A 2-D reduced dynamic model for a shell-and-tube based metal hydride reactor for geometry and operation condition optimal design

• Published in: Applied thermal engineering Vol. 206; p. 118125
• Main Authors: Pan, Chunjian, Ziviani, Davide, Braun, James E.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-04-2022; Elsevier BV
• Subjects: Accuracy; Data-driven models; Design; Dynamic models; Heat transfer; Metal hydrides; Metal hydrides Reactors; Optimal design; Parabolic differential equations; Partial differential equations; Reactors; Reduced model (RM); Tuning; Two dimensional models; Data-driven models; Metal hydrides Reactors; Reduced model (RM); Optimal design
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2022.118125

•A fast 2-D reduced model for a shell-and-tube based metal hydride reactor.•Coarse mesh is employed as a reduced model basis.•Data-driven factors are employed to correct the transportation rates.
An MH reactor is a complex multi-physics system and its optimal design is critical to reduce the operation and investment cost. Geometry and operation condition optimal design reported in the literature is often based on parametric study of high fidelity simulations, which is computationally expensive. In this paper, a framework to develop a fast reduced model for a two-dimensional shell-and-tube based MH reactor is proposed. This framework is generally applicable to parabolic PDEs. A lumped capacity model is used as a reduced model basis. Tuning factors that aim to correct the transportation phenomena in a lumped capacity model are introduced. The tuning factors are correlated to key dimensionless group parameters of the system and are constructed by using data from a high fidelity model (HFM). Comparing to pure data-driven models, the proposed modeling framework has good extrapolation ability and hence requires less high fidelity data. The tuning factors establish parametric dependence of the system for efficient optimal design.