Coupled analysis of hydrogen diffusion, deformation, and fracture: a review

Hydrogen (H), emerging as a sustainable and promising clean energy source, holds significant potential for transitioning towards a H-based economy, offering a cleaner alternative to traditional fossil fuels. However, hydrogen embrittlement (HE) poses a substantial obstacle to this transition, impacting critical sectors such as transportation, defense, energy production, and construction. Computational modeling, driven by the continuous development of new algorithms and high-performance computing platforms, emerges as an attractive avenue to unravel and address the complexities associated with HE. In particular, a multidisciplinary modeling approach shows potential in investigating the intricate interactions between H and materials across different temporal and spatial scales. Over the last few decades, there have already been many developments in computational modeling investigations based on a coupled study of H diffusion, deformation, and fracture processes to address multifaceted aspects of the HE problem. This comprehensive review sheds light on these advancements, providing insights into the modeling methodologies adopted in these investigations and their results. The review begins with a concise overview of commonly adopted mechanisms to explain HE. Thereafter, the discussion shifts to various advancements in H diffusion modeling, from early works to most recent developments, encompassing diverse aspects, such as H uptake and diffusion through the lattice structure and the role of microstructural traps and material microstructure. The last section of the review focuses on several theoretical and numerical studies that simulate how H affects the fracture characteristics and mechanical properties of various metals and alloys. This discussion includes applications of various state-of-the-art fracture models to predict H-assisted crack growth, as well as a range of theoretical models, continuum-based finite element simulations, and micro-meso scale modeling studies.