A new metamodel method using Gaussian process based bias function for vehicle crashworthiness design
Metamodel-based design optimisation is widely used to obtain a better design efficiently in a vehicle lightweight design. However, one of the major drawbacks of using metamodel in design optimisation is that the accuracy of any metamodel is inherently unpredictable, as the behaviours of vehicle performances are highly nonlinear and most metamodels do not consider the model uncertainty or discrepancy between physical experiments and computer model or metamodel. In this article, the bias function is used to statistically correct the model discrepancy, which is represented by a Gaussian process. A new metamodel method using Gaussian process based bias function is proposed to improve the accuracy of the metamodel. The proposed method is demonstrated through a mathematical example and examined by a vehicle crashworthiness design problem aiming at minimising the weight of front-end structure while satisfying the design target.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13588265
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Supplemental Notes:
- Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Wang, Xianhui
- Shi, Lei
- Publication Date: 2014-5
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 311-321
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Serial:
- International Journal of Crashworthiness
- Volume: 19
- Issue Number: 3
- Publisher: Taylor & Francis
- ISSN: 1358-8265
- Serial URL: http://www.tandfonline.com/loi/tcrs20
Subject/Index Terms
- TRT Terms: Accuracy; Bias (Statistics); Crashworthiness; Design methods; Light vehicles; Vehicle design
- Uncontrolled Terms: Gaussian process
- Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01522090
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 16 2014 9:14AM