Active Search Methods to Predict Material Failure Under Intermittent Loading in the Serebrinksy-Ortiz Fatigue Model

摘要

The rainflow counting algorithm for material fatigue is both simple to implement and extraordinarily successful for predicting material failure times. However, it neglects memory effects and time-ordering dependence, and therefor runs into difficulties dealing with intermittent loads, especially those with long tailed distributions. In this report, we use the Serebrinsky-Ortiz model of material fatigue to introduce a partial analytical solution for deterministic intermittent loads, which greatly improves integration speed while still conservatively identifying early failures. Additionally, we apply recent advances in optimal experimental design both to gain insight into how rare events lead to extreme early material failure, and to estimate the long tail of the distribution of failure times.