Abstract
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.
NSTL
Elsevier