氢
氢气储存
氢化物
传热
材料科学
拓扑(电路)
催化作用
入口
金属
化学工程
化学
热力学
机械工程
有机化学
电气工程
冶金
物理
工程类
作者
Hao Ye,Yubing Tao,Hao Chang,Zihan Liu,Qing Huang,Qingqing Deng
标识
DOI:10.1016/j.ijhydene.2024.02.062
摘要
The low thermal conductivity of hydrogen storage materials significantly limits the reaction rate of hydrogen storage and release in metal hydrides reactors. In present paper, a heat transfer fluid channel was designed by topology optimization method to enhance the heat transfer performance and increase the hydrogen storage and release rates. Firstly, a series of channel structures were obtained through two-dimensional topology optimization, then they were embedded into metal hydride reaction beds by three-dimensional reconstruction. The hydrogen storage and release performance of different reaction beds were analyzed, the most effective bed structure was derived and compared with the finned bed. The results show that the hydrogen storage and release time of the designed fluid channel reaction bed is 31.5% and 24.4% less than the finned bed. Lastly, the hydrogen storage and release performance of the designed reaction bed under different operating conditions were examined. The appropriate operation conditions were derived: for hydrogen storage, hydrogen pressure of 1.0 MPa, HTF inlet velocity of 0.25 m s −1 and inlet temperature of 293 K; for hydrogen release, hydrogen pressure of 0.1 MPa, HTF inlet velocity of 0.25 m s −1 and inlet temperature of 363 K. Moreover, the reaction bed designed by topology optimization has obvious advantages and shows better hydrogen storage and release performance compared to finned reactors under various operating conditions. • A reactor structure for hydrogen storage is obtained by topology optimization. • The absorption and desorption time of optimized reactor is 31.5% and 24.4% less than the finned reactor. • The appropriate operation conditions for hydrogen storage and release are obtained. • The optimized reactor has better performance than finned reactors under various conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI