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Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Mathematical Modeling and Analysis of Heat Transfer Enhancement in Nanofluid-Based Cooling Systems

Authors: Suresh Chandra, Raghavendra, Nikhil Agrawal, Poonam Kulkarni;

Mathematical Modeling and Analysis of Heat Transfer Enhancement in Nanofluid-Based Cooling Systems

Abstract

Heat transfer enhancement has become a critical area of research due to increasing demand for efficient thermal management in engineering applications such as electronic cooling, automotive systems, power plants, and renewable energy devices. Conventional heat transfer fluids such as water, ethylene glycol, and oils exhibit limited thermal conductivity, restricting system performance. Nanofluids, engineered by dispersing nanoparticles into base fluids, have emerged as a promising solution to overcome these limitations. This study presents a mathematical modeling and analytical investigation of heat transfer characteristics in nanofluid-based cooling systems. The research analyzes the effects of nanoparticle volume fraction, Reynolds number, and temperature gradient on heat transfer enhancement and flow behavior. Governing equations for fluid flow and heat transfer are developed and solved analytically. The findings demonstrate that nanofluids significantly enhance convective heat transfer performance compared to conventional fluids, making them suitable for advanced thermal management applications.

Keywords

Nanofluids, Heat Transfer Enhancement, Mathematical Modeling, Thermal Management, Convective Heat Transfer

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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