Dr. MIKHAN’s research expertise encompasses applied mathematics, fluid mechanics, computational fluid dynamics (CFD), and optimization strategies for renewable energy applications. His work is particularly focused on Latent Heat Thermal Energy Storage (LHTES), employing nano-enhanced phase change materials (Nano-PCMs) and hybrid nanofluids to improve energy efficiency and sustainability. Additionally, his research integrates nanotechnology, entropy analysis, and heat transfer to advance thermal management systems.
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This study presents an analytical mathematical model for an integrated microbial fuel cell--oxic--anoxic bioreactor (MFC--OB--ANB) system designed for simultaneous slaughterhouse wastewater treatment and energy recovery. The model incorporates bioelectrochemical oxidation, nitrification, and denitrification processes using acetate as a representative substrate. Closed-form analytical solutions are derived for substrate degradation, nitrogen transformation, current density, and system voltage. The effects of biofilm thickness, membrane conductivity, and influent substrate concentration on treatment efficiency and power generation are systematically investigated. Results reveal that enhanced b... More >
This study describes convective temperature and mass transport in a magnetohydrodynamic nanofluid moving via an absorbing channel stretched across an extensive region while being influenced by a securing region. The analytical framework incorporates a multitude of factors including heat generation, thermal radiation effects, viscous dissipation, and chemical reaction implications. The influences of porosity, warm production, thermal emission, attractive fields, sticky indulgence, and substance reactions on the flow dynamics are absolutely expounded across a spectrum of governing parameters. Furthermore, it is posited that regulation can be applied to the nanoparticle volume segment at the bo... More >
Graphical Abstract
Open Access
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Research Article
| 27 July 2025
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This study presents a mathematical framework to analyze the transmission dynamics of the Ebola Virus Disease (EVD) using an extended SEIRVH model. The model incorporates vaccinated and hospitalized compartments, addressing critical factors such as vaccination efficacy, healthcare interventions, and natural disease progression. Differential equations describe the transitions between six population compartments. The study evaluates model stability and bifurcation through well-posedness, positivity, and boundedness analyzes, ensuring realistic and biologically valid solutions. The basic reproduction number, R0, derived from the next generation matrix, serves as a threshold for outbreak control.... More >
