Mathematical Modelling of Nanofluids.

Mathematically modeled the continuity, momentum, and energy equations of two non-Newtonian nanofluids. The equations were numerically solved for changes in velocity, concentration, and temperature with the changes in physical parameters, and the results plotted.

Ramesh, K., Rawal, M., & Patel, A. (2021). Numerical simulation of radiative MHD Sutterby nanofluid flow through porous medium in the presence of hall currents and electroosmosis. International Journal of Applied and Computational Mathematics, 7(2), 1-12.

Ramesh, K., Patel, A., & Rawal, M. (2020). Electroosmosis and transverse magnetic effects on radiative tangent hyperbolic nanofluid flow through porous medium. International Journal of Ambient Energy, 1-8.

Developing Evolutionary Algorithms to solve Advance Engineering Problems.

Developed a novel approach to solve constrained optimization problems. The new algorithm is incorporated with a socio-inspired algorithm called Cohort Intelligence with a modified probability distribution approach created by Tanh and Modular function. The efficiency of the code was tested on Kyoto Test problems, and it showed up to 98% improvement compared to other EAs.

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Solutions to Advanced Manufacturing Process Problems using Cohort Intelligence Algorithm with Improved Constraint Handeling Approaches (Under Review)