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Computational Fluid Dynamics

  1. Anja R. Paschedag

Published Online: 15 JAN 2005

DOI: 10.1002/14356007.i07_i01

Ullmann's Encyclopedia of Industrial Chemistry

Ullmann's Encyclopedia of Industrial Chemistry

How to Cite

Paschedag, A. R. 2005. Computational Fluid Dynamics. Ullmann's Encyclopedia of Industrial Chemistry. .

Author Information

  1. University of Technology Berlin, Berlin, Germany

Publication History

  1. Published Online: 15 JAN 2005

Abstract

The article contains sections titled:

1.Introduction
2.Procedure
3.Modeling
3.1.Transport Equations
3.2.Initial and Boundary Conditions
3.3.Turbulent Flow
3.4.Multiphase Approaches
4.Numerics
4.1.Basics
4.2.Finite Volume Method
4.3.Pressure Correction Methods
4.4.Lattice Boltzmann Method
5.Interpretation
6.Industrial Application

Computational Fluid Dynamics (CFD) is a numerically based tool for the prediction of flow field, concentration and temperature distribution. Its main parts are mathematical modeling, discretization, numerical solution of the discretized equations and the interpretation of numerical results.

Basic equations in all mathematical models for CFD are balances for momentum and total mass determining velocity, pressure and density field. Depending on the case considered they are supplemented by mass balances for single species and a heat balance. Additional models are required to describe, e.g. turbulence, multiphase flows, chemically reactive systems and other special cases.

Basis for the discretization of the balance equation is the discretization of a space — the grid generation. Most codes can handle unstructured grids. Nevertheless, certain requirements concerning grid structure have to be fulfilled to get stable convergence and an accurate solution. Traditionally, most CFD codes use finite volume discretization for the balance equations, even if finite element algorithms are of increasing relevance for simulations with adaptively moving grids and for coupling CFD with structural dynamics simulations. A new approach for simulations with high resolution in space and time is the lattice Boltzmann method.

Finally, the numerical results have to be graphically presented and interpreted. Because of the huge amount of numerical data provided by each simulation this cannot be done with a general method. It must always be analysed in reference to a certain research question. Errors caused by the model formulation and by the numerical scheme have to be analyzed in order to judge the accuracy of a simulation. Quantitative estimates are required for an adequate interpretation of the results.