Coupled mechanical-diffusion modelling of multitrap-mediated hydrogen-assisted fatigue in zirconium alloys

Abstract This study explores the hydrogen diffusion and trapping mechanisms of zirconium alloys under cyclic loading in nuclear reactors. We develop a micromechanical model incorporating multitrap and stress-assisted hydrogen diffusion, along with a hydrogen-induced softening effect. An extensive analysis was conducted to investigate the impacts of various fatigue parameters, including loading frequency, temperature, and hydrogen concentration, on the cyclic behavior of hydrogen diffusion and trapping, explicitly focusing on the dislocation trap. In addition, we quantitatively investigate the effects of Nb trap densities and their binding energy contribute to the enhancement of hydrogen embrittlement resistance in ternary H–Nb–Zr systems. Niobium atoms serve as a beneficial trap, impeding hydrogen diffusion and improving resistance to hydrogen-induced embrittlement. Our findings reveal the competitive mechanisms among different types of traps in regulating hydrogen diffusion and trapping near the crack tip. Evidence demonstrates that an increase in the hydrogen trapping capacity of beneficial traps leads to a more pronounced hydrogen-induced softening effect, thereby increasing the hydrogen trap capacity of dislocations. Conversely, when the amount of hydrogen in the lattice interstitials decreases, trapping hydrogen concentration at the grain boundary also decreases, indicating that increasing the hydrogen trapping capacity of one type of trap can increase the hydrogen trap ability of the other, which is not directly involved with the fracture process. Furthermore, a TS S p -based criterion was employed to quantify hydride-precipitation risk. Results reveal that hydride risk in Zr alloys falls sharply when strong traps and favorable loading conditions act together. Importantly, hydride precipitation is governed jointly by diffusion kinetics, mechanical time scales and trapping thermodynamics, and must be mitigated through a quantitatively balanced, multi-factor strategy.