Mahbuba Tasmin

she/her

Ph.D. Candidate in Computer Science at UMass Amherst. My research integrates machine learning and computational biology to understand and predict antibiotic resistance in Mycobacterium tuberculosis.

Non-Newtonian Effect on Heat Transfer and Entropy Generation of Natural Convection Nanofluid Flow Inside a Vertical Wavy Porous Cavity

Published in SN Applied Sciences, 3:299 (2021), 2021

Studies natural convection of a Cu–water nanofluid, modeled as non-Newtonian via a power-law and Brinkman-extended Darcy formulation, inside a two-dimensional wavy porous cavity. Uses the finite volume method to characterize how the power-law index, Darcy number, volume fraction, and Rayleigh number affect heat transfer and local entropy generation.

Recommended citation: Tasmin, M., Nag, P., Hoque, Z.T., Molla, M.M. Non-Newtonian effect on heat transfer and entropy generation of natural convection nanofluid flow inside a vertical wavy porous cavity. SN Appl. Sci. 3, 299 (2021).
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