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Title
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Identification of quasi-optimal regions in the design space using surrogate modeling
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Author
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Abstract
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| The use of Surrogate Based Optimization (SBO) is widely spread in engineering design to find optimal performance characteristics of expensive simulations (forward analysis: from input to optimal output). However, often the practitioner knows a priori the desired performance and is interested in finding the associated input parameters (reverse analysis: from desired output to input). A popular method to solve such reverse (inverse) problems is to minimize the error between the simulated performance and the desired goal. However, there might be multiple quasi-optimal solutions to the problem. In this paper, the authors propose a novel method to efficiently solve inverse problems and to sample Quasi-Optimal Regions (QORs) in the input (design) space more densely. The development of this technique, based on the probability of improvement criterion and kriging models, is driven by a real-life problem from bio-mechanics, i.e., determining the elasticity of the (rabbit) tympanic membrane, a membrane that converts acoustic sound wave into vibrations of the middle ear ossicular bones. |
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Language
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English
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Source (journal)
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Engineering with computers: an international journal for computer-aided mechanical and structural engineering. - New York
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Publication
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New York
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2013
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ISSN
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0177-0667
[print]
1435-5663
[online]
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Volume/pages
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29
:2
(2013)
, p. 127-138
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ISI
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000316214500001
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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