Two-phase optimized experimental design for fatigue limit testing.

This study proposes an innovative Two-phase method, based on the Langlie method and the D-optimality criterion, to overcome the intrinsic shortcomings of the staircase method used in estimating the fatigue limit distribution. This paper identifies the current challenges and provides an overview of existing solutions, setting the goal of developing an efficient data collection protocol. It further explains the application of D-optimality criterion and describes the Two-phase protocol, accompanied by a relevant example. The most significant advantage of this approach is its minimal requirement for pre-test information. A simulation-based study was executed to analyze the sensitivity of the input parameters and compare the effectiveness of the proposed method with the traditional staircase and Bayesian optimized method. The numerical simulations reveal that the proposed method offers improved estimation performance for the mean and standard deviation of the fatigue limit distribution, even with minimal pre-test information. • A Two-phase strategy based on Langlie and D-optimality is proposed for a better fatigue limit estimation. • The proposed method avoids the fixed step size in the conventional staircase method. • A simulation-based investigation is performed to analyze the proposed two-phase method. • The Two-phase is outperformed on estimated quality even with less information on input bounds. [ABSTRACT FROM AUTHOR]