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

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

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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 Fondue Fountain 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 Horse First-Aid 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.