Application of Genetic Algorithms to Problems in Computational Fluid Dynamics
Fabritius, Björn
Date: 12 February 2014
Publisher
University of Exeter
Degree Title
PhD in Engineering
Abstract
In this thesis a methodology is presented to optimise non–linear mathematical
models in numerical engineering applications. The method is based on biological
evolution and uses known concepts of genetic algorithms and evolutionary compu-
tation. The working principle is explained in detail, the implementation is outlined
and ...
In this thesis a methodology is presented to optimise non–linear mathematical
models in numerical engineering applications. The method is based on biological
evolution and uses known concepts of genetic algorithms and evolutionary compu-
tation. The working principle is explained in detail, the implementation is outlined
and alternative approaches are mentioned. The optimisation is then tested on a
series of benchmark cases to prove its validity. It is then applied to two different
types of problems in computational engineering.
The first application is the mathematical modeling of turbulence. An overview
of existing turbulence models is followed by a series of tests of different models
applied to various types of flows. In this thesis the optimisation method is used to
find improved coefficient values for the k–ε, the k–ω-SST and the Spalart–Allmaras
models. In a second application optimisation is used to improve the quality of a
computational mesh automatically generated by a third party software tool. This
generation can be controlled by a set of parameters, which are subject to the
optimisation.
The results obtained in this work show an improvement when compared to
non–optimised results. While computationally expensive, the genetic optimisation
method can still be used in engineering applications to tune predefined settings
with the aim to produce results of higher quality. The implementation is modular
and allows for further extensions and modifications for future applications.
Doctoral Theses
Doctoral College
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