Seshasai Srinivasan

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A thermodiffusion model based on the principles of artificial neural networks has been proposed. In addition to the development and validation with respect to the experimental data of binary n-alkane mixtures from the literature, the ability of the model to predict the known thermodiffusion trends has been presented. Comparison with other models in the(More)
A previously presented neural network-based thermodiffusion model that was valid for n-alkane type components has been extended to predict the thermo-solutal diffusion in an arbitrary binary hydrocarbon mixture. The enhanced model uses additional input information about the binary system and is based on a significantly large database of thermodiffusion(More)
In this work, we present a curl-curl formulation for computing the electromagnetic modes that propagate in a waveguide, fully or partially made with magneto-optic material. Such medium is characterized by a nonreciprocal permittivity tensor, which is responsible for a different propagation constant for the forward and backward traveling modes. By exploiting(More)
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