A data-driven multi-field analysis of nanocomposites for hydrogen storage

Abstract

This paper focuses on computational parameter identification associated with heat and mass diffusion macro-behavioral models of hydrogen storage systems from a continuum multiphysics perspective. A single wall nanotube (SWNT) based composite pellet is considered as our representative finite continuum system. The corresponding partial differential equations (PDEs) governing the spatio-temporal distribution of temperature and hydrogen concentration are formulated. Analytical solutions of the system of coupled PDEs are constructed and utilized in the context of inverse analysis. The corresponding non-linear optimization problem is formulated in order to determine the unknown parameters of the model, based on an objective function and constraints consistent with experimentally acquired data along with the physical and utilization requirements of the problem. Behavioral simulation results are presented in an effort to demonstrate the applicability of the methodology. Finally, we indicate potential extensions of this methodology to multi-scale and manufacturing process optimization. © Springer-Verlag Berlin Heidelberg 2005.