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Entropy optimized magneto-thermo-diffusive transport in a chemically reactive unsteady third grade nanofluid flow
Mariadoss Moyes1, Subramanyam Reddy Anala2,3
1Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632 014, India.
Discover Nano
|June 30, 2026
Summary
This study analyzes unsteady nanofluid flow with magnetohydrodynamics and Cattaneo-Christov diffusion. Findings show radiation enhances heat transfer, while magnetic fields reduce velocity, impacting thermal systems and biomedical diagnostics.
Area of Science:
- Fluid Dynamics
- Heat and Mass Transfer
- Nanotechnology
Background:
- Advanced thermal systems require accurate prediction of heat-mass transfer.
- Magnetohydrodynamics and diffusion effects are critical in nanofluid flow.
- Buongiorno nanofluid model incorporates Brownian motion and thermophoresis.
Purpose of the Study:
- Investigate magneto-thermo-diffusive transport in unsteady third-grade nanofluid flow.
- Quantify the influence of multiple physical parameters on thermal performance and entropy generation.
- Develop an accurate predictive model using Artificial Neural Networks (ANN).
Main Methods:
- Numerical solution of nonlinear partial differential equations using fourth-order Runge-Kutta with shooting method.
- Application of ANN for enhanced predictive fidelity and model verification.
- Analysis of parameters including magnetic field, radiation, Brownian motion, and activation energy.
Main Results:
- Magnetic fields and unsteadiness suppress fluid velocity.
- Thermal radiation, Eckert number, Brownian motion, and thermophoresis enhance heat transport.
- Entropy generation increases with Brinkman and radiation parameters; activation energy impacts transfer rates.
Conclusions:
- The ANN framework provides superior accuracy for optimizing thermal systems.
- Findings support applications in advanced biomedical diagnostics, including cancer detection.
- Understanding these transport phenomena is crucial for designing efficient thermal devices.
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