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<p>This study presents a thermal analysis that employs the Taguchi orthogonal experimental method (<i>L</i><sub>25</sub>(5<sup>5</sup>) design) to identify key parameters in electrostatic spray cooling. A quadratic regression model via Box–Behnken design analyzes main effects and interactions. Multi-objective optimization using RSM optimizes charging voltage, flow rate, and mixing ratio to maximize critical heat flux (CHF) and minimize cooling non-uniformity (CNU). The results indicate that the control of spray pattern by charging voltage has a nonlinear impact on CHF (significantly increasing in later stages) and CNU (decreasing initially before rising). Increasing the working fluid flow rate and mixing ratio enhances the transport capacity and thermal properties of the working fluid, leading to an almost linear increase in CHF. However, this also results in a rise in surface temperature upon reaching CHF, consequently linearly increasing CNU. The interaction between working fluid flow rate and mixing ratio exhibits a highly significant synergistic enhancement effect on both CHF and CNU, while the interaction between charging voltage and mixing ratio shows a significant effect on suppressing CNU. The interaction effect between charging voltage and working fluid flow rate is not significant due to charge dilution effects. The optimal key parameter combination identified is a charging voltage of 8&#xa0;kV, a working fluid flow rate of 30&#xa0;mL&#xa0;h<sup>−1</sup>, and a mixing ratio of 45%, yielding a CHF of 24.51&#xa0;W&#xa0;cm<sup>−2</sup> (error 5.51%) and a CNU of 3.25&#xa0;°C (error 4.97%). This research provides a calorimetry-based insight into the optimization of electrospray cooling.</p>

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Thermal analysis and synergistic mechanisms of heat transfer performance in electrospray cooling systems

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Yifan Liu,
  • Junxing Hou,
  • Yuqi Sun,
  • Yihang Wang,
  • LingYu Hu

摘要

This study presents a thermal analysis that employs the Taguchi orthogonal experimental method (L25(55) design) to identify key parameters in electrostatic spray cooling. A quadratic regression model via Box–Behnken design analyzes main effects and interactions. Multi-objective optimization using RSM optimizes charging voltage, flow rate, and mixing ratio to maximize critical heat flux (CHF) and minimize cooling non-uniformity (CNU). The results indicate that the control of spray pattern by charging voltage has a nonlinear impact on CHF (significantly increasing in later stages) and CNU (decreasing initially before rising). Increasing the working fluid flow rate and mixing ratio enhances the transport capacity and thermal properties of the working fluid, leading to an almost linear increase in CHF. However, this also results in a rise in surface temperature upon reaching CHF, consequently linearly increasing CNU. The interaction between working fluid flow rate and mixing ratio exhibits a highly significant synergistic enhancement effect on both CHF and CNU, while the interaction between charging voltage and mixing ratio shows a significant effect on suppressing CNU. The interaction effect between charging voltage and working fluid flow rate is not significant due to charge dilution effects. The optimal key parameter combination identified is a charging voltage of 8 kV, a working fluid flow rate of 30 mL h−1, and a mixing ratio of 45%, yielding a CHF of 24.51 W cm−2 (error 5.51%) and a CNU of 3.25 °C (error 4.97%). This research provides a calorimetry-based insight into the optimization of electrospray cooling.