A spectral-statistical analysis of heat transfer in melting micropolar ternary hybrid nanoflows

Abstract

Accurately modeling transport phenomena in melted nanofluids is a pivotal challenge for advancing technologies like high-density electronic cooling due to the strong coupling between phase change, nanoparticle dynamics, and external fields. This study introduces a novel hybrid framework that synergistically combines spectral collocation methods with multiple linear regression analysis. This framework is applied to the specific case of a magnetized, radiative ternary hybrid nanofluid past a shrinking cylinder. Current results reveal that increases in nanoparticle volume fractions escalates angular velocity while diminishing linear velocity and temperature. The micropolar factor reduces the magnitude of the Nusselt number. Enhancing melting at the cylindrical surface inhibits heat transmission and drag force. Regression analysis further identifies shrinkage and radiation as the primary controllers of thermal efficiency, while the magnetic parameter exerts dominance over drag force in this melting regime. This framework provides a powerful diagnostic tool for designing complex thermal systems where multiple physics interact.