System optimization of heat transfer performance of hydrogen storage bed based on backpropagation neural network-genetic algorithm

ABSTRACT

Seven structural parameters that affected the heat transfer performance were proposed as optimization variables to enhance the heat transfer and thermal reaction capacity of the thin double-layered annular zirconium–cobalt (ZrCo) bed of hydrogen metal reactor and to improve the hydrogen storage performance. We used the Taguchi method to conduct numerical experimental sampling and construct a three-dimensional model of the hydrogen absorption of a hydrogen storage bed. COMSOL software was used to simulate 36 models of the hydrogen absorption process and changes in the temperature and time of the hydrogen storage bed under different conditions were identified. A new hybrid method combining a neural network and the genetic algorithm was proposed by taking the hot-spot temperature of the bed and the cooling time when it was cooled to 300 K as the optimization objectives. The algorithm was implemented, and the relationship between the process parameters and the objective function was established. A model response analysis was conducted to improve the understanding of the behavior of the backpropagation model and to analyze the sensitivity of the parameters. This hybrid method was used to optimize the parameters to obtain an excellent hydrogen storage performance. The results showed that the predicted value of the neural network model was highly consistent with the numerical simulation results. The number of cooling tubes had the greatest impact on the heat transfer performance, and the optimal combination of the input parameters was obtained. When the optimized parameters were used to reach the target temperature, the cooling time was reduced by 78s, which provided guidance for the design and operation of hydrogen storage beds.

KEYWORDS:

• ZrCo bed
• neural network and genetic algorithm
• heat transfer performance
• sensitivity analysis
• optimization

Acknowledgments

The authors gratefully acknowledge the financial support of the Sichuan Province application of basic research program “Study on Dynamic Characteristics and Optimization of Heat and Mass Transfer Process in Metal Hydrogen Storage Bed” (Grant No. 2020YJ0257).

Table

Data availability

The raw/processed data required to reproduce the findings in the current manuscript cannot be shared at this time as these data also form a part of an ongoing study.

Additional information

Funding

This work was supported by the the Sichuan Province application of basic research program [2020YJ0257].

Notes on contributors

Ping Zhao

Ping Zhao is undertaking a PhD in Civil Engineering in Sichuan University. Her current research works focus on Study and optimization of kinetic characteristics of heat and mass transfer process in metal hydrogen storage bed and Engineering material plasticity, creep and fatigue life prediction.

XiangGuo Zeng

XiangGuo Zeng is a Professor and the Director of  the Department of Civil and Environmental Engineering at the  Sichuan University.  Professor  Zeng has taught courses in Mechanics of Materials, Structural Mechanics, Structural Steel Design, Structural Analysis and Finite Element Methods. His research interests include Engineering material damage, fracture and constitutive theory research; engineering material mesomechanics test, fracture mechanics experiment, engineering material plasticity, creep, fatigue and relaxation performance test, finite element analysis of engineering structure, and have published about 40 technical papers in these areas in various international journals and conferences.

Wei Li

Wei Li, Ph.D. Candidate in Civil Engineering. College of Architecture and Environment, Sichuan University. Her research on the Heat and Mass Transfer Mechanism of Metal Hydrogen Storage Bed.

Han Zhao

Han Zhao is undertaking a PhD in Solid mechanics  in the School of Sichuan University. He mainly studies on  hydrogen-induced cracking.

Fang Wang

Fang Wang is a Professor of the School of Materials and Energy from Southwest University. Professor Wang's research on Material fatigue fracture theory, method and numerical simulation and microscopic mechanism of hydrogen storage behaviour of alloys and optimal.