Development of chemical storage tank fire situation awareness model for terminal decision-making requirement

doi:10.16265/j.cnki.issn1003-3033.2024.05.1090

Abstract

Abstract:

To solve the information fusion and situation awareness issues of terminal decision-making groups in emergency rescue of major chemical fires, a fire situation awareness model for large-scale storage tanks was proposed based on the evolution characteristics of the storage tank fire situation and the multi-layer network theory. A network edge weight calculation method based on Bayesian parameter estimation was proposed by developing a chemical storage tank fire situation information set. Node importance and inter-layer correlation coefficient were used to present the connection strength of nodes within the network layer and the correlation strength between network layers, respectively. Moreover, the evolution trend of key situations within and between storage tanks was identified. Then, the evolution process of the fire emergency rescue situation in a tank was analyzed. The results indicated that the situation awareness model based on multi-layer networks can better analyze the fire situation evolution characteristics of large storage tanks. The greater the importance of the node, the faster the fire evolution of the corresponding storage tank. The stronger the correlation between layers, the more significant the evolution trend between adjacent storage tanks.

Key words: chemical storage tank fire, terminal decision-making, situation awareness, emergency rescue, multi-layer network

CLC Number:

X928.7火灾与爆炸事故

ZHU Yi, XIA Dengyou. Development of chemical storage tank fire situation awareness model for terminal decision-making requirement[J]. China Safety Science Journal, 2024, 34(5): 69-74.

Figures/Tables 5

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References 15

[1]	STANTON N, CHAMBERS P R G, PIGGOTT J. Situational awareness and safety[J]. Safety Science, 2001, 39: 189-204.
[2]	SMITH T D, ELDRIDGE F, DEJOY D M. Safety-specific transformational and passive leadership influences on firefighter safety climate perceptions and safety behavior outcomes[J]. Safety Science, 2016, 86: 92-97.
[3]	PAYAM H, MOHAMMAD B, LEILI T, et al. Weighing and prioritization of individual factors affecting the performance of industries firefighters[J]. Fire Safety Journal, 2022, 127: DOI:10.1016/j.firesaf.2021.103512.
[4]	LUOKKALA P, VIRRANAUS K. Developing information systems to support situational awareness and interaction in time-pressuring crisis situations[J]. Safety Science, 2014, 63: 191-203.
[5]	陈珑凯. 基于物联网的化工园区事故态势感知研究[D]. 广州: 华南理工大学, 2015.
	CHEN Longkai. Study on accident situation awareness in chemical industry park based on internet of things[D]. Guangzhou: South China University of Technology, 2015.
[6]	王雪栋, 张明广, 钱城江, 等. 化工园区事故社会群众风险感知动态模拟研究[J]. 中国安全科学学报, 2016, 26(1): 169-174.
	WANG Xuedong, ZHANG Mingguang, QIAN Chengjiang, et al. Dynamic simulation of lay public's perception of risk in chemical industry park[J]. China Safety Science Journal, 2016, 26(1): 169-174.
[7]	NADERPOUR M, LU Jie, ZHANG Guangquan. A situation risk awareness approach for process systems safety[J]. Safety Science, 2014, 64: 173-189.
[8]	OLIVEIRA A C M, BOTEGA L C, SARAN J F, et al. Crowdsourcing, data and information fusion and situation awareness for emergency management of forest fires: the project DF100 Fogo(FD Without Fire)[J]. Computers, Environment and Urban Systems, 2019, 77: 1-9.
[9]	窦珊, 张广宇, 熊智华, 等. 基于多源数据融合的化工园区态势感知[J]. 化工学报, 2019, 70(2): 460-466.
	DOU Shan, ZHANG Guangyu, XIONG Zhihua, et al. Danger situation awareness of chemical industry park based on multiple source data fusion[J]. CIESC Journal, 2019, 70(2): 460-466.
[10]	王秉, 史志勇, 朱菁菁, 等. 面向三元空间的安全态势感知路径[J]. 中国安全科学学报, 2023, 33(4): 15-21.
	WANG Bing, SHI Zhiyong, ZHU Jingjing, et al. Research on safety & security situation awareness path for ternary space[J]. China Safety Science Journal, 2023, 33(4): 15-21.
[11]	彭亚飞, 杨凡德, 张书瑞. 基于概念格的航天任务态势要素提取[J]. 指挥控制与仿真, 2021, 43(6): 34-40.
	PENG Yafei, YANG Fande, ZHANG Shurui. Research on the extraction method of situational elements of space mission based on concept lattice[J]. Command Control & Simulation, 2021, 43(6): 34-40.
[12]	MIKKO K, ALEX B, JAMES P G, et al. Multilayer networks[J]. Journal of Complex Networks, 2014, 2: 203-271.
[13]	徐凤, 朱金福, 陈丹. 基于多层网络的空铁联运双层加权网络结构特性[J]. 复杂系统与复杂性科学, 2022, 20(1): 49-56.
	XU Feng, ZHU Jinfu, CHEN Dan. Structure characteristics of air-rail double-layer weighted network based on multilayer network[J]. Complex Systems and Complexity Science, 2022, 20(1): 49-56.
[14]	吴桐雨, 王健. 基于多层复杂网络的物流枢纽城市多尺度分析及发育评价[J]. 交通运输系统工程与信息, 2019, 19(1): 33-39.
	WU Tongyu, WANG Jian. Multi-scale analysis and development evaluation of logistics hub cities based on multi-layer complex networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(1):33-39.
[15]	胡人元. 信息驱动下危化品火灾事故动态情景构建研究[D]. 廊坊: 中国人民警察大学, 2020.
	HU Renyuan. Research on dynamic scenario construction of hazardous chemical fire accidents under information-driven[D]. Langfang: Chinese People's Police University, 2020.

储罐编号	第1阶段	第2阶段
607号	全液面火灾S₁、浮盘卡盘S₂、罐壁坍塌S₃、地面流淌火S₄、沸溢和喷溅S₅	可燃液体复燃S₆、全液面火灾、罐壁坍塌、地面流淌火、沸溢和喷溅
608号	全液面火灾S₁、浮盘卡盘S₂、罐壁坍塌S₃、地面流淌火S₄、沸溢和喷溅S₅	可燃液体复燃S₆、全液面火灾、罐壁坍塌、地面流淌火、沸溢和喷溅
610号	全液面火灾、浮盘卡盘、罐壁坍塌、地面流淌火	可燃液体复燃、全液面火灾、罐壁坍塌、地面流淌火
609号	呼吸阀起火S₇、罐顶爆炸S₈、全液面火灾、罐壁坍塌、地面流淌火	罐顶爆炸、全液面火灾、浮盘卡盘、罐壁坍塌、地面流淌火