Abstract

© 2018, Springer Nature Switzerland AG. In many product design and development applications, Computational Fluid Dynamics (CFD) has become a useful tool for analysis. This is particularly because of the accuracy of CFD simulations in predicting the important flow attributes for a given design. On occasions when design optimisation is applied to real-world engineering problems using CFD, the implementation may not be available for examination. As such, in both the CFD and optimisation communities, there is a need for a set of computationally expensive benchmark test problems for design optimisation using CFD. In this paper, we present a suite of three computationally expensive real-world problems observed in different fields of engineering. We have developed Python software capable of automatically constructing geometries from a given decision vector, running appropriate simulations using the CFD code OpenFOAM, and returning the computed objective values. Thus, users may easily evaluate a decision vector and perform optimisation of these design problems using their optimisation methods without developing custom CFD code. For comparison, we provide the objective values for the base geometries and typical computation times for the test cases presented here.

DOI

10.1007/978-3-319-99259-4_24

Publication Date

2018-08-21

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

11102 LNCS

Publisher

Springer International Publishing

ISBN

9783319992587

ISSN

1611-3349

Embargo Period

2024-11-22

First Page

296

Last Page

307

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