Engineering design optimisation with physical modelling and evolutionary algorithms
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.