A sensitivity analysis on thermal conductivity of Al2O3-H2O nanofluid: A case based on molecular dynamics and support vector regression method

The current study examines the sensitivity study of the thermal conductivity of water-based alumina nanofluids with variations in concentration, sphericity, and temperature. Thermal conductivity data of alumina nanofluids were obtained by simulation using the non-equilibrium molecular dynamics method with the parameters of nanoparticle volume fraction (1.24-6.2%), particle sphericity (0.6975-1.0), and temperature (290-360 K). Volume fraction and temperature have been discovered to have a major effect on the thermal conductivity of nanofluids, but sphericity should also be taken into consideration. Further, for parameter sensitivity analysis, a support vector machine regression model of thermal conductivity versus parameters was created with a coefficient of determination up to 0.98. The findings show that an Al2O3-H2O nanofluid's thermal conductivity increases with temperature and volume fraction while decreasing with sphericity. Temperature, sphericity, and volume fraction are the variables that are most sensitive to modification, according to a sensitivity analysis. A change in thermal conductivity of up to 4 % can occasionally be brought on by temperature differences of merely 1 %. The use of spherical particles makes it possible for the thermal conductivity of the nanofluid to be more stable, and the sensitive volume fraction region that can cause thermal conductivity to fluctuate across a large range is between 2.5 % and 5.5 %.