The goal of the present work is three fold. Firstly to create the forward continuum model of a multi-species diffusing system under simultaneous presence of chemical reactivity and temperature as the general case of all hydrogen storage systems. Secondly, cast the problem of hydrogen storage in a pragmatic product-design context where the appropriate design parameters of the system are determined via appropriate optimization methods that utilize extensive experimental data encoding the behavior of the system. Thirdly, demonstrate this methodology on characterizing certain systemic parameters. Thus, the context of the work presented is defined by a data-driven characterization of coupled heat and mass diffusion models of hydrogen storage systems from a multiphysics perspective at the macro length scale. In particular, a single wall nanotube (SWNT) based composite is modeled by coupled partial differential equations representing spatio-temporal evolution of distributions of temperature and hydrogen concentration. Analytical solutions of these equations are adopted for an inverse analysis that defines a non-linear optimization problem for determining the parameters of the model by objective function minimization. Experimentally acquired and model produced data are used to construct the system’s objective function. Simulations to demonstrate the applicability of the methodology and a discussion of its potential extension to multi-scale and manufacturing process optimization are also presented.
Characterization of the chemical reactivity and nephrotoxicity of N-acetyl-S-(1,2-dichlorovinyl)-l-cysteine sulfoxide, a potential reactive metabolite of trichloroethylene
