Probabilistic hydrogen-assisted fatigue crack growth under random pressure fluctuations in pipeline steels

The increasing demand for energy and the global threat of climate change have driven the search for alternative energy sources, with hydrogen emerging as a prominent substitute for fossil fuels. The fatigue behavior of pipeline steels under gaseous hydrogen is a critical problem that is impeding the industry's adoption of hydrogen into the current natural gas infrastructure. A brief review of existing hydrogen-assisted fatigue crack growth (HAFCG) studies, which reveal several key gaps, is given first. Existing HA-FCG models predominantly address constant amplitude loading, while the realistic driving force is random loading in gas pipelines. Also, the current uncertainty quantification studies for HA-FCG focus on material randomness and overlook the large uncertainties associated with random pressure fluctuations. To address these issues, this study proposes a HA-FCG model that utilizes a time-based subcycle approach, allowing for direct application to random spectrum loads without the need for cycle counting. A model parameter as a function of hydrogen operating conditions is introduced to capture the different regimes in HA-FCG, and the model predictions are compared with ASME B31.12 code. Following this, statistical analysis of random pressure fluctuation data collected from natural gas pipelines at multiple locations is performed. The realistic industry pressure data shows distinct statistical features, and it is observed that the high-fidelity data (high sampling frequency) is beneficial for accurate fatigue life predictions. Uncertainty quantification and load reconstruction are performed by the Karhunen-Loe`ve expansion with a post- clipping procedure, leading to a probabilistic HA-FCG analysis. The paper concludes with key findings and suggests directions for future research.