搜索
Effective thermal conductivity of metal hydride particle bed: Theoretical model and experimental validation
发布时间：2025-04-30
点击次数：
- 发布时间：
- 2025-04-30
- 论文名称：
- Effective thermal conductivity of metal hydride particle bed: Theoretical model and experimental validation
- 发表刊物：
- Energy
- 摘要：
- It is essential to accurately predict the effective thermal conductivities of metal hydride (MH) beds for simulating the dynamic hydrogen storage of MH reactors. In this study, a 3-D analysis model was established to detailedly analyze the contributions of different heat transfer pathways on overall heat transfer of particle bed. The results indicate more than 95% heat quantity is transferred through the particle-gas fflm-particle pathway. Besides, taking the LaNi5 particle bed (λs equals 12.5 W m− 1K− 1) as an example, only 26.2% gas volume contributes to transferring 90% heat quantity, proving the existence of heat transfer concentrating (HTC). Thus, a heat transfer concentrating model for predicting effective thermal conductivities of particle beds was established. The predicted thermal conductivities of HTC model were compared with six different models and the experimental data in references. The prediction accuracy and applicability of HTC model are the best. Then, the thermal conductivities of LaNi5 and Fe particle beds were experimentally measured. The predicted thermal conductivities by HTC model agree great with the experimental data, and the mean prediction errors are less than 7%. Finally, the HTC model is applicable within the porosity and thermal conductivity ratio from 0.33 to 0.68 and 1 to 8915, respectively.
- 合写作者：
- Xiao-Shuai Bai, Long Rong, Wei-Wei Yang* , Fu-Sheng Yang**
- 卷号：
- 271
- 页面范围：
- 127085
- 是否译文：
- 否
- 发表时间：
- 2023-02-26
- 上一条：Energy saving control and operation strategy analysis of thermal coupling system of fuel cell and metal hydride tank
- 下一条：Energetic, economic and environmental (3E) optimization of hydrogen production process from coal-biomass co-gasification based on a novel method of Ordering Preference Targeting at Bi-Ideal Average Solutions (OPTBIAS)
