Multi-objective optimization design of NPR protection shell for hydrogen storage tank

储罐 壳体(结构) 氢气储存 工程类 结构工程 计算机科学 机械工程 化学 有机化学
作者
Guan Zhou,Yuankui Niu,Jiale Zhao,Yuanlong Wang
出处
期刊:Mechanics of Advanced Materials and Structures [Informa]
卷期号:: 1-14 被引量:1
标识
DOI:10.1080/15376494.2024.2382360
摘要

In order to improve the safety of on-board hydrogen storage tanks during collision, a protective shell based on a negative Poisson's ratio (NPR) core is designed in this paper. After analyzing and comparing the crashworthiness of three typical honeycomb structures, the concave hexagonal negative Poisson's ratio honeycomb is selected as the energy-absorbing inner core of the hydrogen storage tank protection structure. The sensitivity analysis of the structural parameters of the NPR shell is conducted through orthogonal tests to identify parameters with a significant impact on crash performance. These parameters are then used as experimental variables for subsequent optimization design. Subsequently, a response surface approximation model between the optimization objective and the structural parameters is established based on the response surface method. Finally, the adaptive simulated annealing algorithm (ASA), neighborhood cultivation genetic algorithm (NCGA), and non-dominated sorting genetic algorithm-II (NSGA-II) are used to optimize the structural parameters, and the optimization results are verified by the whole-vehicle crash simulation. The simulation results demonstrate that all three algorithms achieve better optimization results, among which NCGA is more advantageous in improving the overall performance of the protective shell. After NCGA optimization, the specific energy absorption of the protective shell increases by 19.75%, the maximum collision force of the rigid wall decreases by 23.63%, and the maximum stress of the hydrogen storage tank body decreases by 22.77%. These findings indicate that the designed protection shell effectively improves the crashworthiness of the hydrogen storage tank during collisions.
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