1 Discretization of Fluid Models (Navier Stokes) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal.

Slides:



Advertisements
Similar presentations
Stable Fluids A paper by Jos Stam.
Advertisements

My First Fluid Project Ryan Schmidt. Outline MAC Method How far did I get? What went wrong? Future Work.
HE 316 Term Project Presentation Symmetry Analysis in Fluid Dynamics
Computational Methods II (Elliptic)
Chapter 8 Elliptic Equation.
Particle Acceleration Particle t t+dt. Physical Interpretation Total acceleration of a particle Local acceleration Convective acceleration time velocity.
Continuity Equation. Continuity Equation Continuity Equation Net outflow in x direction.
12/21/2001Numerical methods in continuum mechanics1 Continuum Mechanics On the scale of the object to be studied the density and other fluid properties.
2-1 Problem Solving 1. Physics  2. Approach methods
Lecture 4 Pressure variation in a static fluid N.S. Equations & simple solutions Intro DL.
P M V Subbarao Professor Mechanical Engineering Department I I T Delhi
Reynolds Method to Diagnosize Symptoms of Infected Flows.... P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Reynolds Averaged.
Numerical methods for PDEs PDEs are mathematical models for –Physical Phenomena Heat transfer Wave motion.
Conservation Laws for Continua
Lecture Objectives Review SIMPLE CFD Algorithm SIMPLE Semi-Implicit Method for Pressure-Linked Equations Define Residual and Relaxation.
1 EMT 101 – Engineering Programming Dr. Farzad Ismail School of Aerospace Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week 9.
1 EMT 101 – Engineering Programming Dr. Farzad Ismail School of Aerospace Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week 4.
1 Discretization of Fluid Models (Navier Stokes) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal.
1 Computational Methods Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week.
Governing equations: Navier-Stokes equations, Two-dimensional shallow-water equations, Saint-Venant equations, compressible water hammer flow equations.
1 Computational Methods II (Elliptic) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau.
1 Discretization of Fluid Models (Navier Stokes) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal.
Lecture Objectives: Explicit vs. Implicit Residual, Stability, Relaxation Simple algorithm.
Yoon kichul Department of Mechanical Engineering Seoul National University Multi-scale Heat Conduction.
1 Computational Methods II (Elliptic) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau.
1 Discretization Methods Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week.
IIT-Madras, Momentum Transfer: July 2005-Dec 2005 Perturbation: Background n Algebraic n Differential Equations.
AOE 5104 Class 8 Online presentations for next class: –Kinematics 2 and 3 Homework 3 (thank you) Homework 4 (6 questions, 2 graded, 2 recitations, worth.
1 EMT 101 – Engineering Programming Dr. Farzad Ismail School of Aerospace Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week 9.
1 EEE 431 Computational Methods in Electrodynamics Lecture 3 By Dr. Rasime Uyguroglu.
Lecture Objectives Review Define Residual and Relaxation SIMPLE CFD Algorithm SIMPLE Semi-Implicit Method for Pressure-Linked Equations.
CIS/ME 794Y A Case Study in Computational Science & Engineering 2-D Conservation of Mass uu dx dy vv (x,y)
Stream Function & Velocity Potential
1 EMT 101 – Engineering Programming Dr. Farzad Ismail School of Aerospace Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week 6.
COMPUTATIONAL FLUID DYNAMICS (AE 2402) Presented by IRISH ANGELIN S AP/AERO.
1 Scalar Conservation Law Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week.
LES of Turbulent Flows: Lecture 5 (ME EN )
AMS 691 Special Topics in Applied Mathematics Lecture 3
CP502 Advanced Fluid Mechanics
V. Fundamentals of Fluid Dynamics. Contents 1. State of Stress in Moving Fluid 2. Equations of Motion 3. Bernoulli Equation.
Lecture 6 The boundary-layer equations
Solving linear systems in fluid dynamics P. Aaron Lott Applied Mathematics and Scientific Computation Program University of Maryland.
Model Anything. Quantity Conserved c  advect  diffuse S ConservationConstitutiveGoverning Mass, M  q -- M Momentum fluid, Mv -- F Momentum fluid.
Computer Animation Rick Parent Computer Animation Algorithms and Techniques Computational Fluid Dynamics.
MAE 5130: VISCOUS FLOWS Lecture 2: Introductory Concepts
I- Computational Fluid Dynamics (CFD-I)
Objective Numerical methods SIMPLE CFD Algorithm Define Relaxation
EMT 101 – Engineering Programming
Lecture Objectives: Review Explicit vs. Implicit
© Fluent Inc. 1/10/2018L1 Fluids Review TRN Solution Methods.
AE/ME 339 Computational Fluid Dynamics (CFD) K. M. Isaac 11/13/2018
Lecture Objectives: Advance discretization methods
Objective Unsteady state Numerical methods Discretization
AMS 599 Special Topics in Applied Mathematics Lecture 3
Space Distribution of Spray Injected Fluid
CFD – Fluid Dynamics Equations
INTRODUCTION to FLUID MECHANICS
Objective Numerical methods Finite volume.
topic8_NS_vectorForm_F02
Objective Reynolds Navier Stokes Equations (RANS) Numerical methods.
topic4: Implicit method, Stability, ADI method
AE/ME 339 Computational Fluid Dynamics (CFD) K. M. Isaac 2/28/2019
topic8_NS_vectorForm_F02
Part 5:Vorticity.
12. Navier-Stokes Applications
Topic 8 Pressure Correction
FLUID MECHANICS LECTURE
14. Computational Fluid Dynamics
CFD Applications G.S.RAVI SHANKAR.
David Marshburn Comp 259 April 17, 2002
Presentation transcript:

1 Discretization of Fluid Models (Navier Stokes) Dr. Farzad Ismail School of Aerospace and Mechanical Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang Week 5 (Lecture 1 and 2)

2 Preview We have talked about various schemes to solve model problems. Would like to use the knowledge to solve real fluid models. Before we do that, first need to understand the mathematical and physical nature of fluid dynamics.

3 The Compressible Navier Stokes One of the most complete mathematical models for fluids. Includes compressibility, viscous, heat transfer, advection, pressure effects. Can also be used to account for reacting fluids

4 2D Compressible NS

5 The Compressible Navier Stokes (cont’d) In 2D, a system of 4 x 4 (3D - 5 x 5) A hybrid of hyperbolic and parabolic types for unsteady cases Elliptic in nature for steady cases Decompose NS model into inviscid (compressible) and viscous (incompressible) parts

6 2D Incompressible Navier Stokes (NS) How do you know that mass equation is numerically satisfied?

7 Pressure Poisson (1) (2) (3)(4) (1) (4) (3)

8 Pressure Poisson (cont’d) (3) Solve * and ** for incompressible NS (*) (**)

9 2D Incompressible Navier Stokes (NS) The momentum can be rewritten (***)

10 Exercise Take the gradient of Eqn (***), apply the mass equation and show that What does this equation provide? More importantly, what is the nature of this eqn And how to solve it?

11 2D Incompressible NS (cont’d) Incompressible flow has only mass and momentum equations –The energy equation drops out (3 eqns, 3 unknowns) Mass is implicitly solved through the pressure-Poisson equation –Pressure-based solver (i.e. SIMPLE, PISO) –Requires iterations to satisfy velocity divergence- expensive! Adds an elliptic nature to pde on top of the hyperbolic and parabolic natures Flow is ‘smooth’