To numerically investigate the flow and heat transfer characteristics of a water/Al₂O₃ nanofluid in a double-pipe helical coil heat exchanger, we simulated a two-phase Eulerian model to predict the heat transfer coefficient, Nusselt number, and pressure drop at various concentrations (i.e., volume fraction) and under diverse flow rates at the steady state. In this simulation, we used the k-epsilon turbulence model with an enhanced wall treatment method. The performance factor of the nanofluid was evaluated by accounting for the heat transfer and pressure drop characteristics. As a result, the heat transfer was enhanced by increasing the nanofluid concentration. The 1.0 vol.% nanofluid (i.e., the highest concentration) showed a heat transfer coefficient 1.43 times greater than water and a Nusselt number of 1.38 times greater than water. The pressure drop of nanofluids was greater than that of water due to the increased density and viscosity induced using nanoparticles. Based on the relationship between the Nusselt number and pressure drop, the 1.0 vol.% nanofluid was calculated to have a performance factor of 1.4 relative to water, indicating that the enhancement rate in heat transfer performance was greater than that in the pressure drop. In conclusion, the Al₂O₃ nanofluid shows potential as an enhanced working fluid in diverse heat transfer applications.

Boiling heat transfer, utilizing latent heat during phase change, has widely been used due to its high thermal efficiency and plays an important role in existing and next-generation cooling technologies. The most critical parameter in boiling heat transfer is critical heat flux (CHF), which represents the maximum heat flux a heated surface can sustain during boiling. CHF is primarily influenced by the wicking performance, which governs liquid supply to the surface. This study experimentally and numerically analyzed the wicking performance of micropillar structures at various temperatures (20–95 °C) using distilled water as the working fluid to provide fundamental data for CHF prediction. Infrared (IR) visualization was used to extract the wicking coefficient, and the experimental data were compared with computational fluid dynamics (CFD) simulations for validation. At room temperature (20 °C), the wicking coefficient increased with larger pillar diameters (D) and smaller gaps (G). Specifically, the highest roughness factor sample (D04G10, r = 2.51) exhibited a 117% higher wicking coefficient than the lowest roughness factor sample (D04G20, r = 1.51), attributed to enhanced capillary pressure and improved liquid supply. Additionally, for the same surface roughness factor, the wicking coefficient increased with temperature, showing a 49% rise at 95 °C compared to 20 °C due to reduced viscous resistance. CFD simulations showed strong agreement with experiments, with error within ±10%. These results confirm that the proposed numerical methodology is a reliable tool for predicting wicking performance near boiling temperatures.