小型堆中窄矩形通道自然循环临界热流密度实验研究OA北大核心CSTPCD

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.