HFE-7100工质稳态临界沸腾传热实验研究

Experimental Study on Steady-state Critical Pool Boiling Heat Transfer of HFE-7100

池沸腾临界热通量是沸腾相变传热的重要参数,决定了相变换热器件的推广应用。表面粗糙度和饱和压力对沸腾传热边界层分布、表面铺展润湿及工质动力学特性具有重要影响,进而对临界热通量作用显著。本文对HFE-7100工质在4种不同粗糙度的铜基表面(0.019、0.205、0.311和0.587μm)条件及在不同饱和压力(0.07、0.10、0.15及0.20 MPa)工况下的池沸腾稳态临界状态下的传热及可视化实验进行了研究。对表面粗糙度及饱和压力对稳态临界沸腾的影响机制进行了分析,并考察了临界热通量预测模型对临界热通量的预测准确性。可视化研究表明,临界状态下的沸腾气液两相工质由小气泡、大气泡、气柱及蘑菇状气团组成,而在过渡状态下,沸腾表面会形成非平滑气膜,并不断分离出气泡。同时传热数据表明,表面粗糙度及饱和压力的增加能使表面临界热通量得到提升。相比而言,Bailey等建立的临界热通量预测模型能相对准确地预测HFE-7100工质沸腾临界热通量数据。为进一步提升预测准确度,建立了临界热通量无因次参数K预测经验关联式,其预测值与本实验及文献实验数据吻合较好。

Critical heat flux(CHF)is an important parameter for pool boiling,which determines the popularization and application of heat transfer devices.The surface roughness and saturated pressure have significant effects on the distribution of heat transfer boundary layer,the ability of working liquid spreading and dynamic properties,so that have a major impact on CHF of pool boiling.An experimental visualization and heat transfer study on CHF of HFE-7100 as working fluid on copper surfaces with various surface roughnesses(0.019,0.205,0.311 and 0.587μm)under different pressures(0.07,0.10,0.15 and 0.20 MPa)has been conducted.The effect of surface roughness and pressure on CHF of pool boiling was analyzed,and the accuracy of CHF predictive model was also compared.The visualization results show that two-phase working fluid at boiling critical state is composed of small bubbles,large bubbles,vapour column and mushroom vapour,while non-flat vapour film at transitional state will cover the surface and inject bubbles.It also can be found that both surface roughness and saturated pressure can enhance CHF of pool boiling.Compared with other predictive models,CHF correlation of Bailey et al.can predict the critical boiling heat flux of HFE-7100 relatively accurately.To further improve the prediction accuracy,the new empirical correlation for CHF dimensionless K was developed.The predicted results are in good agreement with our and other literatures’experimental data.