Bayesian optimized collection strategies for fatigue strength testing |
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Authors: | Christopher Massimo Magazzeni Rory Rose Chris Gearhart Jicheng Gong Angus J Wilkinson |
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Affiliation: | 1. Department of Materials, University of Oxford, Oxford, UK;2. Center for Integrated Mobility Sciences, National Renewables Energy Laboratory, Golden, USA |
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Abstract: | A statistical framework is presented enabling optimal sampling and analysis of constant life fatigue data. Protocols using Bayesian maximum entropy sampling are built based on conventional staircase and stress step methods, reducing the requirement of prior knowledge for data collection. The Bayesian Staircase method shows improved parameter estimation efficiency, and the Bayesian Stress Step method shows equal accuracy to the standard method at larger step size allowing experimentalists to lessen concerns of loading history. Statistical methods for determining model suitability are shown, highlighting the influence of protocol. Experimental validation is performed, showing the applicability of the methods in laboratory testing. |
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Keywords: | fatigue high cycle fatigue optimum design statistical model statistics of extremes |
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