Title
Identification of quasi-optimal regions in the design space using surrogate modeling
Author
Faculty/Department
Faculty of Sciences. Physics
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
New York ,
Subject
Mathematics
Physics
Human medicine
Computer. Automation
Source (journal)
Engineering with computers: an international journal for computer-aided mechanical and structural engineering. - New York
Volume/pages
29(2013) :2 , p. 127-138
ISSN
0177-0667
ISI
000316214500001
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
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.
E-info
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