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Open AccessFeature PaperArticle

A Response-Adaptive Method for Design of Validation Experiments in Computational Mechanics

1
Department of System Dynamics, Korea Institute of Machinery and Materials, Daejeon 34103, Korea
2
Department of Safety Engineering, Chungbuk National University, Chungbuk 28644, Korea
3
Department of Nuclear Equipment Safety, Korea Institute of Machinery and Materials, Daejeon 34103, Korea
4
School of Mechanical Engineering, Gwangju Institute of Science and Technology, Gwangju 61005, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(2), 647; https://doi.org/10.3390/app10020647
Received: 25 November 2019 / Revised: 12 January 2020 / Accepted: 13 January 2020 / Published: 16 January 2020
(This article belongs to the Special Issue Selected Papers from the ICMR 2019)
For model verification and validation (V & V) in computational mechanics, a hypothesis test for the validity check (HTVC) is useful, in particular, with a limited number of experimental data. However, HTVC does not address how type I and II errors can be reduced when additional resources for sampling become available. For the validation of computational models of safety-related and mission-critical systems, it is challenging to design experiments so that type II error is reduced while maintaining type I error at an acceptable level. To address the challenge, this paper proposes a new method to design validation experiments, response-adaptive experiment design (RAED). The RAED method adaptively selects the next experimental condition from among candidates of various operating conditions (experimental settings). RAED consists of six key steps: (1) define experimental conditions, (2) obtain experimental data, (3) calculate u-values, (4) compute the area metric, (5) select the next experimental condition, and (6) obtain additional experimental datum. To demonstrate the effectiveness of the RAED method, a case study of a numerical example is shown. It is demonstrated that additional experimental data obtained through the RAED method can reduce type II error in hypothesis testing and increase the probability of rejecting an invalid computational model. View Full-Text
Keywords: epistemic uncertainty; experimental design; false negative; model validation epistemic uncertainty; experimental design; false negative; model validation
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Jung, B.C.; Shin, Y.-H.; Lee, S.H.; Huh, Y.C.; Oh, H. A Response-Adaptive Method for Design of Validation Experiments in Computational Mechanics. Appl. Sci. 2020, 10, 647.

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