摘要
为提高海底隧道火灾搜索效率,基于隧道火灾情景分析,建立时间最短的火灾救援搜索优化模型。首先,考虑海底隧道结构特点和CO浓度对救援效果的影响,给出模型的目标函数与限制条件,提升模型的适用性。然后,改进蚁群优化算法(ACA)的邻接矩阵和启发式函数确立规则,以克服搜索网络复杂和路径选择策略单一的问题,并求解模型。最后,以翔安海底隧道火灾为例进行模拟。结果表明,使用该模型在实现路径最短目标的同时,能优先对CO浓度较高的点进行救援搜索,降低CO对滞留人员的伤害。
To improve fire rescue search efficiency in subsea tunnel fire,a search optimization model was built based on tunnel fire scenario analysis. To enhance the applicability of the model,subsea tunnel construction features and effect of CO concentration on rescue activities were taken into account and an objective function and constraints were designed for the model. To avoid a search network of complexity and a path choosing strategy characterized by having a one-track mind,the adjacent matrix and heuristic function of ACA were improved. The model was solved. Taking Xiang'an subsea tunnel fire as an example,a simulation was made. The results show that the following can be achieves by means of the model: finding the shortest path,ensuring points with higher CO volume fraction get searched first,and prevent severe damage by CO to the stranded personnel.
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2016年第2期56-61,共6页
China Safety Science Journal
基金
国家自然科学基金资助(51304051)
福建交通运输科技发展项目(201441)
关键词
海底隧道火灾
救援搜索
优化建模
CO浓度
改进蚁群算法(ACA)
subsea tunnel fire
rescue search
optimization modeling
CO concentration
im proved ant colony algorithm(ACA)