Open-Access Experiment Dataset for Fatigue Damage Accumulation and Life Prediction Models

This work addresses the lack of focus on verification and comparison of existing fatigue damage accumulation and life prediction models on the basis of large and well-documented experiment datasets. Sixty-four constant amplitude, 54 two-level block loading, and 27 three-level block loading valid experiments were performed in order to generate an open-access, high-quality dataset that can be used as a benchmark for existing models. In the future, more experiments of various specimen geometries and loading conditions will be added. The obtained dataset was used for a study comparing five (non)linear fatigue damage and life prediction models. It is shown how the performance of several (non)linear damage models is strongly dependent on the considered material dataset and loading sequence. Therefore, it is important to verify models with a broad set of independent datasets, as many existing models show significant bias to certain datasets.

Automated summary

This work focuses on the lack of verification and comparison of existing fatigue damage accumulation and life prediction models using large and well-documented experiment datasets. A comprehensive dataset was generated by conducting several valid experiments, which can be used as a benchmark for existing models. The study compared five (non)linear fatigue damage and life prediction models using the obtained dataset, revealing the strong dependence of model performance on material dataset and loading sequence. It emphasizes the importance of verifying models with diverse independent datasets to overcome biases exhibited by existing models.