氮气在各种实验室中广泛用作抑制气体和保护气体。一旦氮气泄漏并积聚在这样的密闭空间中,这将给实验人员带来严重威胁。特别是在没有自然风的地下隧道或地下实验室,威胁更加强烈。在这项工作中,以锦屏地下实验室(CJPL)大型液氮罐泄漏扩散为例,对通风设计因素和潜在泄漏因素进行了识别。基于计算流体力学(CFD)研究,新鲜空气入口位置的影响,新鲜空气速度,排气口位置,泄漏孔位置,泄漏孔尺寸,从氮浓度场和氮扩散特性的角度,详细讨论了泄漏氮质量流量对特定环境下氮扩散行为的影响。影响因素参数化,并采用拉丁超立方抽样(LHS)在各因子的指定范围内进行均匀抽样,得到能代表整个样本空间的样本。氮浓度通过数值测量,并按类别测量氮扩散特性。建立了氮浓度预测和氮扩散特征预测的GA-BP-ANN数值回归和分类回归模型。通过使用各种评级指标来评估训练模型的性能,发现模型具有较高的准确率和识别率,表明根据通风因素和潜在泄漏因素预测和确定氮的浓度值和扩散特性是有效的。研究结果可为通风系统的参数化设计提供理论参考。
Nitrogen is widely used in various laboratories as a suppressive gas and a protective gas. Once nitrogen leaks and accumulates in a such confined space, it will bring serious threats to the experimental staff. Especially in underground tunnels or underground laboratories where there is no natural wind, the threat is more intense. In this work, the ventilation design factors and potential leakage factors are identified by taking the leakage and diffusion of a large liquid nitrogen tank in China Jinping Underground Laboratory (CJPL) as an example. Based on computational fluid dynamics (CFD) research, the effects of fresh air inlet position, fresh air velocity, exhaust outlet position, leakage hole position, leakage hole size, and leaked nitrogen mass flow rate on nitrogen diffusion behavior in specific environments are discussed in detail from the perspectives of nitrogen concentration field and nitrogen diffusion characteristics. The influencing factors are parameterized, and the Latin hypercube sampling (LHS) is used to uniformly sample within the specified range of each factor to obtain samples that can represent the whole sample space. The nitrogen concentration is measured by numerical value, and the nitrogen diffusion characteristics are measured by category. The GA-BP-ANN numerical regression and classification regression models for nitrogen concentration prediction and nitrogen diffusion characteristics prediction are established. By using various rating indicators to evaluate the performance of the trained model, it is found that models have high accuracy and recognition rate, indicating that it is effective in predicting and determining the concentration value and diffusion characteristics of nitrogen according to ventilation factors and potential leakage factors. The research results can provide a theoretical reference for the parametric design of the ventilation system.