清华大学学报（自然科学版）2025，Vol.65Issue(4)：644-654,11.DOI:10.16511/j.cnki.qhdxxb.2024.27.045
集聚型传统村落火灾蔓延模型构建与路径分析
Construction and path analysis of fire spread models in traditional village clusters:A case study of Hongcun in Anhui province
摘要
Abstract
[Objective]Fire risk has consistently posed a significant challenge in traditional villages owing to their diverse layouts and architectural elements,complex geographical environments,and the inherent flammability of building materials.Most research on fire spread models predominantly focuses on individual buildings or forest fires,neglecting the unique conditions of traditional villages.Safety concerns also limit field studies.Therefore,it is crucial to study fire spread dynamics in Huizhou's traditional villages to develop a quantitative model that enhances both fire safety and emergency response capabilities in these communities.[Methods]This paper constructs a disaster field model using cellular automata to simulate fire spread in village conditions,considering factors like fire dynamics,environmental characteristics,building materials,and layout considerations.The model was validated using the Miaozhai fire incident in Wenquan village,Jianhe county,Guizhou province(February 2016),analyzing how ignition points,wind speeds,and wind directions influenced potential ignition sites,spread paths,and impact zones.Computer simulations were employed to mitigate the risks associated with live-fire experiments,enhancing simulation efficiency.By incorporating multiple influencing factors into the prediction framework,this approach models how fires spread through village environments,using initial conditions regarding village elements and fire states to create visual data of fire spread patterns.However,most studies utilizing cellular automata primarily address forest fires,making them unsuitable for traditional villages.This paper specifically investigates Hongcun,a dense village in Anhui province,and proposes a model tailored to its unique wildfire risks,applicable to similar settings in the region.[Results]Findings indicate that simulated outcomes align closely with real-world observations,confirming the method's feasibility.Fires follow distinct pathways depending on different ignition sources,and densely clustered buildings are more susceptible to extensive fire spread than less populated regions throughout the respective timelines analyzed herein.Layout configurations significantly influence both the paths flames take and the extent of their spread after ignition.This variability is influenced by how structures are distributed over time.Higher building densities are linked to faster fire spread,especially when wind plays a crucial role in determining how far the fire reaches.Wind direction significantly influences the path of the fire,largely pushing it downwind orientations and away from the point of ignition.However,with prevailing easterly or southerly winds,the fire range is considerably reduced,limiting the overall local impact despite ongoing combustion taking place nearby.Conversely,strategically placed roadways and water systems effectively slow down fire progression and limit its lateral spread.This helps mitigate threats beyond the immediate area affected by the fire,protecting surrounding locations from the phenomena previously discussed.[Conclusions]The developed modeling framework offers detailed analysis for assessing risks in clustered traditional settlements,facilitating informed decision-making.It supports the implementation of preventative measures,including hazard identification protocols and isolation strategies,specifically targeting identified vulnerabilities.This framework provides valuable insights for future planning,optimizing firefighting resources allocated and ensuring sustainable development practices are maintained.关键词
传统村落/元胞自动机/火灾蔓延/模型构建/蔓延路径/集聚型布局Key words
traditional villages/cellular automata/fire spread/model construction/spreading path/agglomeration layout分类
资源环境引用本文复制引用
吴运法,王岩青,陈萨如拉,陈泽昊,丁超..集聚型传统村落火灾蔓延模型构建与路径分析[J].清华大学学报（自然科学版）,2025,65(4):644-654,11.基金项目
国家自然科学基金面上项目(52478001,52476097) （52478001,52476097）
安徽省高校省级自然科学研究重点项目(2024AH050240) （2024AH050240）
国家消防救援局科技计划(2023XFLR45) （2023XFLR45）
安徽省社会科学创新发展研究课题(2023CX119,2023CX084) （2023CX119,2023CX084）
