Finite element analysis and surrogate-optimized design of a nature-inspired auxetic stent

Prior studies have revealed that the structural design of stents is critical to reducing some of the alarming post-operative complications associated with stent-related intervention. However, the technical search for stents that guarantee robustness against stent-induced post-intervention complications remains an open problem. Along this objective, this study investigates a re-entrant auxetic stent's structural response and performance optimizations. In pursuit of the goal, a nonlinear finite element analysis (FEA) is employed to uncover metrics characterizing the auxetic stent's mechanical behavior. Subsequently, the non-dominated sorting genetic algorithm (NSGA-II) is implemented to simultaneously minimize the stent's von Mises stress and the elastic radial recoil (ERR). Results from the FEA revealed a tight connection between the stent's response and the features of the base auxetic building block (the rib length, strut width, and the re-entrant angle). It is observed that the auxetic stent exhibits a much lower ERR. Besides, larger values of its rib length and re-entrant angle are noticed to favor smaller von Mises stress. The Pareto-optimal front from the NSGA-II-based optimization scheme revealed a sharp trade-off in the simultaneous minimization of the von Mises stress and the ERR. Moreover, an optimal combination of the auxetic unit cell's geometric parameters is found to yield a much lower maximum von Mises stress of