers Meet Akshay.K.R, Huseyin Ozdemir, Edwin van der Weide Content ECN part of TNO SU2 applications at ECN Incompressible flow solver Pressure-based

More information

1D-HAM. Coupled Heat, Air and Moisture Transport in Multi-layered Wall Structures. Manual with brief theory and an example. Version 2.

1D-HAM. Coupled Heat, Air and Moisture Transport in Multi-layered Wall Structures. Manual with brief theory and an example. Version 2. 1D-HAM Coupled Heat, Air and Moisture Transport in Multi-layered Wall Structures. Manual with brief theory and an example. Version 2.0 30 t=70 days (1680 h) 100 Temperatures ( C) v (g/m³) 25 20 15 10 5

More information

DOING PHYSICS WITH MATLAB ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S EQUATION

DOING PHYSICS WITH MATLAB ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S EQUATION DOING PHYSICS WITH MATLAB ELECTRIC FIELD AND ELECTRIC POTENTIAL: POISSON S EQUATION Ian Cooper School of Physics, University of Sydney ian.cooper@sydney.edu.au DOWNLOAD DIRECTORY FOR MATLAB SCRIPTS For

More information

Kasetsart University Workshop. Multigrid methods: An introduction

Kasetsart University Workshop. Multigrid methods: An introduction Kasetsart University Workshop Multigrid methods: An introduction Dr. Anand Pardhanani Mathematics Department Earlham College Richmond, Indiana USA pardhan@earlham.edu A copy of these slides is available

More information

16.2 Iterated Integrals

16.2 Iterated Integrals 6.2 Iterated Integrals So far: We have defined what we mean by a double integral. We have estimated the value of a double integral from contour diagrams and from tables of values. We have interpreted the

More information

JMBC Computational Fluid Dynamics I Exercises by A.E.P. Veldman

JMBC Computational Fluid Dynamics I Exercises by A.E.P. Veldman JMBC Computational Fluid Dynamics I Exercises by A.E.P. Veldman The exercises will be carried out on PC s in the practicum rooms. Several (Matlab and Fortran) files are required. How these can be obtained

More information

The Generalized Interpolation Material Point Method

The Generalized Interpolation Material Point Method Compaction of a foam microstructure The Generalized Interpolation Material Point Method Tungsten Particle Impacting sandstone The Material Point Method (MPM) 1. Lagrangian material points carry all state

More information

Multigrid Methods and their application in CFD

Multigrid Methods and their application in CFD Multigrid Methods and their application in CFD Michael Wurst TU München 16.06.2009 1 Multigrid Methods Definition Multigrid (MG) methods in numerical analysis are a group of algorithms for solving differential

More information

Numerical Solution of Laplace's Equation

Numerical Solution of Laplace's Equation Syracuse University SURFACE Electrical Engineering and Computer Science Technical Reports College of Engineering and Computer Science 9-1992 Numerical Solution of Laplace's Equation Per Brinch Hansen Syracuse

More information

Flow simulation on moving boundary-fitted grids and application to fluid-structure interaction problems

Flow simulation on moving boundary-fitted grids and application to fluid-structure interaction problems Flow simulation on moving boundary-fitted grids and application to fluid-structure interaction problems Martin Engel and Michael Griebel Institute of Numerical Simulation, University of Bonn, Wegelerstr.

More information

Programación Gráfica de Altas Prestaciones

Programación Gráfica de Altas Prestaciones Programación Gráfica de Altas Prestaciones Short course on High-performance simulation with high-level languages Part 1b André R. Brodtkorb, SINTEF Technology for a better society 1 Outline Part 1a Introduction

More information

Transient flow and heat equations - the Rayleigh-Benard instability

Transient flow and heat equations - the Rayleigh-Benard instability Transient flow and heat equations - the Rayleigh-Benard instability Directory: RayleighBenard Solvers: HeatSolve, FlowSolve Tools: ElmerGUI Dimensions: 2D, Transient Case definition This tutorial is about

More information

The Advanced Research WRF (ARW) Dynamics Solver

The Advanced Research WRF (ARW) Dynamics Solver Dynamics: Introduction The Advanced Research WRF (ARW) Dynamics Solver 1. What is a dynamics solver? 2. Variables and coordinates 3. Equations 4. Time integration scheme 5. Grid staggering 6. Advection

More information

Exercice I Exercice II Exercice III Exercice IV Exercice V. Exercises. Boundary Conditions in lattice Boltzmann method

Exercice I Exercice II Exercice III Exercice IV Exercice V. Exercises. Boundary Conditions in lattice Boltzmann method Exercises Boundary Conditions in lattice Boltzmann method Goncalo Silva Department of Mechanical Engineering Instituto Superior Técnico (IST) Lisbon, Portugal Setting the problem Exercise I: Poiseuille

More information

Implementation of 3D Incompressible N-S Equations. Mikhail Sekachev

Implementation of 3D Incompressible N-S Equations. Mikhail Sekachev Implementation of 3D Incompressible N-S Equations Mikhail Sekachev Navier-Stokes Equations The motion of a viscous incompressible fluid is governed by the Navier-Stokes equations u + t u = ( u ) 0 Quick

More information

Lecture 18 Classical Iterative Methods

Lecture 18 Classical Iterative Methods Lecture 18 Classical Iterative Methods MIT 18.335J / 6.337J Introduction to Numerical Methods Per-Olof Persson November 14, 2006 1 Iterative Methods for Linear Systems Direct methods for solving Ax = b,

More information

5. FVM discretization and Solution Procedure

5. FVM discretization and Solution Procedure 5. FVM discretization and Solution Procedure 1. The fluid domain is divided into a finite number of control volumes (cells of a computational grid). 2. Integral form of the conservation equations are discretized

More information

A multi-solver quasi-newton method for the partitioned simulation of fluid-structure interaction

A multi-solver quasi-newton method for the partitioned simulation of fluid-structure interaction A multi-solver quasi-newton method for the partitioned simulation of fluid-structure interaction J Degroote, S Annerel and J Vierendeels Department of Flow, Heat and Combustion Mechanics, Ghent University,

More information

ECE539 - Advanced Theory of Semiconductors and Semiconductor Devices. Numerical Methods and Simulation / Umberto Ravaioli

ECE539 - Advanced Theory of Semiconductors and Semiconductor Devices. Numerical Methods and Simulation / Umberto Ravaioli ECE539 - Advanced Theory of Semiconductors and Semiconductor Devices 1 General concepts Numerical Methods and Simulation / Umberto Ravaioli Introduction to the Numerical Solution of Partial Differential

More information

Supplementary Information for Engineering and Analysis of Surface Interactions in a Microfluidic Herringbone Micromixer

Supplementary Information for Engineering and Analysis of Surface Interactions in a Microfluidic Herringbone Micromixer Supplementary Information for Engineering and Analysis of Surface Interactions in a Microfluidic Herringbone Micromixer Thomas P. Forbes and Jason G. Kralj National Institute of Standards and Technology,

More information

Background. Background. C. T. Kelley NC State University tim C. T. Kelley Background NCSU, Spring / 58

Background. Background. C. T. Kelley NC State University tim C. T. Kelley Background NCSU, Spring / 58 Background C. T. Kelley NC State University tim kelley@ncsu.edu C. T. Kelley Background NCSU, Spring 2012 1 / 58 Notation vectors, matrices, norms l 1 : max col sum... spectral radius scaled integral norms

More information

Numerical Solution Techniques in Mechanical and Aerospace Engineering

Numerical Solution Techniques in Mechanical and Aerospace Engineering Numerical Solution Techniques in Mechanical and Aerospace Engineering Chunlei Liang LECTURE 3 Solvers of linear algebraic equations 3.1. Outline of Lecture Finite-difference method for a 2D elliptic PDE

More information

MATH 333: Partial Differential Equations

MATH 333: Partial Differential Equations MATH 333: Partial Differential Equations Problem Set 9, Final version Due Date: Tues., Nov. 29, 2011 Relevant sources: Farlow s book: Lessons 9, 37 39 MacCluer s book: Chapter 3 44 Show that the Poisson

More information

Relevant self-assessment exercises: [LIST SELF-ASSESSMENT EXERCISES HERE]

Relevant self-assessment exercises: [LIST SELF-ASSESSMENT EXERCISES HERE] Chapter 6 Finite Volume Methods In the previous chapter we have discussed finite difference methods for the discretization of PDEs. In developing finite difference methods we started from the differential

More information

Lattice-Boltzmann vs. Navier-Stokes simulation of particulate flows

Lattice-Boltzmann vs. Navier-Stokes simulation of particulate flows Lattice-Boltzmann vs. Navier-Stokes simulation of particulate flows Amir Eshghinejadfard, Abouelmagd Abdelsamie, Dominique Thévenin University of Magdeburg, Germany 14th Workshop on Two-Phase Flow Predictions

More information

n i,j+1/2 q i,j * qi+1,j * S i+1/2,j

n i,j+1/2 q i,j * qi+1,j * S i+1/2,j Helsinki University of Technology CFD-group/ The Laboratory of Applied Thermodynamics MEMO No CFD/TERMO-5-97 DATE: December 9,997 TITLE A comparison of complete vs. simplied viscous terms in boundary layer

More information

Fluid-Structure Interaction Problems using SU2 and External Finite-Element Solvers

Fluid-Structure Interaction Problems using SU2 and External Finite-Element Solvers Fluid-Structure Interaction Problems using SU2 and External Finite-Element Solvers R. Sanchez 1, D. Thomas 2, R. Palacios 1, V. Terrapon 2 1 Department of Aeronautics, Imperial College London 2 Department

More information

Computation Fluid Dynamics Prof. Dr. Suman Chakraborty Department of Mechanical Engineering Indian Institute of Technology, Kharagpur

Computation Fluid Dynamics Prof. Dr. Suman Chakraborty Department of Mechanical Engineering Indian Institute of Technology, Kharagpur Computation Fluid Dynamics Prof. Dr. Suman Chakraborty Department of Mechanical Engineering Indian Institute of Technology, Kharagpur Lecture No. # 40 What is there in implementing a CFD Code So far, we

More information

Math 502 Fall 2005 Solutions to Homework 5. Let x = A ;1 b. Then x = ;D ;1 (L+U)x +D ;1 b, and hence the dierences

Math 502 Fall 2005 Solutions to Homework 5. Let x = A ;1 b. Then x = ;D ;1 (L+U)x +D ;1 b, and hence the dierences Math 52 Fall 25 Solutions to Homework 5 (). The i-th row ofd ; (L + U) is r i =[ a i ::: a i i; a i i+ ::: a i M ] a i i a i i a i i a i i Since A is strictly X row diagonally dominant jr i j = j a i j

More information

Code: 101MAT4 101MT4B. Today s topics Finite-difference method in 2D. Poisson equation Wave equation

Code: 101MAT4 101MT4B. Today s topics Finite-difference method in 2D. Poisson equation Wave equation Code: MAT MTB Today s topics Finite-difference method in D Poisson equation Wave equation Finite-difference method for elliptic PDEs in D Recall that u is the short version of u x + u y Dirichlet BVP:

More information

One Dimensional Convection: Interpolation Models for CFD

One Dimensional Convection: Interpolation Models for CFD One Dimensional Convection: Interpolation Models for CFD ME 448/548 Notes Gerald Recktenwald Portland State University Department of Mechanical Engineering gerry@pdx.edu ME 448/548: 1D Convection-Diffusion

More information

13 Plastic Flow in a Punch Problem

13 Plastic Flow in a Punch Problem Plastic Flow in a Punch Problem 13-1 13 Plastic Flow in a Punch Problem 13.1 Problem Statement Difficulties are sometimes reported in the modeling of plastic flow where large velocity gradients exist.

More information

Tutorial for the heated pipe with constant fluid properties in STAR-CCM+

Tutorial for the heated pipe with constant fluid properties in STAR-CCM+ Tutorial for the heated pipe with constant fluid properties in STAR-CCM+ For performing this tutorial, it is necessary to have already studied the tutorial on the upward bend. In fact, after getting abilities

More information

Introduction to Heat and Mass Transfer. Week 9

Introduction to Heat and Mass Transfer. Week 9 Introduction to Heat and Mass Transfer Week 9 補充! Multidimensional Effects Transient problems with heat transfer in two or three dimensions can be considered using the solutions obtained for one dimensional

More information

NOVEL FINITE DIFFERENCE SCHEME FOR THE NUMERICAL SOLUTION OF TWO-DIMENSIONAL INCOMPRESSIBLE NAVIER-STOKES EQUATIONS

NOVEL FINITE DIFFERENCE SCHEME FOR THE NUMERICAL SOLUTION OF TWO-DIMENSIONAL INCOMPRESSIBLE NAVIER-STOKES EQUATIONS INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING Volume 7 Number Pages 3 39 c Institute for Scientific Computing and Information NOVEL FINITE DIFFERENCE SCHEME FOR THE NUMERICAL SOLUTION OF TWO-DIMENSIONAL

More information

Draft Notes ME 608 Numerical Methods in Heat, Mass, and Momentum Transfer

Draft Notes ME 608 Numerical Methods in Heat, Mass, and Momentum Transfer Draft Notes ME 608 Numerical Methods in Heat, Mass, and Momentum Transfer Instructor: Jayathi Y. Murthy School of Mechanical Engineering Purdue University Spring 00 c 1998 J.Y. Murthy and S.R. Mathur.

More information

Numerical Modelling in Fortran: day 9. Paul Tackley, 2017

Numerical Modelling in Fortran: day 9. Paul Tackley, 2017 Numerical Modelling in Fortran: day 9 Paul Tackley, 2017 Today s Goals 1. Implicit time stepping. 2. Useful libraries and other software 3. Fortran and numerical methods: Review and discussion. New features

More information

Sparse Linear Systems. Iterative Methods for Sparse Linear Systems. Motivation for Studying Sparse Linear Systems. Partial Differential Equations

Sparse Linear Systems. Iterative Methods for Sparse Linear Systems. Motivation for Studying Sparse Linear Systems. Partial Differential Equations Sparse Linear Systems Iterative Methods for Sparse Linear Systems Matrix Computations and Applications, Lecture C11 Fredrik Bengzon, Robert Söderlund We consider the problem of solving the linear system

More information

Numerical Programming I (for CSE)

Numerical Programming I (for CSE) Technische Universität München WT 1/13 Fakultät für Mathematik Prof. Dr. M. Mehl B. Gatzhammer January 1, 13 Numerical Programming I (for CSE) Tutorial 1: Iterative Methods 1) Relaxation Methods a) Let

More information

Algebraic Multigrid as Solvers and as Preconditioner

Algebraic Multigrid as Solvers and as Preconditioner Ò Algebraic Multigrid as Solvers and as Preconditioner Domenico Lahaye domenico.lahaye@cs.kuleuven.ac.be http://www.cs.kuleuven.ac.be/ domenico/ Department of Computer Science Katholieke Universiteit Leuven

More information

A multigrid method for large scale inverse problems

A multigrid method for large scale inverse problems A multigrid method for large scale inverse problems Eldad Haber Dept. of Computer Science, Dept. of Earth and Ocean Science University of British Columbia haber@cs.ubc.ca July 4, 2003 E.Haber: Multigrid

More information

Game Physics. Game and Media Technology Master Program - Utrecht University. Dr. Nicolas Pronost

Game Physics. Game and Media Technology Master Program - Utrecht University. Dr. Nicolas Pronost Game and Media Technology Master Program - Utrecht University Dr. Nicolas Pronost Soft body physics Soft bodies In reality, objects are not purely rigid for some it is a good approximation but if you hit

More information

Diffusion / Parabolic Equations. PHY 688: Numerical Methods for (Astro)Physics

Diffusion / Parabolic Equations. PHY 688: Numerical Methods for (Astro)Physics Diffusion / Parabolic Equations Summary of PDEs (so far...) Hyperbolic Think: advection Real, finite speed(s) at which information propagates carries changes in the solution Second-order explicit methods

More information

Basic Aspects of Discretization

Basic Aspects of Discretization Basic Aspects of Discretization Solution Methods Singularity Methods Panel method and VLM Simple, very powerful, can be used on PC Nonlinear flow effects were excluded Direct numerical Methods (Field Methods)

More information

Matrices handling in PDEs resolution with MATLAB R

Matrices handling in PDEs resolution with MATLAB R Matrices handling in PDEs resolution with MATLAB R Riccardo Zamolo riccardo.zamolo@phd.units.it Dipartimento di Ingegneria Meccanica e Navale Università degli Studi Trieste, 34127 TRIESTE April 6, 2016

More information

SPECTRAL METHOD FOR TIME DEPENDENT NAVIER-STOKES EQUATIONS

SPECTRAL METHOD FOR TIME DEPENDENT NAVIER-STOKES EQUATIONS Miskolc Mathematical Notes HU e-issn 1787-2413 Vol. 17 (216), No. 1, pp. 43 56 DOI: 1.18514/MMN.216.1815 SPECTRAL METHOD FOR TIME DEPENDENT NAVIER-STOKES EQUATIONS GABRIELLA BOGNÁR AND ZOLTÁN CSÁTI Received

More information

Parallel Programming in C with MPI and OpenMP

Parallel Programming in C with MPI and OpenMP Parallel Programming in C with MPI and OpenMP Michael J. Quinn Chapter 13 Finite Difference Methods Outline n Ordinary and partial differential equations n Finite difference methods n Vibrating string

More information

Additive Manufacturing Module 8

Additive Manufacturing Module 8 Additive Manufacturing Module 8 Spring 2015 Wenchao Zhou zhouw@uark.edu (479) 575-7250 The Department of Mechanical Engineering University of Arkansas, Fayetteville 1 Evaluating design https://www.youtube.com/watch?v=p

More information

DISPENSA FEM in MSC. Nastran

DISPENSA FEM in MSC. Nastran DISPENSA FEM in MSC. Nastran preprocessing: mesh generation material definitions definition of loads and boundary conditions solving: solving the (linear) set of equations components postprocessing: visualisation

More information

Elliptic Problems / Multigrid. PHY 604: Computational Methods for Physics and Astrophysics II

Elliptic Problems / Multigrid. PHY 604: Computational Methods for Physics and Astrophysics II Elliptic Problems / Multigrid Summary of Hyperbolic PDEs We looked at a simple linear and a nonlinear scalar hyperbolic PDE There is a speed associated with the change of the solution Explicit methods

More information

Physics 432, Physics of fluids: Assignment #1 Solutions

Physics 432, Physics of fluids: Assignment #1 Solutions Physics 432, Physics of fluids: Assignment #1 Solutions 1. This is an investigation of the two-dimensional draining bathtub problem described in lecture, where the tub has fluid level h, width 2L and drain

More information

High-resolution finite volume methods for hyperbolic PDEs on manifolds

High-resolution finite volume methods for hyperbolic PDEs on manifolds High-resolution finite volume methods for hyperbolic PDEs on manifolds Randall J. LeVeque Department of Applied Mathematics University of Washington Supported in part by NSF, DOE Overview High-resolution

More information

Least-Squares Spectral Collocation with the Overlapping Schwarz Method for the Incompressible Navier Stokes Equations

Least-Squares Spectral Collocation with the Overlapping Schwarz Method for the Incompressible Navier Stokes Equations Least-Squares Spectral Collocation with the Overlapping Schwarz Method for the Incompressible Navier Stokes Equations by Wilhelm Heinrichs Universität Duisburg Essen, Ingenieurmathematik Universitätsstr.

More information

Chapter 6. Finite Element Method. Literature: (tiny selection from an enormous number of publications)

Chapter 6. Finite Element Method. Literature: (tiny selection from an enormous number of publications) Chapter 6 Finite Element Method Literature: (tiny selection from an enormous number of publications) K.J. Bathe, Finite Element procedures, 2nd edition, Pearson 2014 (1043 pages, comprehensive). Available

More information

1 R.V k V k 1 / I.k/ here; we ll stimulate the action potential another way.) Note that this further simplifies to. m 3 k h k.

1 R.V k V k 1 / I.k/ here; we ll stimulate the action potential another way.) Note that this further simplifies to. m 3 k h k. 1. The goal of this problem is to simulate a propagating action potential for the Hodgkin-Huxley model and to determine the propagation speed. From the class notes, the discrete version (i.e., after breaking

More information

Peristaltic Pump. Introduction. Model Definition

Peristaltic Pump. Introduction. Model Definition Peristaltic Pump Introduction In a peristaltic pump, rotating rollers are squeezing a flexible tube. As the pushed down rollers move along the tube, the fluid in the tube follows the motion. The main advantage

More information

Finite Difference Method

Finite Difference Method Finite Difference Method for BVP ODEs Dec 3, 2014 1 Recall An ordinary differential equation is accompanied by auxiliary conditions. In the analytical method, these conditions are used to evaluate the

More information

Bindel, Fall 2016 Matrix Computations (CS 6210) Notes for

Bindel, Fall 2016 Matrix Computations (CS 6210) Notes for 1 Iteration basics Notes for 2016-11-07 An iterative solver for Ax = b is produces a sequence of approximations x (k) x. We always stop after finitely many steps, based on some convergence criterion, e.g.

More information

Design and Modeling of Fluid Power Systems ME 597/ABE Lecture 7

Design and Modeling of Fluid Power Systems ME 597/ABE Lecture 7 Systems ME 597/ABE 591 - Lecture 7 Dr. Monika Ivantysynova MAHA Professor Fluid Power Systems MAHA Fluid Power Research Center Purdue University Content of 6th lecture The lubricating gap as a basic design

More information

Chapter 5 HIGH ACCURACY CUBIC SPLINE APPROXIMATION FOR TWO DIMENSIONAL QUASI-LINEAR ELLIPTIC BOUNDARY VALUE PROBLEMS

Chapter 5 HIGH ACCURACY CUBIC SPLINE APPROXIMATION FOR TWO DIMENSIONAL QUASI-LINEAR ELLIPTIC BOUNDARY VALUE PROBLEMS Chapter 5 HIGH ACCURACY CUBIC SPLINE APPROXIMATION FOR TWO DIMENSIONAL QUASI-LINEAR ELLIPTIC BOUNDARY VALUE PROBLEMS 5.1 Introduction When a physical system depends on more than one variable a general

More information

Computation Time Assessment of a Galerkin Finite Volume Method (GFVM) for Solving Time Solid Mechanics Problems under Dynamic Loads

Computation Time Assessment of a Galerkin Finite Volume Method (GFVM) for Solving Time Solid Mechanics Problems under Dynamic Loads Proceedings of the International Conference on Civil, Structural and Transportation Engineering Ottawa, Ontario, Canada, May 4 5, 215 Paper o. 31 Computation Time Assessment of a Galerkin Finite Volume

More information