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March 23, 2026Proceedings of the Institution of Mechanical Engineers Part N Journal of Nanomaterials Nanoengineering and Nanosystems2 citations

Multi-factor sensitivity analysis of heat transfer rate in swirling flow induced by torsional motion of cylinder: A Taguchi-based approach

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VKV Vinay KumarRSRam Prakash Sharma

Key Points

  • The study aims to optimize thermal enhancement in swirling flows through sensitivity analysis and statistical methods.
  • Employed Taguchi-based optimization and sensitivity analysis to assess thermal transfer rate.
  • Converted partial differential equations to ordinary differential equations using similarity variables.
  • Utilized Runge-Kutta-Fehlberg-4 th –5 th order numerical technique for solution.
  • Achieved a maximum heat transfer rate of 4.916537.
  • Found that the Reynolds number has the largest effect (94.76%) on the Nusselt number.
  • Indicated optimal parameters at specific levels for the heat source/sink, Dufour number, and Reynolds number.

Abstract

This research examines the optimization of thermal enhancement in viscous fluids using statistical and numerical methods. The present study considers the impact of thermophoretic particle deposition on the swirling flow generated by the cylinder’s torsional motion. It is presumed that the cylinder rotates continuously along its axis and that the expansion rate of the cylinder wall is proportional to the position along the axis from the origin. Similarity variables are employed to convert partial differential equations (PDEs) into ordinary differential equations (ODEs), which are subsequently solved using the Runge-Kutta-Fehlberg-4 th –5 th (RKF-45) order numerical technique. Furthermore, Taguchi-based optimization, in conjunction with sensitivity analysis, is employed to assess the thermal transfer rate. The graphical representation indicates that with a rise in the Reynolds number, both the velocity and thermal profiles decrease, while the concentration profile increases. The Taguchi technique indicates that the third level of the heat source/sink parameter, the second level of the Dufour number, and the first level of the Reynolds number provide optimal circumstances for optimizing the Nusselt number. The analysis forecasts its industrial significance by attaining a maximum heat transfer rate of 4.916537. The Reynolds number (94.76%) has the largest effect on the Nusselt number, while the heat source/sink parameter (1.53%) has the least.

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Cite This Study

Kumar et al. (2026) studied this question.

synapsesocial.com/papers/69c08b6ba48f6b84677f8843https://doi.org/10.1177/23977914261427854
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