Multidisciplinary optimization formulations benefits on space mapping techniques

Purpose - The purpose of this paper is to investigate the use of multidisciplinary optimization (MDO) formulations within space-mapping techniques in order to reduce their computing time.Design methodology approach - The aim of this work is to quantify the interest of using MDO formulations within s...

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Bibliographic Details
Published in:Compel 2012-01, Vol.31 (3), p.945-957
Main Authors: Ben Ayed, Ramzi, Brisset, Stéphane
Format: Article
Language:English
Subjects:
Algorithms
Computational efficiency
Computing time
Copper
Decomposition
Design optimization
Feasibility
Finite element analysis
Mapping
Mathematical analysis
Mathematical models
Multidisciplinary
Noise
Studies
Temperature
Transformers
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Summary:Purpose - The purpose of this paper is to investigate the use of multidisciplinary optimization (MDO) formulations within space-mapping techniques in order to reduce their computing time.Design methodology approach - The aim of this work is to quantify the interest of using MDO formulations within space mapping techniques. A comparison of three MDO formulations is carried out in a short time by using an analytical model of a safety transformer. This comparison reveals the advantage of two formulations in terms of robustness and computing time among the three MDO formulations. Then, the best formulations are investigated within output space mapping, using both analytical and FE models of the transformer.Findings - A major computing time gain equal to 5.5 is achieved using the Individual Disciplinary Feasibility formulation within the output space-mapping technique in the case of the safety transformer.Originality value - The MultiDisciplinary Feasibility formulation is the common formulation used within space-mapping technique because it is the most conventional way to perform MDO. The originality of this paper is to investigate the Individual Disciplinary Feasibility formulation within output space-mapping technique in order to allow the parallelization of calculation and to achieve a major reduction of computing time.
ISSN:0332-1649
2054-5606
DOI:10.1108/03321641211209825