Seshasai Srinivasan

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In an unprecedented experimental investigation, a ternary and a four component hydrocarbon mixture at high pressure have been studied in a nearly convection free environment to understand the thermodiffusion process. A binary mixture has also been investigated in this environment. Experimental investigations of the three mixtures have been conducted in(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)
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)
Experimental investigations on thermodiffusion have been conducted for five different ternary mixtures of methane, n-butane, and n-dodecane at a high temperature and pressure. While the mole fraction of methane was fixed at 0.2 the mole fraction of n-dodecane was varied from 0.7 to 0.2. The experiments were performed in a microgravity environment on board(More)
Models of chemical reaction systems can be quite complex as they need to include information regarding the reactions and the transfer of mass and heat. The commonly used state variables—concentrations and temperatures—describe the interplay between many phenomena. As a consequence, each state variable is affected by several rate processes. On the other(More)
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