基于N‑K和SNA的高层住宅火灾事故风险因素分析及控制

Risk Factors Analysis and Control of Fire Accidents in HighRise Residential Buildings Based on N‑K and SNA

摘要:

高层住宅火灾安全防控是一个复杂系统问题，从系统层面确定其风险耦合形式及关键风险因素对提升我国高层住宅消防安全水平具有重要意义。为分析高层住宅火灾事故风险因素并提出防控策略，通过收集2015~2023 年我国发生的162起高层住宅火灾较大事故案例，结合专家访谈和已有的事故致因分类模型，将高层住宅火灾事故风险因素分为5类一级风险因素和26个二级风险因素；基于N-K模型求解出风险因素耦合值，将风险耦合形式量化并进行耦合致险性评价；利用社会网络分析（Social Network Analysis，SNA）可视化风险因素间的作用关系，分析其中心度和可达性，挖掘出风险因素的发展态势和诱发其他风险因素出现的可能性；结合N-K和SNA对各风险节点的出度进行修正，确定高层住宅火灾事故的关键风险因素。结果表明：多风险因素耦合导致事故发生的概率较大；火灾事故的起因在较大程度上是居民方的原因，开发商、物业、社区、监管单位四方的风险易使灾情扩大、程度升级；防控开发商-监管单位两风险因素耦合可有效避免事故发生；开发商、社区、监管单位风险因素的出现易连通各风险节点，引发耦合效应；从开发商、物业、社区及监管单位角度出发进行防控是重点。

Abstract:

Fire safety and prevention in high-rise residential buildings is a complex system issue. Identifying risk coupling forms and key risk factors at the system level is crucial for improving fire safety standards in China's high-rise residential buildings. To analyze the risk factors of fire accidents in high rise residential buildings and propose prevention and control strategies, 162 major accident cases that occurred in China's high-rise residential buildings from 2015 to 2023 were collected. Using expert interviews and an existing accident causality classification model, the risk factors of these fire accidents were categorized into 5 primary risk factors and 26 secondary risk factors. Using the N-K model, the risk factor coupling values were calculated, the risk coupling forms were quantified, and a coupling hazard evaluation was conducted. Social Network Analysis (SNA) was employed to visualize the relationships between risk factors, analyzing their centrality and accessibility. This revealed the development trends of the risk factors and assessed the probability of one risk factor triggering the occurrence of others. By integrating N-K and SNA, the out-degree of each risk node was corrected, leading to the identification of the key risk factors for fire accidents in high-rise residential buildings. The results indicated that the coupling of multiple risk factors significantly increased the probability of accidents. The primary cause of fire accidents was largely attributed to residents, while risks associated with developers, property management, communities, and regulatory bodies tended to exacerbate the severity of accidents. Preventing the coupling of risk factors related to developers and regulatory bodies could effectively avoid accidents. Risks from developers, communities, and regulatory bodies tended to connect various risk nodes, triggering a coupling effect. Therefore, prevention and control efforts should focus on developers, property management, communities, and regulatory bodies.