Thomas Algorithm for Tridiagonal Systems
|
|
- Laurence Stanley
- 5 years ago
- Views:
Transcription
1 Appendix Thomas Algorithm for Tridiagonal Systems A.I SALAR TRIDIAGONAL SYSTEMS For tridiagonal systems the LV decomposition method leads to an efficient algorithm, known as Thomas's algorithm. For a system of the form with akxk-l+bkxk+kxk+i=!k k=i,...,n (A.I) al = N = 0 (A.2) the following algorithm is obtained. Forward step {31=bl {3k=bk-ak- {3k-1 k-1 k=2,...,n 'YI-{31 -A 'Yk- _(-ak'yk-i+!k) {3k k - 2,..., N (A.3) Backward step XN = 'YN Xk='Yk-Xk+l~ k k=n-i,...,1 (A.4) This requires, in total, 5N operations. It can be shown that the above algorithm will always converge if the tridiagonal system is diagonal dominant, that is, if Ibkl~lakl+lckl Ibll>lcllandlbNI>laNI k=2,...,n-i (A.5) If a, b, are matrices we have a block-tridiagonal system, and the same algorithm can be applied. Due to the importance of triadiagonal system, we 505
2 506 present here a subroutine which can be used for an arbitrary scalar tridiagonal system. Subroutine TRIDAG SUBROUTINE TRIDAG (AA,BB,,FF,N1,N) ********************************************************************* SOLUTION OF A TRIDIAGONAL SYSTEM OF N-N1+1 EQUATIONS OF THE FORM AA(K)*X(K-1) + BB(K)*X(K) + (K)*X(K+1) = FF(K) K=N1,...,N K RANGING FROM N1 TO N THE SOLUTION X(K) IS STORED IN FF(K) AA (N1) AND (N) ARE NOT USED AA,BB,,FF ARE VETORS WITH DIMENSION N, TO BE SPEIFIED IN THE ALLING PROGRAM ********************************************************************* DIMENSION BB(N1)=1./BB(N1) AA(N1)=FF(N1)*BB(N1) N2=N1+1 N1N-N1+N DO 10 K-N2,N K1=K-1 (K1)=(K1)*BB(K1) BB(K) BB(K) AA(l),BB(l),(l),FF(l) =BB(K)-AA(K)*(K1) =l./bb(k) AA(K) =(FF(K)-AA(K)*AA(K1»*BB(K) 10 ONTINUE BAK SUBSTITUTION FF(N)-AA(N) DO 20 K1=N2,N K=N1N-K1 FF(K)-AA(K)-(K)*FF(K+1) 20 ONTINUE RETURN END A.2 PERIODI TRIDIAGONAL SYSTEMS For periodic boundary conditions, and a tridiagonal matrix with one in the extreme corners as in equation ( ), the above method does not apply. The following approach leads to an algorithm whereby two tridiagonal systems have to be solved. If the periodic matrix Bp( ii, E, c) has (N + 1) lines and columns resulting from a periodicity between points 1 and N + 2, the solution X is written as a linear combination X= X(I) + XN+IX(2), or Xk = xkl) + Xk2). XN+ I (A.6)
3 507 where xkl) and xk2) are solutions of the tridiagonal systems obtained by removing the last line and last column of Bp, containing the periodic elements. If this matrix is called B(N)(a, E, c) we solve successively, where the right-hand side terms Ik are put in a vector F: B(N)(a, E, )X(I) = F (A.7) and with B(N)(a, E, )X(2) = G (A.8) GT=(-OI,...,O, -N) (A.9) The last unknown XN+ I is obtained from the last equation by backsubstitution: I" (I) 0) _IN+I-N+IXr -ON+IXN (AIO) XN+ I - L. -..(2). -..(2). bn+i + ON+IXN + N+IXr The periodicity condition determines XN + 2 as Xn+2 = XI (A.II) The svbroutine TRIPER, based on this algorithm is included here. Note that if the periodicity condition is XN+2 = XI + (A.12) then the periodicity constant has to be added to the right-hand side of the last instruction, defining FF(N + 2). Subroutine TRIPER SUBROUTINE TRIPER(AA,BB,,FF,Nl,N,GAM2) ********************************************************************* SOLUTION OF A TRIDIAGONAL SYSTEM OF EQUATIONS WITH PERIODIITY IN THE POINTS K-Nl AND K~N+2 AA(K)*X(K-l) + BB(K)*X(K) + (K)*X(K+l) = FF(K) K=Nl,...,N+l THE ELEMENT IN THE UPPER RIGHT ORNER IS STORED IN AA(Nl) THE ELEMENT IN THE LOWER LEFT ORNER IS STORED IN (N+l) AA,BB,,FF,GAM2 ARE VETORS WITH DIMENSION N+2, TO BE SPEIFIED IN THE ALLING PROGRAM GAM2 IS AN AUXILIARY VETOR NEEDED FOR STORAGE THE SOLUTION IS STORED IN FF ********************************************************************* DIMENSION AA(1),BB(1),(1),FF(1),GAM2(1) BB(Nl)=l./BB(Nl) GAM2 (Nl)=-AA(Nl) AA(Nl)=FF(Nl)*BB(Nl) *BB(Nl)
4 508 N2=N1+1 N1N=N1+N DO 10 K=N2,N K1-K-1 (K1)=(K1)*BB(K1) BB(K) =BB(K)-AA(K)*(K1) BB(K) =l./bb(k) GAM2 (K)=-AA(K) *GAM2 (K1)*BB(K) AA(K) =(FF(K)-AA(K)*AA(K1»*BB(K) 10 ONTINUE GAM2 (N)=GAM2(N)-(N) *BB(N) BAK SUBSTITUTION FF(N)=AA(N) BB(N)=GAM2(N) DO 20 K1=N2,N K=N1N-K1.'- K2=K+1 FF(K)-AA(K)-(K)*FF(K2) BB(K)=GAM2 (K)-(K) *BB(K2) 20 ONTINUE K1=N+1 ZAA=FF(K1)-(K1) *FF(N1)-AA(K1) *FF(N) ZAA=ZAA/(BB(K1)+AA(K1) *BB(N)+(K1) *BB(N1» FF(K1)=ZAA DO 30 K=N1,N FF(K)=FF(K)+BB(K)*ZAA 30 ONTINUE FF(N+2)=FF(N1) RETURN END
5 Index Accuracy 161, 166, 265, 274, 275 Brailowskaya method 433 order of accuracy 161, 164, 198,219, Briley and McDonald method ,276,278,342,346,354, Burger's equation 269, 326, 327, 360, 356, ,364,365,436,437 ADl method 424, 437, 439, 440, 442, 457, 481 auchy problem 153, 409 Algebriac system 161, 163,421,456, ebeci-smith model 50, 51, 56c~\\-c~..\-nd fw~."..i\i 500 entrifugal force 17 14"f, 24- Aliasing phenomenon 325 haracteristic direction Amplification factor of numerical normal scheme 287, 296, 336, 375, 379, polynomial 377, 391, 393, 394, 425, 401,402,409, ,428,432,446 of differential equation 301, 343, 346, speed ,375 surface Amplification matrix 296, 336 irculation of iterative method 463, 464, 466, ircular cylinder, flow over ,470,471,478 lebsch representation Amplitude error 303, 353, 380, 444 ollocation 203, 223 Approximate factorization (see ompact differencing formula Factorization) ompatibility relations (equations) Approximation level (see Level of approximation) ondition number 373, 479 Artificial dissipation (viscosity) 324, 326, onditional stability 274, , 397, 398, 399 onditioning operator (see onvergence A-stability 423, 427, 429 operator) Averaging procedures for turbulent flow onforming element 205 (see Turbulent flow) onjugate gradient method 457, 484 onservation form 13, 19,88,108,139, Banded matrix , 238 Beam and Warming scheme 359, 360, onservation law 8, 12, 221, 223, 237, 426,430,431,436, Boundary conditions 153, 156, 267, 268, differential form ,409,410,412,413,442 for mass 12 Dirichlet 155,406,442,447,448,458, for momentum 14,15,16, for energy 18,24,111 Neumann 155, 381, 383, 385, 457 general form 10, 13 periodic 370, 376, 382, 385, 388, 393, integral form scalar 9 Boundary layer approximation 63, 64, vector 11 75, 78, 79 onservative discretization (scheme) Boundary-layer equations 154,
6 510 onservative discretization (scheme) Discretization error 248, 265, , (cont.) 301 variables 29,88 operator 290, 296 onsistency (condition) 267,275,276, Dispersion error 303,317,344,346, 277,278,345,348,350,351,356, 353,354,360,364,380, , 362, 363, 376, 379, 425, 445 Dispersion relation ontact discontinuity 89, 90 exact 152, 302 ontinuity equation 108 numerical 302, 318 ontrol-volume 237, 241, 253 Displacement operator 171 onvection-diffusion equation 268, Dissipation (viscous) , 270, 322, 329, 331, 334, 336, Dissipation error (see Diffusion error) 403, 409, 411 numerical (see Numerical dissipation) onvection equation 267, 270, 272, 289, Dissipation in the sense of Kreiss 324, 303,305,319,321,342,347,351, 352,375,379,380,382,386,392, 325,354,360 Dissipative scheme 324, 325, ,394,395,400,405,411,412, Distributed loss model , 429, 430, 433, 435, 442, 443, friction force 82, , 481 Divergence form 13 onvergence (condition) 162, 166, 275, Domain of dependence 143, Douglas and Rachford method 439 of iterative method 457, Du Fort and Frankel scheme 313,314, matrix (operator) 462, 478, 485, rate , 468, 480 oriolis force 16 ourant-friedrichs-lewy (FL) Elliptic equation 133, ,269, condition 287, 288, 289, 305, 353, 300,301,421, ,394,405,433,434,448 Energy (conservation) equation 19, III, ourant number 272, 288, 308, 314, ,319,326,327,328,360,364, Enthalpy 19, , 448 stagnation (total) enthalpy 19, 32, ran4k-nic 0Ison method 426, 429, 109, ,440 Entropy 20,21,31-33,108,110, III rocco's equation 21, 24, 82, 88 condition 92, 120 urved duct 72 equation 20, 83, 85, 88 inequality 92 Damping 305,317,323,346,389,444, production ,467,468,470,480,488,489, Equation discretization 161, f Equation of state 32 Delta form 436, 439 Equivalence Theorem of Lax 281, 401 Diagonal dominance 194, 472 Equivalent differential equation 265, Diffusion error 303, 316, 317, 344, 346, 277,278, , , 430 Error analysis for hyperbolic problems Diffusion equation 268,291,303,314, , ,330,343,380,382,385,392, for parabolic problems , 395, 405, 429, 437, 440,,448 Error of iterative scheme 462, 463, 465, Diffusion phenomena 133, 135, 268, , 406 Error of numerical scheme 283, 284, Direct method 163,456,463, ,412,413,415 Dirichlet boundary condition (see high-frequency 304, 310, 313, 316, Boundary condition) 319, 325, 326, 354, 430, 449, Discontinuities 13, 88, 92, 111,311, 467,468, ,316,317,365 low-frequency 304,316,318,325, Discrete Fourier transform , 467, 468,
7 Euler equations 15, 87-99, 111, 125, Gauss and Seidel point iteration 460, 128,240,298,386,397,423,429, 437, 447, 448, ,462,464,466,468,469,471, 473, 486 Euler explicit method 271, 289, 298, line iteration ,388, ,395,403,413, Gaussian quadrature , 429, 433, 478, 481 Generating polynomial 425, 426 Euler implicit method 271, 289, 379, Godunov and Ryabenkii condition ,394,429,439 Group velocity 152, , 327, 409 EVP method 301 (', Expansion shock 91 Heat conduction equation 268 i Explicit method (scheme) 162,271, 376, Heat sources , 431, 432 Helmholtz equation 16, 44 Henn's method 433, 446 \\ Factorization 424, 439, 440 Hermitian elements 205, Fick's law 133 schemes 181, 183 Finite difference method , 319, Horizontal line relaxation , 383 Hybrid equations 140, 154 Finite difference operators 168, 171, Hyperbolic equation (problem) 133, 172,174, averaging operator ,267,270,303,305,322, 323, ,386,387,409,421, backward difference 168, 172, 448, ,271,389,394 non-linear central difference 168,172, , 331, 336, 343, 374, 378, 388, III-posed problem ,392,395,403,423,429,433 Implicit difference formulas 171, forward difference 168,172, , ,272, 389, 391 Implicit method 162, 163, 376, 423, for mixed derivatives ,437 on non-uniform mesh Implicit scheme 271, 279, 280, 412 Finite element method 125, 190,201, Incomplete holeski factorization ,382,459,484 Incompressible fluid 44,45,106,127 Finite volume method 223, 224, 237, Initial (boundary) value problem ,283,301,370,371.,386 Five-point formula for Laplace equation Integral formulation ,301,457 Internal energy 20 Flux 9, 10, 29, , 360, 436 Internal flows convective 9, 11, 18 Interior scheme 387, 403, 409 diffusive 9, 11, 18 Interpolation functions 203, Fourier analysis (decomposition) Inviscid flow 84, 100, ,290,320,375,385 Inviscid pressure field harmonics 285,290,315,323,344, Irregular mesh Irrotational flows 108, 109, 120 of iterative scheme Isentropic condition Fourier's law 18 potential equation Fractional-step method 438, 439, 444 shock Friction force 83, 84 Isoparametric transformaticjp (mapping) Fromm's scheme , 227 Iterative method (scheme) 163;412, Galerkin method 190, 218, , \ Galerkin and Bubnow method 218 Galerkin and Petrov method 218, 222 Jacobi point iterative method 412, Gas constant , 464, 466, 467, 469, 472, Gauss points
8 512 Jacobi point iterative method (cont.) Multistep method , line relaxation 475, 476, 487, 488 Jacobian matrix 139, 150, 436, 485 Navier-Stokes equations 15,29-48,63, of flux vector 139, ,154,424,428,433,435,488 of isoparametric transformation Neumann boundary condition (see Boundary condition) Kutta-Joukowski condition , Newton method 435, Newtonian fluid 14, 15, 16,31, Nine-point formula for Laplace Lagrangian elements , equation 190, 191 Non-conservative form (scheme) 15, Laminar flow 45, 71, , 239 Laplace's equation ,219,301, Non-dimensional form of equations 437,471,472,479,486,487,490 Lax equivalence theorem ,134 ( Non-linear error terms 343, Lax-Friedrichs scheme 299,306,315, instability 326,327,328,397, ,324,333,348,349,352,354, Non-uniform mesh , 244, Non-uniqueness of potential flow Lax-Wendroff scheme ,314, ,317,325,348,354,355,357, of viscous flow , 364, 435 Normal matrix 297, 321, 401 Leapfrog scheme , , Normal mode representation 266, 326,336,347,348,357,366,374, ,388,390,393,395,413,423 Levels of approximation 133, 135, 161 Nozzle Numerical boundary condition 265, 319 dynamical level 5, 26 Numerical dissipation 307, 324, 326, spatial level 4 329, 346, 347, 358, 360, 364, 365, steadiness level 4 366,379,389,390,397,431,443, Linearization 431, Linearized potential flow 127 Numerical domain of dependence 289 Local mode analysis 375 Numerical flux 241, 361, 364 Mach angle 148 Numerical viscosity 277, 346, 352, 353, 358, 363, 364 Mach line 137 Mach number 32,35,44,51,56,67, Odd-even decoupling (oscillations) 189 6?, 81, 95, 97, ,137 Order of accuracy 161,167,197,219, Mappmg 2~6 Mass lump!ng , , 343, 346, 351, 356, 360 Mass. matnx Ordinary differential equations Matnx form (of dlscretlzed equations) Oscillations 311, 406, , 290 non-linear , 365 method 265, Overrelaxation Mcormack's met~od 433, 434, 437 Gauss-Seidel Mesh Reynolds (Peclet) number 334, Jacobi ~, 410, 411 successive point (SOR) 471,473,487 Method of lines 271 successive line 474 Mixed derivatives symmetric Modal equation 374, 425, 432 Momentum conservation Momentum equation 108, 112 Panel method 128 Monotone scheme 357 Parabolic equation (problem) 133, 154, Multigrid method 163, 422, 457, 467, 267, 268, 270, 303, 304, 320, 322, ,421,437
9 513 Parabolized Navier-Stokes equations Rothalpy 21, 24, 85, 100 (PNS) 70-75, 421 Round-off error 284, 411 Peaceman-Rachford method 441 Runge-Kutta method 413, 424, Peclet number 268 Perfect gas 31-33, 103 Secondary flows 74 Periodic boundary conditions (see Shallow-water equations 141, 150,291, Boundary condition) 298 Phase angle 286,316 Shear stress 14,18 Phase error (see Dispersion error) Shock 35, 44, 51, 69189, 90, 91, lagging 305, 308, 316, 317, 360, ,240,318,326 leading 305, 307, 353, 360 normal shock Phase velocity 149, 153, 303, 318, 319 Singularity method 127 Physical boundary condition Slip lines 91 Poisson equation , 466, 488 Small disturbance approximation 126, for pressure ,147 Potential flow , 137, 155, 269, Sonic velocity 33, , 482 Space discretization 161 Potential shocks eigenvalues of 371,373,377,488 Prandtl number 19 operator 290, , 425, 436, 456, Preconditioning 163, 374, 422, 457, spectrum of , 488 Predictor-corrector method , stability of 373, Space marching 412 Pressure correction method 73 Spacelike variables Principal root 379 Specific heat, ratio of 18, 32, 103 Propagatidh phenomena 134, 386 Spectral analysis of numerical errors Pseudo-unsteady formulation 162, ,422 radius 296, 297, 321, 400, 402, 406, Quasi-linear differential equations 133, 408, 413, 463, 468, 469, 472, Spectrum (of a difference operator) Quasi-three-dimensional approximation (see Levels of approximation) for convection equation for diffusion equation 378, 380, 385, Rankine-Hugoniot relations 89-93, , 123, 240 of iterative method Relaxation method 457, 488 Speed of sound (see Sonic velocity) equivalent differential equation Spline methods Spurious solution (root) 314, 379 parameter 471,479,482 red-black 476, 492 Stability (condition) 162, 166,265,275, 277, ,287,342,343,345, smoothing properties ,356,357,375,376,377, zebra 477,478, ,400,402,403,423,425, Residual 216, 278, 461, 462, ,429,432,446 Reynolds-averaged Navier-Stokes for convection-diffusion equation equations 48, , Reynolds number 45,75,87, 134,268, for hyperbolic problems , Reynolds stress 50 of iterative method 478 Richardson's method 479, 482 from matrix method , Rotary stagnation pressure 106, Rotating frame of reference 16-18, 82, for multi-dimensional problems Rotational flow 24, neutral 313,326
10 514 Stability (condition) (cont.) Transonic flow , 137, 240, 270, for non-linear problems for parabolic problems 303, 320, Transport equation 268, Trapezoidal method 426, 428, 430 from Von Neumann method , Tridiagonal system 182, 183, 271, 346,351,352,355,356,359, 370,375,385,392, ,430,431,437,441,460 eigenvalues of Stagnation enthalpy (see Enthalpy) Truncation error 174, 175, , Stagnation pressure 33,103, ,240,265, ,342,343, Stagnation temperature ,351,352,361,362,390,464 Steady-state (stationary) formulation 70, Turbulence models 51 84, 373, , 421, 424, 444, Turbulent flow 47, 48, 50-62, 73, , 479 Two-level schemes (general form) inviscid flows , , 375,400, potential flow ,431 Stiffness matrix 218, 484 Stokes Streamline equation 108, Unconditional instability 287 ' 393, 405, Strongl~ implicit procedure (SIP) 483 stabili~y 289, 314, 345, 413, 423, 428, Subsonic flow 120, 137, 155, 270, Successive overrelaxation (SOR) (see Unstable s~heme 272 Supercrit~cal Overrelaxation) airfoil 119 Upwind 351,354,358,386,389,392,395, scheme ' Supersonic flow 137, 270, Sutherland's formula 31 Variational principle (formulation) 204, Taylor expansion , 174, 183, ' 361' 379' 425' 426' 432', Vertical line relaxation 476, 488 Viscid-inviscid interaction 78 Test fu~ctio~s 217 " Viscosity, coefficient of 14, 15,31 Thermal conductivity, coefficient of 19, Viscous-inviscid interaction 27,87 31 Von Neumann method 265, , Thermal diffusivity ,351,355,356,359,370,375, Thin-shear layer approximation 27, 385, 392, 393, 401, 402, , Thomas al~ori~hm 457, ,413,422,434,441,468 Von Neumann polynomial Three-level schemes ' 378, 379, Vortex Vortex sheet singularity 89, Through-flo~ 84 ' Vorticity equation 15, 44, 93 Time-dependent (equation) approach vector 15, 18, 24, 88, 100, 102, ,270,373,412,421,423,456, 464. WarmIng and Beam scheme (see Beam Time-integration method 370, 374, 413, and Warming scheme) 456 stability of , , 413, Wave equation 270, 291, 300, 314, Wave-front 135,136,140,146 Time-like variable ,421 Wave-length 285, 286 Time-marching method 162 Wave-like solutions 135, 136, , Total energy Total enthalpy (see Enthalpy) Wave-number , 285, Transient solution 373,374,376,377, vector , 466 Wave packet , 360
11 Wave (phase) speed 149, 299, 305 Well-posed problem (in the sense of Weak formulation 204, 217, 221 Hadamard) 152, 343, 372, 377, Weak instability , 394, 486 Weak solution 241 Weighted residual method 204, Zone of dependence J,:;:zi~1 ~ ",.-, "",.. r j,'*; ;~' -"
12
NUMERICAL METHODS FOR ENGINEERING APPLICATION
NUMERICAL METHODS FOR ENGINEERING APPLICATION Second Edition JOEL H. FERZIGER A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York / Chichester / Weinheim / Brisbane / Singapore / Toronto
More informationAppendix A Computer Programs on the Accompanying CD-ROM
Appendix A Computer Programs on the Accompanying CD-ROM The CD-ROM accompanying this book contains both source and executable computer programs and test cases. They are listed below. Prior to running the
More informationIndex. higher order methods, 52 nonlinear, 36 with variable coefficients, 34 Burgers equation, 234 BVP, see boundary value problems
Index A-conjugate directions, 83 A-stability, 171 A( )-stability, 171 absolute error, 243 absolute stability, 149 for systems of equations, 154 absorbing boundary conditions, 228 Adams Bashforth methods,
More informationFluid Dynamics: Theory, Computation, and Numerical Simulation Second Edition
Fluid Dynamics: Theory, Computation, and Numerical Simulation Second Edition C. Pozrikidis m Springer Contents Preface v 1 Introduction to Kinematics 1 1.1 Fluids and solids 1 1.2 Fluid parcels and flow
More informationA THEORETICAL INTRODUCTION TO NUMERICAL ANALYSIS
A THEORETICAL INTRODUCTION TO NUMERICAL ANALYSIS Victor S. Ryaben'kii Semyon V. Tsynkov Chapman &. Hall/CRC Taylor & Francis Group Boca Raton London New York Chapman & Hall/CRC is an imprint of the Taylor
More informationPartial Differential Equations
Partial Differential Equations Introduction Deng Li Discretization Methods Chunfang Chen, Danny Thorne, Adam Zornes CS521 Feb.,7, 2006 What do You Stand For? A PDE is a Partial Differential Equation This
More informationNumerical Solution of partial differential equations
G. D. SMITH Brunei University Numerical Solution of partial differential equations FINITE DIFFERENCE METHODS THIRD EDITION CLARENDON PRESS OXFORD Contents NOTATION 1. INTRODUCTION AND FINITE-DIFFERENCE
More informationFundamentals of Aerodynamics
Fundamentals of Aerodynamics Fourth Edition John D. Anderson, Jr. Curator of Aerodynamics National Air and Space Museum Smithsonian Institution and Professor Emeritus University of Maryland Me Graw Hill
More informationME 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 informationDetailed Outline, M E 521: Foundations of Fluid Mechanics I
Detailed Outline, M E 521: Foundations of Fluid Mechanics I I. Introduction and Review A. Notation 1. Vectors 2. Second-order tensors 3. Volume vs. velocity 4. Del operator B. Chapter 1: Review of Basic
More informationCHAPTER 7 SEVERAL FORMS OF THE EQUATIONS OF MOTION
CHAPTER 7 SEVERAL FORMS OF THE EQUATIONS OF MOTION 7.1 THE NAVIER-STOKES EQUATIONS Under the assumption of a Newtonian stress-rate-of-strain constitutive equation and a linear, thermally conductive medium,
More informationFundamentals of Aerodynamits
Fundamentals of Aerodynamits Fifth Edition in SI Units John D. Anderson, Jr. Curator of Aerodynamics National Air and Space Museum Smithsonian Institution and Professor Emeritus University of Maryland
More informationIntroduction. Finite and Spectral Element Methods Using MATLAB. Second Edition. C. Pozrikidis. University of Massachusetts Amherst, USA
Introduction to Finite and Spectral Element Methods Using MATLAB Second Edition C. Pozrikidis University of Massachusetts Amherst, USA (g) CRC Press Taylor & Francis Group Boca Raton London New York CRC
More informationNumerical Cornp u tat ion
Numerical Cornp u tat ion n INTERNAL AND EXTERNAL FLOWS Volume 1 : Fundamentals of Numerical Discretization Charles Hirsch Department of Fluid Mechanics, Vrije Universiteit Brussel, Brussels, Belgium A
More informationNumerical Solutions for Hyperbolic Systems of Conservation Laws: from Godunov Method to Adaptive Mesh Refinement
Numerical Solutions for Hyperbolic Systems of Conservation Laws: from Godunov Method to Adaptive Mesh Refinement Romain Teyssier CEA Saclay Romain Teyssier 1 Outline - Euler equations, MHD, waves, hyperbolic
More informationPartial differential equations
Partial differential equations Many problems in science involve the evolution of quantities not only in time but also in space (this is the most common situation)! We will call partial differential equation
More informationNUMERICAL COMPUTATION IN SCIENCE AND ENGINEERING
NUMERICAL COMPUTATION IN SCIENCE AND ENGINEERING C. Pozrikidis University of California, San Diego New York Oxford OXFORD UNIVERSITY PRESS 1998 CONTENTS Preface ix Pseudocode Language Commands xi 1 Numerical
More informationImplicit Solution of Viscous Aerodynamic Flows using the Discontinuous Galerkin Method
Implicit Solution of Viscous Aerodynamic Flows using the Discontinuous Galerkin Method Per-Olof Persson and Jaime Peraire Massachusetts Institute of Technology 7th World Congress on Computational Mechanics
More informationBoundary-Layer Theory
Hermann Schlichting Klaus Gersten Boundary-Layer Theory With contributions from Egon Krause and Herbert Oertel Jr. Translated by Katherine Mayes 8th Revised and Enlarged Edition With 287 Figures and 22
More informationPDE Solvers for Fluid Flow
PDE Solvers for Fluid Flow issues and algorithms for the Streaming Supercomputer Eran Guendelman February 5, 2002 Topics Equations for incompressible fluid flow 3 model PDEs: Hyperbolic, Elliptic, Parabolic
More informationIndex. C 2 ( ), 447 C k [a,b], 37 C0 ( ), 618 ( ), 447 CD 2 CN 2
Index advection equation, 29 in three dimensions, 446 advection-diffusion equation, 31 aluminum, 200 angle between two vectors, 58 area integral, 439 automatic step control, 119 back substitution, 604
More informationHigh Speed Aerodynamics. Copyright 2009 Narayanan Komerath
Welcome to High Speed Aerodynamics 1 Lift, drag and pitching moment? Linearized Potential Flow Transformations Compressible Boundary Layer WHAT IS HIGH SPEED AERODYNAMICS? Airfoil section? Thin airfoil
More informationComputation Fluid Dynamics
Computation Fluid Dynamics CFD I Jitesh Gajjar Maths Dept Manchester University Computation Fluid Dynamics p.1/189 Garbage In, Garbage Out We will begin with a discussion of errors. Useful to understand
More informationPreface. 2 Linear Equations and Eigenvalue Problem 22
Contents Preface xv 1 Errors in Computation 1 1.1 Introduction 1 1.2 Floating Point Representation of Number 1 1.3 Binary Numbers 2 1.3.1 Binary number representation in computer 3 1.4 Significant Digits
More information2.29 Numerical Fluid Mechanics Spring 2015 Lecture 9
Spring 2015 Lecture 9 REVIEW Lecture 8: Direct Methods for solving (linear) algebraic equations Gauss Elimination LU decomposition/factorization Error Analysis for Linear Systems and Condition Numbers
More informationNumerical Methods for Engineers and Scientists
Numerical Methods for Engineers and Scientists Second Edition Revised and Expanded Joe D. Hoffman Department of Mechanical Engineering Purdue University West Lafayette, Indiana m MARCEL D E К К E R MARCEL
More informationNumerical Mathematics
Alfio Quarteroni Riccardo Sacco Fausto Saleri Numerical Mathematics Second Edition With 135 Figures and 45 Tables 421 Springer Contents Part I Getting Started 1 Foundations of Matrix Analysis 3 1.1 Vector
More informationComputational Fluid Dynamics
Computational Fluid Dynamics Dr.Eng. Reima Iwatsu Phone: 0355 69 4875 e-mail: iwatsu@las.tu-cottbus.de NACO Building Room 53-107 Time Summer Term Lecture: Tuesday 7:30-9:00 (every two weeks) LG4/310 Exercise:
More informationNumerical Methods for Problems with Moving Fronts Orthogonal Collocation on Finite Elements
Electronic Text Provided with the Book Numerical Methods for Problems with Moving Fronts by Bruce A. Finlayson Ravenna Park Publishing, Inc., 635 22nd Ave. N. E., Seattle, WA 985-699 26-524-3375; ravenna@halcyon.com;www.halcyon.com/ravenna
More informationAA214B: NUMERICAL METHODS FOR COMPRESSIBLE FLOWS
AA214B: NUMERICAL METHODS FOR COMPRESSIBLE FLOWS 1 / 29 AA214B: NUMERICAL METHODS FOR COMPRESSIBLE FLOWS Hierarchy of Mathematical Models 1 / 29 AA214B: NUMERICAL METHODS FOR COMPRESSIBLE FLOWS 2 / 29
More informationHow Many Steps are Required to Solve the Euler Equations of Steady, Compressible Flow: In Search of a Fast Solution Algorithm
AIAA 2 2673 How Many Steps are Required to Solve the Euler Equations of Steady, Compressible Flow: In Search of a Fast Solution Algorithm Antony Jameson Stanford University Stanford, CA 9435 D. A. Caughey
More informationFUNDAMENTALS OF AERODYNAMICS
*A \ FUNDAMENTALS OF AERODYNAMICS Second Edition John D. Anderson, Jr. Professor of Aerospace Engineering University of Maryland H ' McGraw-Hill, Inc. New York St. Louis San Francisco Auckland Bogota Caracas
More information1. Introduction, tensors, kinematics
1. Introduction, tensors, kinematics Content: Introduction to fluids, Cartesian tensors, vector algebra using tensor notation, operators in tensor form, Eulerian and Lagrangian description of scalar and
More informationDiffusion / 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 informationBack Matter Index The McGraw Hill Companies, 2004
INDEX A Absolute viscosity, 294 Active zone, 468 Adjoint, 452 Admissible functions, 132 Air, 294 ALGOR, 12 Amplitude, 389, 391 Amplitude ratio, 396 ANSYS, 12 Applications fluid mechanics, 293 326. See
More informationTime stepping methods
Time stepping methods ATHENS course: Introduction into Finite Elements Delft Institute of Applied Mathematics, TU Delft Matthias Möller (m.moller@tudelft.nl) 19 November 2014 M. Möller (DIAM@TUDelft) Time
More informationChapter 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 information3. FORMS OF GOVERNING EQUATIONS IN CFD
3. FORMS OF GOVERNING EQUATIONS IN CFD 3.1. Governing and model equations in CFD Fluid flows are governed by the Navier-Stokes equations (N-S), which simpler, inviscid, form is the Euler equations. For
More informationApplied Linear Algebra
Applied Linear Algebra Peter J. Olver School of Mathematics University of Minnesota Minneapolis, MN 55455 olver@math.umn.edu http://www.math.umn.edu/ olver Chehrzad Shakiban Department of Mathematics University
More informationSpace-time Discontinuous Galerkin Methods for Compressible Flows
Space-time Discontinuous Galerkin Methods for Compressible Flows Jaap van der Vegt Numerical Analysis and Computational Mechanics Group Department of Applied Mathematics University of Twente Joint Work
More informationComputational Fluid Dynamics-1(CFDI)
بسمه تعالی درس دینامیک سیالات محاسباتی 1 دوره کارشناسی ارشد دانشکده مهندسی مکانیک دانشگاه صنعتی خواجه نصیر الدین طوسی Computational Fluid Dynamics-1(CFDI) Course outlines: Part I A brief introduction to
More informationApplication of Dual Time Stepping to Fully Implicit Runge Kutta Schemes for Unsteady Flow Calculations
Application of Dual Time Stepping to Fully Implicit Runge Kutta Schemes for Unsteady Flow Calculations Antony Jameson Department of Aeronautics and Astronautics, Stanford University, Stanford, CA, 94305
More informationPartial Differential Equations
Partial Differential Equations Analytical Solution Techniques J. Kevorkian University of Washington Wadsworth & Brooks/Cole Advanced Books & Software Pacific Grove, California C H A P T E R 1 The Diffusion
More informationChapter 1: Basic Concepts
What is a fluid? A fluid is a substance in the gaseous or liquid form Distinction between solid and fluid? Solid: can resist an applied shear by deforming. Stress is proportional to strain Fluid: deforms
More informationIntroduction to Numerical Analysis
J. Stoer R. Bulirsch Introduction to Numerical Analysis Second Edition Translated by R. Bartels, W. Gautschi, and C. Witzgall With 35 Illustrations Springer Contents Preface to the Second Edition Preface
More informationNumerical Analysis. A Comprehensive Introduction. H. R. Schwarz University of Zürich Switzerland. with a contribution by
Numerical Analysis A Comprehensive Introduction H. R. Schwarz University of Zürich Switzerland with a contribution by J. Waldvogel Swiss Federal Institute of Technology, Zürich JOHN WILEY & SONS Chichester
More informationIntroduction to Aerodynamics. Dr. Guven Aerospace Engineer (P.hD)
Introduction to Aerodynamics Dr. Guven Aerospace Engineer (P.hD) Aerodynamic Forces All aerodynamic forces are generated wither through pressure distribution or a shear stress distribution on a body. The
More information1. Fluid Dynamics Around Airfoils
1. Fluid Dynamics Around Airfoils Two-dimensional flow around a streamlined shape Foces on an airfoil Distribution of pressue coefficient over an airfoil The variation of the lift coefficient with the
More informationAA210A Fundamentals of Compressible Flow. Chapter 5 -The conservation equations
AA210A Fundamentals of Compressible Flow Chapter 5 -The conservation equations 1 5.1 Leibniz rule for differentiation of integrals Differentiation under the integral sign. According to the fundamental
More informationApplied Numerical Analysis
Applied Numerical Analysis Using MATLAB Second Edition Laurene V. Fausett Texas A&M University-Commerce PEARSON Prentice Hall Upper Saddle River, NJ 07458 Contents Preface xi 1 Foundations 1 1.1 Introductory
More informationSeveral forms of the equations of motion
Chapter 6 Several forms of the equations of motion 6.1 The Navier-Stokes equations Under the assumption of a Newtonian stress-rate-of-strain constitutive equation and a linear, thermally conductive medium,
More informationBasic 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 informationDetailed Outline, M E 320 Fluid Flow, Spring Semester 2015
Detailed Outline, M E 320 Fluid Flow, Spring Semester 2015 I. Introduction (Chapters 1 and 2) A. What is Fluid Mechanics? 1. What is a fluid? 2. What is mechanics? B. Classification of Fluid Flows 1. Viscous
More informationChapter 5. The Differential Forms of the Fundamental Laws
Chapter 5 The Differential Forms of the Fundamental Laws 1 5.1 Introduction Two primary methods in deriving the differential forms of fundamental laws: Gauss s Theorem: Allows area integrals of the equations
More informationModeling Unsteady Flow in Turbomachinery Using a Harmonic Balance Technique
Modeling Unsteady Flow in Turbomachinery Using a Harmonic Balance Technique Torsten Palenschat 317220 30.04.2014 Master seminar CES WS 2013/2014 Center for Computational Engineering Sciences RWTH Aachen
More information2.29 Numerical Fluid Mechanics Fall 2011 Lecture 7
Numerical Fluid Mechanics Fall 2011 Lecture 7 REVIEW of Lecture 6 Material covered in class: Differential forms of conservation laws Material Derivative (substantial/total derivative) Conservation of Mass
More informationMULTIGRID CALCULATIONS FOB. CASCADES. Antony Jameson and Feng Liu Princeton University, Princeton, NJ 08544
MULTIGRID CALCULATIONS FOB. CASCADES Antony Jameson and Feng Liu Princeton University, Princeton, NJ 0544 1. Introduction Development of numerical methods for internal flows such as the flow in gas turbines
More informationMath 7824 Spring 2010 Numerical solution of partial differential equations Classroom notes and homework
Math 7824 Spring 2010 Numerical solution of partial differential equations Classroom notes and homework Jan Mandel University of Colorado Denver May 12, 2010 1/20/09: Sec. 1.1, 1.2. Hw 1 due 1/27: problems
More informationThe RAMSES code and related techniques I. Hydro solvers
The RAMSES code and related techniques I. Hydro solvers Outline - The Euler equations - Systems of conservation laws - The Riemann problem - The Godunov Method - Riemann solvers - 2D Godunov schemes -
More informationRiemann Solvers and Numerical Methods for Fluid Dynamics
Eleuterio R Toro Riemann Solvers and Numerical Methods for Fluid Dynamics A Practical Introduction With 223 Figures Springer Table of Contents Preface V 1. The Equations of Fluid Dynamics 1 1.1 The Euler
More informationComputation 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 informationContents. I Introduction 1. Preface. xiii
Contents Preface xiii I Introduction 1 1 Continuous matter 3 1.1 Molecules................................ 4 1.2 The continuum approximation.................... 6 1.3 Newtonian mechanics.........................
More information2.29 Numerical Fluid Mechanics Spring 2015 Lecture 13
REVIEW Lecture 12: Spring 2015 Lecture 13 Grid-Refinement and Error estimation Estimation of the order of convergence and of the discretization error Richardson s extrapolation and Iterative improvements
More informationTAU Solver Improvement [Implicit methods]
TAU Solver Improvement [Implicit methods] Richard Dwight Megadesign 23-24 May 2007 Folie 1 > Vortrag > Autor Outline Motivation (convergence acceleration to steady state, fast unsteady) Implicit methods
More informationAdvanced. Engineering Mathematics
Advanced Engineering Mathematics A new edition of Further Engineering Mathematics K. A. Stroud Formerly Principal Lecturer Department of Mathematics, Coventry University with additions by Dexter j. Booth
More informationProspects for High-Speed Flow Simulations
Prospects for High-Speed Flow Simulations Graham V. Candler Aerospace Engineering & Mechanics University of Minnesota Support from AFOSR and ASDR&E Future Directions in CFD Research: A Modeling & Simulation
More informationAn Efficient Low Memory Implicit DG Algorithm for Time Dependent Problems
An Efficient Low Memory Implicit DG Algorithm for Time Dependent Problems P.-O. Persson and J. Peraire Massachusetts Institute of Technology 2006 AIAA Aerospace Sciences Meeting, Reno, Nevada January 9,
More informationNumerical methods Revised March 2001
Revised March 00 By R. W. Riddaway (revised by M. Hortal) Table of contents. Some introductory ideas. Introduction. Classification of PDE's.3 Existence and uniqueness.4 Discretization.5 Convergence, consistency
More informationKINGS COLLEGE OF ENGINEERING DEPARTMENT OF MATHEMATICS ACADEMIC YEAR / EVEN SEMESTER QUESTION BANK
KINGS COLLEGE OF ENGINEERING MA5-NUMERICAL METHODS DEPARTMENT OF MATHEMATICS ACADEMIC YEAR 00-0 / EVEN SEMESTER QUESTION BANK SUBJECT NAME: NUMERICAL METHODS YEAR/SEM: II / IV UNIT - I SOLUTION OF EQUATIONS
More informationPEMP ACD2505. M.S. Ramaiah School of Advanced Studies, Bengaluru
Governing Equations of Fluid Flow Session delivered by: M. Sivapragasam 1 Session Objectives -- At the end of this session the delegate would have understood The principle of conservation laws Different
More informationA Bound-Preserving Fourth Order Compact Finite Difference Scheme for Scalar Convection Diffusion Equations
A Bound-Preserving Fourth Order Compact Finite Difference Scheme for Scalar Convection Diffusion Equations Hao Li Math Dept, Purdue Univeristy Ocean University of China, December, 2017 Joint work with
More informationContents. Preface to the Third Edition (2007) Preface to the Second Edition (1992) Preface to the First Edition (1985) License and Legal Information
Contents Preface to the Third Edition (2007) Preface to the Second Edition (1992) Preface to the First Edition (1985) License and Legal Information xi xiv xvii xix 1 Preliminaries 1 1.0 Introduction.............................
More information8. Introduction to Computational Fluid Dynamics
8. Introduction to Computational Fluid Dynamics We have been using the idea of distributions of singularities on surfaces to study the aerodynamics of airfoils and wings. This approach was very powerful,
More informationAdvection / Hyperbolic PDEs. PHY 604: Computational Methods in Physics and Astrophysics II
Advection / Hyperbolic PDEs Notes In addition to the slides and code examples, my notes on PDEs with the finite-volume method are up online: https://github.com/open-astrophysics-bookshelf/numerical_exercises
More informationIntroduction to Fluid Mechanics. Chapter 13 Compressible Flow. Fox, Pritchard, & McDonald
Introduction to Fluid Mechanics Chapter 13 Compressible Flow Main Topics Basic Equations for One-Dimensional Compressible Flow Isentropic Flow of an Ideal Gas Area Variation Flow in a Constant Area Duct
More informationSimulation of low Mach number flows
Simulation of low Mach number flows Improvement of accuracy and convergence of the TAU code using time derivative preconditioning Ralf Heinrich, Braunschweig, 9th February 008 Simulation of low Mach number
More informationIndex. Boundary integral method, 27 Boundary location method, 255 Brinkman number, 14, 158
Index ABFIND,275 Adaptive control, 304, 312 Adaptive process model, 315 Air drag, 221 Alternating Direction Implicit (ADI) technique, 30 Axisymmetric flow, 48 die entry, 58 Boundary integral method, 27
More informationFinite volume method on unstructured grids
Finite volume method on unstructured grids Praveen. C praveen@math.tifrbng.res.in Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore 560065 http://math.tifrbng.res.in/~praveen
More informationFinite Difference Method for PDE. Y V S S Sanyasiraju Professor, Department of Mathematics IIT Madras, Chennai 36
Finite Difference Method for PDE Y V S S Sanyasiraju Professor, Department of Mathematics IIT Madras, Chennai 36 1 Classification of the Partial Differential Equations Consider a scalar second order partial
More informationComputer Simulation Using Particles
Computer Simulation Using Particles R W Hockney Emeritus Professor, University ofreading and J W Eastwood Culham Laboratory, Abingdon Institute of Physics Publishing Bristol and Philadelphia CONTENTS Foreword
More information1. Introduction Some Basic Concepts
1. Introduction Some Basic Concepts 1.What is a fluid? A substance that will go on deforming in the presence of a deforming force, however small 2. What Properties Do Fluids Have? Density ( ) Pressure
More informationBASIC EXAM ADVANCED CALCULUS/LINEAR ALGEBRA
1 BASIC EXAM ADVANCED CALCULUS/LINEAR ALGEBRA This part of the Basic Exam covers topics at the undergraduate level, most of which might be encountered in courses here such as Math 233, 235, 425, 523, 545.
More informationIn which of the following scenarios is applying the following form of Bernoulli s equation: steady, inviscid, uniform stream of water. Ma = 0.
bernoulli_11 In which of the following scenarios is applying the following form of Bernoulli s equation: p V z constant! g + g + = from point 1 to point valid? a. 1 stagnant column of water steady, inviscid,
More informationPhysical Diffusion Cures the Carbuncle Phenomenon
Physical Diffusion Cures the Carbuncle Phenomenon J. M. Powers 1, J. Bruns 1, A. Jemcov 1 1 Department of Aerospace and Mechanical Engineering University of Notre Dame, USA Fifty-Third AIAA Aerospace Sciences
More informationChapter 10 Exercises
Chapter 10 Exercises From: Finite Difference Methods for Ordinary and Partial Differential Equations by R. J. LeVeque, SIAM, 2007. http://www.amath.washington.edu/ rl/fdmbook Exercise 10.1 (One-sided and
More informationFUNDAMENTALS OF FINITE DIFFERENCE METHODS
FUNDAMENTALS OF FINITE DIFFERENCE METHODS By Deep Gupta 3 rd Year undergraduate, Mechanical Engg. Deptt., IIT Bombay Supervised by: Prof. Gautam Biswas, IIT Kanpur Acknowledgements It has been a pleasure
More informationTopics in Fluid Dynamics: Classical physics and recent mathematics
Topics in Fluid Dynamics: Classical physics and recent mathematics Toan T. Nguyen 1,2 Penn State University Graduate Student Seminar @ PSU Jan 18th, 2018 1 Homepage: http://math.psu.edu/nguyen 2 Math blog:
More informationTyn Myint-U Lokenath Debnath. Linear Partial Differential Equations for Scientists and Engineers. Fourth Edition. Birkhauser Boston Basel Berlin
Tyn Myint-U Lokenath Debnath Linear Partial Differential Equations for Scientists and Engineers Fourth Edition Birkhauser Boston Basel Berlin Preface to the Fourth Edition Preface to the Third Edition
More informationChapter 2 Finite-Difference Discretization of the Advection-Diffusion Equation
Chapter Finite-Difference Discretization of the Advection-Diffusion Equation. Introduction Finite-difference methods are numerical methods that find solutions to differential equations using approximate
More informationCAM Ph.D. Qualifying Exam in Numerical Analysis CONTENTS
CAM Ph.D. Qualifying Exam in Numerical Analysis CONTENTS Preliminaries Round-off errors and computer arithmetic, algorithms and convergence Solutions of Equations in One Variable Bisection method, fixed-point
More informationSlip flow boundary conditions in discontinuous Galerkin discretizations of the Euler equations of gas dynamics
Slip flow boundary conditions in discontinuous Galerkin discretizations of the Euler equations of gas dynamics J.J.W. van der Vegt and H. van der Ven Nationaal Lucht- en Ruimtevaartlaboratorium National
More informationMETHODS FOR SOLVING MATHEMATICAL PHYSICS PROBLEMS
METHODS FOR SOLVING MATHEMATICAL PHYSICS PROBLEMS V.I. Agoshkov, P.B. Dubovski, V.P. Shutyaev CAMBRIDGE INTERNATIONAL SCIENCE PUBLISHING Contents PREFACE 1. MAIN PROBLEMS OF MATHEMATICAL PHYSICS 1 Main
More informationThe RAMSES code and related techniques 2- MHD solvers
The RAMSES code and related techniques 2- MHD solvers Outline - The ideal MHD equations - Godunov method for 1D MHD equations - Ideal MHD in multiple dimensions - Cell-centered variables: divergence B
More informationNumerical Methods for Engineers. and Scientists. Applications using MATLAB. An Introduction with. Vish- Subramaniam. Third Edition. Amos Gilat.
Numerical Methods for Engineers An Introduction with and Scientists Applications using MATLAB Third Edition Amos Gilat Vish- Subramaniam Department of Mechanical Engineering The Ohio State University Wiley
More informationShock Reflection-Diffraction, Nonlinear Conservation Laws of Mixed Type, and von Neumann s Conjectures 1
Contents Preface xi I Shock Reflection-Diffraction, Nonlinear Conservation Laws of Mixed Type, and von Neumann s Conjectures 1 1 Shock Reflection-Diffraction, Nonlinear Partial Differential Equations of
More informationProjection Dynamics in Godunov-Type Schemes
JOURNAL OF COMPUTATIONAL PHYSICS 142, 412 427 (1998) ARTICLE NO. CP985923 Projection Dynamics in Godunov-Type Schemes Kun Xu and Jishan Hu Department of Mathematics, Hong Kong University of Science and
More informationAeroacoustic and Aerodynamics of Swirling Flows*
Aeroacoustic and Aerodynamics of Swirling Flows* Hafiz M. Atassi University of Notre Dame * supported by ONR grant and OAIAC OVERVIEW OF PRESENTATION Disturbances in Swirling Flows Normal Mode Analysis
More informationV (r,t) = i ˆ u( x, y,z,t) + ˆ j v( x, y,z,t) + k ˆ w( x, y, z,t)
IV. DIFFERENTIAL RELATIONS FOR A FLUID PARTICLE This chapter presents the development and application of the basic differential equations of fluid motion. Simplifications in the general equations and common
More informationENO and WENO schemes. Further topics and time Integration
ENO and WENO schemes. Further topics and time Integration Tefa Kaisara CASA Seminar 29 November, 2006 Outline 1 Short review ENO/WENO 2 Further topics Subcell resolution Other building blocks 3 Time Integration
More informationModeling, Simulating and Rendering Fluids. Thanks to Ron Fediw et al, Jos Stam, Henrik Jensen, Ryan
Modeling, Simulating and Rendering Fluids Thanks to Ron Fediw et al, Jos Stam, Henrik Jensen, Ryan Applications Mostly Hollywood Shrek Antz Terminator 3 Many others Games Engineering Animating Fluids is
More information