4.7 Article

Hydrogen storage in branch mini-channel metal hydride reactor: Optimization design, sensitivity analysis and quadratic regression

期刊

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 46, 期 49, 页码 25189-25207

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2021.05.051

关键词

Metal hydride reactor; Branch tube; Heat transfer; Mass transfer; Sensitivity analysis; Quadratic response surface analysis

资金

  1. National Natural Science Foundation of China [22078262, 21808183]
  2. Technology Innovation Talent Serviced Industrial Project of Xi'an Science and Technology Bureau [2020KJRC0114]
  3. Local Service Fund of Education Department of Shaanxi Province [18JC031]
  4. State Key Laboratory of Chemical Engineering [SKL-ChE18A02]

向作者/读者索取更多资源

Research shows that using metal hydride for hydrogen storage has potential advantages, and the new branch mini-channel reactor can significantly reduce hydrogenation/dehydrogenation time, achieving more efficient reactions. Analysis of the optimal performance of operating conditions reveals that hydrogen pressure and fluid temperature have the most significant impacts on reactor performance.
Metal hydride is an encouraging way for H-2 storage owing to the large H-2 storage capacity and suitable physical properties. As a crucial equipment for reversible chemical reaction of metal hydride, we propose a new branch mini-channel reactor to promote heat transfer and reaction effectively in H-2 storage reactor, which can reduce more than 55% hydrogenation/dehydrogenation time compared with straight tube reactor. Meanwhile, the optimal performance of both reactors could be achieved at branch number of 3 and center distance of branch bifurcation point of 8.5 mm. The optimal and sensitivity analysis of 6 operation conditions reveal that both reactors performances are most sensitive to H-2 pressure and fluid temperature for hydrogenation and dehydrogenation, respectively. Moreover, quadratic response surface analysis indicates an extremely marked impact (99% believable probability) on the regression model, whose regression coefficient (R-2) could achieve 0.9955. (C) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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