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Bayesian optimized collection strategies for fatigue strength testing
Authors:Christopher Massimo Magazzeni  Rory Rose  Chris Gearhart  Jicheng Gong  Angus J Wilkinson
Affiliation:1. Department of Materials, University of Oxford, Oxford, UK;2. Center for Integrated Mobility Sciences, National Renewables Energy Laboratory, Golden, USA
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.
Keywords:fatigue  high cycle fatigue  optimum design  statistical model  statistics of extremes
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