建筑火灾中人员疏散响应过程推理与评估模型研究

为了预防建筑火灾发生和减少火灾中人员的伤亡，利用消防大数据分析技术和贝叶斯网络分析方法，研究了建筑火灾发展过程及人员疏散响应过程的推理与动态评估方法。通过对建筑消防设施响应状态和火灾中人员心理和行为特征的分析，探讨了火灾阶段划分方法和人员疏散行为的分类，提出了火灾中人员伤亡的轨迹交叉理论，进而构建了基于贝叶斯网络的建筑火灾动态风险和人员疏散安全评估框架。分别探讨了建筑火灾发展、人员疏散响应等2 条研究主线的推理过程，探讨了疏散条件评估过程。研究表明，该模型可通过对建筑特征、消防设施状态信息以及人员响应信息等消防大数据进行融合，实现火灾中人员疏散响应过程推理与动态风险评估，从而提高建筑消防安全管理水平

Research on evacuation response process reasoning and assessment model in building fire

In order to prevent building fires and reduce casualties in fires, reasoning and dynamic evaluation methods of building fire development process and evacuation response process are studied by using fire big data analysis technology and Bayesian network analysis method. Through the analysis of the response state of building fire fighting facilities and the psychological and behavioral characteristics of occupants in fire, the method of fire stage division and the classification of evacuation behavior are discussed and the trajectory intersection theory of casualties in fire is put forward, and framework on fire dynamic risk and evacuation safety assessment based on Bayesian network is constructed. The reasoning process of building fire development and evacuation response are discussed respectively, and the evacuation condition assessment process is discussed Research shows that the model can fuse large fire data such as building characteristics, fire facility status information and occupant response information, evacuation response process reasoning and dynamic risk assessment model in building fire are realized, so as to improve the level of building fire safety management.