小型堆中窄矩形通道自然循环临界热流密度实验研究

Experimental research on natural circulation CHF in narrow rectangular channels

针对窄矩形通道在换热过程中有较高功率密度的问题,本文为了解决在小型反应堆中的应用,采用所搭建的小型窄矩形自然循环通道,进行实验研究,并结合BP神经网络方法对实验数据进行预测,分析在不同参数工况下临界热流密度随不同参数的变化情况以及不同参数对临界热流密度的影响程度。研究结果表明:质量流量与系统压力对临界热流密度点的影响呈现正相关;出口干度对临界热流密度呈现负相关;且质量流量对临界热流密度的影响程度最大;压力对临界热流密度的影响程度最小。利用相关实验数据,基于影响因素大小,通过BP神经网络方式,建立了适合于自然循环窄通道小堆的模型。BP神经网络算法的预测值与实验值符合良好,误差为10%;Katto模型与实验数据相比误差较大,Zhang公式和拟合公式的误差较小,所建立的临界热流密度模型可作为窄矩形通道自然循环临界热流密度的计算公式。

To address the problem of high power in the heat exchange process of narrow rectangular channels and apply it in small reactors,a small,narrow rectangular natural circulation channel was built for the experiment.The BP neural network method predicts the experimental data and analyzes the variation of critical heat flux with differ-ent parameters under different conditions and the influence of different parameters on critical heat flux.Results re-vealed that the influence of mass flow and system pressure on(critical heat flux density)CHF points was positively correlated,outlet dryness and CHF were negatively correlated,the influence of mass flow on CHF was the greatest,and the influence of pressure on CHF was the smallest.Using relevant experimental data and considering the size of the influencing factors,a model for naturally circulated small piles in a narrow channel was established based on the BP neural network.The predicted value of the BP neural network algorithm was agreed with the experimental val-ue,with an error of 10%;the Katto model has a large error compared with the experimental data,and the error be-tween the Zhang and fitting formulas is small.The established CHF model can be used as the calculation formula for critical heat flux density in the natural circulation of a narrow rectangular channel.