The critical heat flux (CHF) of minichannel heat sinks is crucial, as it helps prevent thermal safety incidents and equipment failure. However, the underlying mechanisms of CHF in minichannels remain poorly understood, and existing CHF prediction models require further refinement. This study systematically investigates the characteristics and influencing factors of critical heat flux (CHF) in rectangular minichannels through combined experimental and theoretical approaches. Experiments were conducted using microchannels with hydraulic diameters ranging from 0.5 to 2.0 mm, with ethanol employed as the working fluid. Key parameters-including mass flux, channel geometry, system pressure, and inlet subcooling-were analyzed to assess their influence on CHF. Results indicate that CHF increases with mass flux; however, the increase rate diminishes under higher mass flux. Larger channel dimensions significantly enhance CHF by delaying liquid film dryout. System pressure further improves CHF by reducing bubble detachment frequency and promoting flow stability. Increased inlet subcooling enhances CHF by delaying the onset of nucleate boiling and improving convective heat transfer. Four classical CHF prediction models were evaluated, revealing significant overprediction-up to 148.69% mean absolute error (MAE)-particularly for channels with hydraulic diameters below 1.0 mm. An ANN deep learning model was developed, achieving a reduced MAE of 8.93%, with 93% of predictions falling within ±15% error. This study offers valuable insights and a robust predictive model for optimizing microchannel heat sink performance in high heat flux applications.
Deng et al. (Fri,) studied this question.