The work develops the application of evolutionary algorithms in the domain of
automotive heat exchanger design. The principal employed is that of computer
regulated changes to a physical model which attempts optimisation using methods
analogous to biological evolution. It shows that the use of airside fins with differing
louvre angles can enhance the performance of automotive heat exchangers by a useful
margm.
This has been achieved with a wind tunnel model that allows automatic configuration
of the louvre angles, and novel instrumentation allowing heat transfer performance to
be assessed in terms of shear and drag forces acting on the louvres. During the
investigation an important coupling between the behaviour of adjacent louvres was
discovered, manifested as a loss in useful shear force at around ±12° relative angle.
The work as a whole shows that specific louvre angle selections and quantitative
estimates of the potential performance gains could be made with the following
improvements to the physical model and search algorithms. The number of louvre
rows should be doubled (to 16) to better represent typical matrices and the
instrumented louvres should be centrally positioned in the air stream. Improved data
filtering is required for reliable operation and the specific figure of merit has been
shown to be an important factor in the optimisation process.
A parallel area of application for the optimisation strategies was the solution of the
Wilson plot problem. This represents a novel approach to the analysis of heat
exchanger experimental test data where an alternative curve fitting and visualisation
format allows more accurate models to be established. By these methods functions
defining heat transfer coefficients for both sides of a heat exchanger may be
determined that give a fit to experimental data to within less than 1. 5% on measured
overall heat transfer coefficient.
Date of Award | Sept 1996 |
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Original language | English |
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Awarding Institution | |
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Engineering Design Optimisation with Physical Modelling and Evolutionary Algorithms
Cox, S. G. (Author). Sept 1996
Student thesis: Doctoral Thesis