Samarjeet Chanda

TL;DR: In this paper, a novel experimental technique for the simultaneous estimation of principal thermal conductivities of a layered honeycomb composite widely used in aerospace structures was developed, where a new standard test material exhibiting structural anisotropy with respect to thermal transport was first conceptualized, designed and fabricated.

TL;DR: In this paper, the principal thermal conductivities (kx,ky, and kz) of an anisotropic composite medium using an inverse heat transfer analysis were determined using a two-layer feed forward back propagation artificial neural network (ANN) trained using the Levenberg-Marquardt algorithm.

TL;DR: In this paper, the authors developed a methodology to predict the gas production potential and hydrological transport properties of methane hydrate reservoirs using artificial neural network coupled with genetic algorithm using a surrogate model, mimicking the full scale model along with reservoir heterogeneity is developed using a feed forward back-propagation artificial neural networks trained using the Levenberg-Marquardt algorithm coupled with Bayesian regularization.

TL;DR: In this paper, an inverse methodology was developed to estimate the thermal and mass diffusivities of a solute-solvent system using a combination of evolutionary simulation and optimization algorithms.

TL;DR: In this paper, the authors developed a measurement technique for the estimation of thermal contact conductance at a polymer (Nylon)-metal (Copper) two dimensional interface having an annular contact under low external loading.