Computational Fluid Dynamics II



Similar documents
8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

Consider a 1-D stationary state diffusion-type equation, which we will call the generalized diffusion equation from now on:

Imperial College London

1 Example 1: Axis-aligned rectangles

Damage detection in composite laminates using coin-tap method

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Immersed interface methods for moving interface problems

Support Vector Machines

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

An Overview of Computational Fluid Dynamics

Actuator forces in CFD: RANS and LES modeling in OpenFOAM

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST)

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and

Finite difference method

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

Recurrence. 1 Definitions and main statements

Extending Probabilistic Dynamic Epistemic Logic

Modern Problem Solving Techniques in Engineering with POLYMATH, Excel and MATLAB. Introduction

PERRON FROBENIUS THEOREM

Simulating injection moulding of microfeatured components

v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

This circuit than can be reduced to a planar circuit

Time Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters

Ring structure of splines on triangulations

Method for Production Planning and Inventory Control in Oil

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A Three-Point Combined Compact Difference Scheme

Quantization Effects in Digital Filters

Faraday's Law of Induction

Modelling of Hot Water Flooding

The Noether Theorems: from Noether to Ševera

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM

Analysis of Lattice Boltzmann Boundary Conditions

A high-order compact method for nonlinear Black-Scholes option pricing equations of American Options

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Comparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions

Generalizing the degree sequence problem

Basic Equations of Fluid Dynamics

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.

CHAPTER-II WATER-FLOODING. Calculating Oil Recovery Resulting from Displ. by an Immiscible Fluid:

Lecture 2 Sequence Alignment. Burr Settles IBS Summer Research Program 2008 bsettles@cs.wisc.edu

Introduction to Differential Algebraic Equations

NUMERICAL INVESTIGATION OF AIR FLOW INSIDE AN OFFICE ROOM UNDER VARIOUS VENTILATION CONDITIONS

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process

A DATA MINING APPLICATION IN A STUDENT DATABASE

Interlude: Interphase Mass Transfer

Sharp-Crested Weir Discharge Coefficient

Numerical Methods 數 值 方 法 概 說. Daniel Lee. Nov. 1, 2006

FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals

Exhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

An MILP model for planning of batch plants operating in a campaign-mode

BERNSTEIN POLYNOMIALS

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Finite Math Chapter 10: Study Guide and Solution to Problems

LECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS

Portfolio Loss Distribution

IMPACT ANALYSIS OF A CELLULAR PHONE

s-domain Circuit Analysis

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Brigid Mullany, Ph.D University of North Carolina, Charlotte

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are:

THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES

L10: Linear discriminants analysis

Least Squares Fitting of Data

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

Mathematical modeling of water quality in river systems. Case study: Jajrood river in Tehran - Iran

CFD MODELLING BY DHI. Statement of Qualifications

Applied Research Laboratory. Decision Theory and Receiver Design

Multiple stage amplifiers

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch

where the coordinates are related to those in the old frame as follows.

Compiling for Parallelism & Locality. Dependence Testing in General. Algorithms for Solving the Dependence Problem. Dependence Testing

Research Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization

NPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6

Depreciation of Business R&D Capital

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

Implementation of Deutsch's Algorithm Using Mathcad

An Analysis of Pricing Methods for Baskets Options

Introduction. by a source term ( ) 242 / Vol. XXVIII, No. 2, April-June 2006 ABCM. Denise Maria V. Martinez et al

Sensor placement for leak detection and location in water distribution networks

Form-finding of grid shells with continuous elastic rods

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

Loop Parallelization

The Proper Use of Risk Measures in Portfolio Theory

Simulation of Under Water Explosion using MSC.Dytran

An Analysis of Dynamic Severity and Population Size

Transcription:

Computatonal Flud Dynamcs II Eercse 2 1. Gven s the PDE: u tt a 2 ou Formulate the CFL-condton for two possble eplct schemes. 2. The Euler equatons for 1-dmensonal, unsteady flows s dscretsed n the followng form: U n+1 U n + Fn +1 Fn, U = ρ ρu ρe For whch veloctes does ths scheme fulfll the CFL-condton? 3. Formulate for the lnear model equaton the followng soluton schemes: (a) eplct scheme, central dfferences (b) La-Wendroff scheme (c) Mac-Cormack scheme u t +au, F n = F(U n ) Determne the stablty condtons and truncaton errors. Show that the Mac-Cormack scheme and the La-Wendroff scheme are equvalent for ths lnear model equaton. 4. Check the consstency, stablty and convergence of an mplct method wth backward dfference n tme and central dfferences n space for the followng PDE: u t +au Specfy the soluton algorthm for that scheme, wth use of the boundary condtons u(=0)=u and u =L=0. 4

Computatonal Flud Dynamcs II Eercse 2 (soluton) 1. CFL condton: the numercal doman of nfluence has to enclose the physcal one. The characterstc lnes defne the physcal doman of nfluence, the dfference stencl defnes the numercal doman of nfluence. eplct scheme 1: 2u n +un 1 2 a 2 u n +1 2un +un 1 0 2 physcal doman of nfluence: dt d C = ± 1 a 0 t,n 1/a 0 1/a 0, eplct scheme 2: numercal nfluence area physcal nfluence area numercal doman of nfluence: dt d = ± N CFL-condton: 1 a 0 2u n +un 1 2 a 2 u+1 n 1 2un 1 +u 1 n 1 0 2 physcal doman of nfluence: dt d C = ± 1 a 0 t,n, 1/a 0 1/a 0 numercal nfluence area physcal nfluence area numercal doman of nfluence: CFL-condton: dt d N = ±2 1 2 a 0 5

2. 1D-Euler equatons: ρ t +(ρu) (ρu) t +(ρu 2 +p) (ρe) t +(u(ρe +p)) wth the equaton of state for deal gases: p = (κ 1)(ρE ρ 2 u2 ) and a 2 = κrt Dfferentate and convert n non-conservatve form: ρ t +uρ +ρu uρ t +ρu t +u(ρu) +ρuu +p (ρe) t +(uρe) +(up) Insert the contnuty equaton nto the momentum equaton and the contnuty, momentum, and equaton of state nto the energy equaton. After smplfcaton the followng form can be obtaned: ρ t +uρ +ρu u t +uu + 1 ρ p p t +up +ρa 2 u Characterstc lnes: Ω t +uω ρω 0 1 0 Ω t +uω ρ Ω 0 ρa 2 Ω Ω t +uω (Ω t +uω ) 3 Ω 2 a 2 (Ω t +uω ) Ω t = d 1 dt = u Ω t = d 1 2,3 dt = u±a 2,3 CFL-condton: all characterstc lnes have to le n the numercal doman of nfluence: Ω Ω condton (sde ): u+a 0 n+1 condton (sde +1): t n u a t u+a u +1 u a.e.: a u a 6

3. Lnear model equaton u t +au (a) Eplct, central dfferences wth u n +a un +1 un 1 2 u n = u+u t + 2 2 u tt + 3 6 u ttt +... = u u n +1 = u+ u + 2 2 u + 3 6 u +... u n 1 = u u + 2 2 u 3 6 u +... follows Truncaton error u t + 2 2 u tt + 3 6 u ttt +a 2 u +2 3 6 u 2 u t + 2 u tt + 2 6 u ttt +a(u + 2 6 u ) von Neumann analyss: u t +au = 2 u tt 2 6 u ttt a 2 6 u = O(, 2 ) Approach for the error functonǫ: ǫ n = φ=π φ=0 n (Φ)e ΦI, Φ = 2π λ, t = n, I = 1 apply the approach n the model equaton wth e ΦI n e ΦI +a n e (+1)ΦI n e ( 1)ΦI 2 1 n +a eφi e ΦI 2 e ΦI = cos(φ)+isn(φ) e ΦI = cos(φ) Isn(Φ) 7

follows G = 1 n +a 2Isn(Φ) 2 n = 1 a Isn(Φ) G 2 = 1+ n 1+a Isn(Φ) ( a sn(φ) ) 2 for a stable dfference scheme t s requred that G 2 1 scheme s unstable! (b) La-Wendroff scheme u n +a un +1 un 1 2 wth,u n,un +1 andun 1 (see (a)) follows u+u t + 2 2 u tt + 3 6 u ttt u + a 2 un +1 2un +un 1 2 2 a (u+ u + 2 2 u + 3 6 u ) (u u + 2 2 u 3 6 u ) 2 a 2 (u+ u + 2 2 u + 3 6 u ) (2u)+(u u + 2 2 u 3 6 u ) 2 2 u+u t + 2 2 u tt + 3 6 u ttt u +a 2 u +2 3 6 u 2 u t + 2 u tt + 2 6 u ttt +au +a 2 6 u a 2 2 u Truncaton error a 2 2 2 2 u 2 2 u t +au = 2 u tt 2 6 u ttt a 2 6 u +a 2 2 u wth u tt = a 2 u von Neumann analyss: = a 2 2 u 2 6 u ttt a 2 6 u +a 2 2 u = 2 6 u ttt a 2 6 u = O( 2, 2 ) e ΦI n e ΦI 1 n +a eφi e ΦI 2 G = +a n e (+1)ΦI n e ( 1)ΦI 2 a 2 eφi 2+e ΦI 2 2 = n = 1 aisn(φ) a 2 n e (+1)ΦI 2 n e ΦI + n e ( 1)ΦI 2 2 1 n +a 2Isn(Φ) a 2 2cos(Φ) 2 2 2 2 +a 2 2cos(Φ) 1 2 wth k = a 8

G 2 = (1+k 2 (cos(φ) 1)) 2 +( ksn(φ)) 2 = 1+2k 2 (cos(φ) 1)+k 4 (cos(φ) 1) 2 +k 2 sn 2 (Φ) = k 4 (1 cos(φ)) 2 +k 2 (sn 2 (Φ) 2+2cos(Φ))+1 = k 4 (1 cos(φ)) 2 +k 2 ( 1+2cos(Φ) cos 2 (Φ))+1 = k 4 (1 cos(φ)) 2 k 2 (1 2cos(Φ)+cos 2 (Φ))+1 = k 4 (1 cos(φ)) 2 k 2 (1 cos(φ)) 2 +1 = (k 4 k 2 )(1 cos(φ)) 2 +1 1 (for stablty) stable f G 2 1 = (k 4 k 2 )(1 cos(φ)) 2 0 } {{ } 0 k 2 (k 2 1) 0 k 2 1 a 1 (c) Mac-Cormack scheme Step 1 Step 2 ũ = u n a (un u n 1) wth follows = 1 2 (un +ũ ) 1 2 a (ũ +1 ũ ) ũ = u a ( u 2 2 u + 3 6 u ) ũ +1 = u+ u + 2 2 u + 3 6 u a ( u + 2 2 u + 3 6 u ) = 1 2 u+u a ( u 2 2 u + 3 6 u ) 1 2 a u+ u + 2 2 u + 3 6 u a ( u + 2 2 u + 3 6 u ) 1 2 a (u a ( u 2 2 u + 3 6 u )) = 1 2u a 2 ( u 2 2 u + 3 6 u ) + 1 2 a u u 2 2 u 3 6 u +a ( u + 2 2 u + 3 6 u ) + 1 2 a u+a ( u + 2 2 u 3 6 u ) 9

wth = 1 2 2u a ( u 2 2 u + 3 6 u ) + 1 2 a u 2 2 u 3 6 u +a 2 u = u+ 1 2 a u + 2 2 u 3 6 u + 1 2 a u 2 2 u 3 6 u +a 2 u = u+ 1 2 a 2 u 2 3 u +a 6 2 u = u+u t + 2 2 u tt + 3 6 u ttt u+u t + 2 2 u tt + 3 6 u ttt = u+ 1 2 a and u tt = a 2 u follows u t + 2 2 a2 u + 3 6 u ttt = 1 2 a Truncaton error 2 u 2 3 u +a 6 2 u 2 u 2 3 u +a 6 2 u u t +a 2 2 u + 2 6 u ttt = au a 2 6 u +a 2 2 u Alternatve: nsert step 1 nto step 2: 2 2 u t +au = 2 6 u ttt a 2 6 u = O( 2, 2 ) = 1 2 (un +u n a (un u n 1)) 1 2 a (un +1 a (un +1 u n ) u n +a (un u n 1)) = 2u n a (un u n 1) a (un +1 a (un +1 u n ) u n +a (un u n 1)) = 2u n a (un u n 1 +u n +1 u n )+a 2 2 2(un +1 u n u n +u n 1) 2 2u n +a (un +1 u n 1) a 2 2 2(un 1 2u n +u n +1) u n +a un +1 un 1 2 a 2 un 1 2un +un +1 2 2 Truncaton error and stablty equvalent to that of the La-Wendroff scheme. 10

4. u t +au Implct scheme wth backward deducton n tme, central dfferences n space: wth u n +a un+1 +1 un+1 1 2 u n = t + 2 2 un+1 tt +... ±1 = ± + 2 2 un+1 ± 3 6 un+1 +... Consstency: lm L(u) L (u) = lm τ(u), 0, 0 L (u) = un+1 + t ( = t 2 un+1 tt +a L(u) = t +a Stablty: lm τ(u) = lm, 0 2 2 un+1 tt, 0 + 2 6 un+1 +a 2 un+1 ) 2 un+1 tt 2 6 un+1 +2 3 6 un+1 2 +O( 3, 2 ) +O( 3, 3 ) +O( 3, 2 ) scheme s consstent u n +a un+1 +1 un+1 1 2 von Neumann analyss e IΦ n e IΦ +a e IΦ(+1) e IΦ( 1) 2 = 1 n = n +a 2IsnΦ 2 = 1 n +a (e IΦ e IΦ ) 2 n+1 +a snφi n 1 G = = 1+a snφi ( 1 G 2 = 1+ a ) 2 sn 2 Φ G 2 1 = ( 1+ a ) 2 1 stable sn 2 Φ } {{ } 0 11

La s theorem: consstency + stablty convergence The trdagonal equaton system, wth the unknownu a u 1 +b u +c u +1 = R = 2,...,m 1 has the followng form a 2 b 2 c 2 a 3 b 3 c 3......... u 1 u 2. = R 2 R 3. a m 1 b m 1 c m 1 u m R m 1 (m 2) equatons wth m unknown varables two boundary condtons have to be gven. Ths trdagonal system of equatons can be solved wth the followng recursve soluton approach (Thomas algorthm): wth E = u = E u +1 +F c a E 1 +b and F = R a F 1 a E 1 +b The ntal values fore 1 andf 1 follow from e.g. a Neumann boundary condton foruat = 1 u 1 = r 1 u 2 +s 1 = E 1 u 2 +F 1 E 1 = r 1 F 1 = s 1 After all coeffcentse,f are computed, the soluton foru s obtaned by back substtuton: u = E u +1 +F 12