石油化工厂区可能会因各种原因导致泄漏事故发生，引发一系列次生衍生事故，事故后果极为严重。通过事故统计分析，发现液化烃(在15 °C时，蒸气压大于0.1 MPa的烃类液体及其他类似的液体，包括液化石油气在内，同时还涉及乙烯、乙烷、丙烯等单组分液化烃类)泄漏扩散形成蒸气云，遇到点火源发生蒸气云爆炸后导致火灾是石化厂区最为常见的多米诺事故。然而，目前国家石化厂区建设防火规范和相关研究，都主要从防止火灾热辐射和满足消防操作的角度，规定和研究相关设计参数。此外，对泄漏物质的研究主要集中在二氧化碳、液化氢气、液化石油气和液化天然气等，对液化烃类研究有限。因此，基于CFD模型FLACS开展液化烃气体泄漏扩散和气云爆炸数值仿真，定性和定量评价典型的液化烃类燃料泄漏和爆炸事故危险性，研究常见安全防控措施对液化烃泄漏扩散和气云爆炸的防护作用。主要研究结论如下：

(1) 通过理论分析，将影响液化烃泄漏扩散的原因，在传统的泄漏和环境条件的基础上，提出泄漏条件、几何条件和环境条件三类。参考事故发生规律和挪威风险和应急准备分析标准，讨论了泄漏速率的选取，分析了乙烷、丙烷、丁烷、乙烯和丙烯的泄漏扩散结果，综合气体层流燃烧速度、爆炸极限和密度等因素综合判定乙烯危险性最高。通过泄漏速率和气体组成的正交实验结论，建立了可燃气云体积和泄漏速率与液化烃气体密度的理论预测模型，发现了泄漏气体在高于或低于临界泄漏速率48 kg/s时，由重气驱动与浮力驱动的气体泄漏扩散机制的不同。发现泄漏源附近和泄漏方向上的几何障碍物阻塞率是影响气云形成的关键，乙烯在较低阻塞率储罐组的泄漏，气云体积显著低于阻塞率较高的复杂油气管网。通过理论分析，将风速小于3 m/s的天气定义为微风条件，研究得出微风条件下泄漏气体就会被强烈稀释，特别对于以浮力驱动为主的气体，会大幅降低泄漏危险性。

(2) 基于液化烃泄漏扩散的仿真结果，从气云形成条件和气云分布条件两个方面开展气云爆炸研究。发现随着乙烯气云体积在复杂油气管网内增大，最大爆炸超压(P_max) 增强，当气云高度高于油气管网，爆炸火焰传播到开敞空间后，障碍物对火焰传播的加速作用中止，P_max不再进一步增强。在多种液化烃类中，乙烯层流燃烧速度最快，在当量比为1.2时对应P_max最强，气云爆炸事故危险性最高。研究气云覆盖多个模块的爆炸现象，发现两模块之间的无障碍区域能够有效中断湍流反馈，火焰在几何障碍物内加速，无几何障碍区域减速，因此火焰燃烧速度在两个模块之间呈现加速‒减速‒加速过程。多个模块之间蒸气云爆炸的变化规律，为安全间距效应研究提供了理论依据。

(3) 基于泄漏扩散-爆炸的最危险场景和概率分析方法，研究储罐之间安全间距，模块之间安全间距和防爆墙高度改变对泄漏扩散-爆炸后果的影响。储罐安全间距增大，大幅降低丙烯气云整体浓度和可燃气云体积，减弱爆炸超压。随着油气管网模块之间安全间距从50 m增大到60 m，被保护模块的可燃气云被稀释，气云体积降低。通过超压概率曲线分析得知，安全间距60 m对应的乙烯爆炸超压频率分布显著低于50 m对应的乙烯爆炸超压频率。在重要建筑物或区域前增设防爆墙，能有效降低被保护区域的泄漏扩散-爆炸风险，但需要针对具体场景进行泄漏扩散-爆炸评估，才能确定防爆墙高度参数。

本文的研究结果提供了典型的设计参数和完整的评价方案，对于工程项目风险评估和安全设计有一定借鉴意义。

Leakage accidents may occur in petrochemical plants due to various reasons, resulting in a series of secondary and derivative accidents, and the consequences of the accidents are tremendously serious. By statistical analysis on accidents, it found that the most common domino accidents in the petrochemical plant was that vapor cloud explosion and followed a fire caused by liquefied hydrocarbon leakage and dispersion (Liquefied hydrocarbon refers to hydrocarbon liquids and other similar liquids with a vapor pressure greater than 0.1 MPa at 15 °C, including liquefied petroleum gas, also involving single component such as ethylene, propylene, ethane liquefied hydrocarbon). However, the current national petrochemical plant construction-related fire codes and related studies stipulate the design parameters, were principally from the point of fire operation and fire heat radiation model. Additionally, the research on leakage materials mainly focuses on carbon dioxide, liquefied hydrogen, liquefied petroleum gas, and liquefied natural gas, and research on liquefied hydrocarbons is limited. Therefore, a CFD-based numerical simulation of liquefied hydrocarbon gas leakage, dispersion, and vapor cloud explosion was conducted. The risk of typical liquefied hydrocarbon leaks was evaluated. The protective effect of common safety prevention and control measures on the leakage, dispersion, and vapor cloud explosion of liquefied hydrocarbons was researched. The main conclusions are as follows:

(1) Through theoretical analysis of the causes affecting the leakage and dispersion of liquefied hydrocarbon, three categories of leakage conditions, geometric conditions, and environmental conditions were proposed. Refer to the cases of the accidents and the risk and emergency preparedness analysis code, the selection of leak rate was discussed. Results of leakage and dispersion of the ethane, propane, butane, ethylene, and propylene were analyzed. The ethylene with the highest risk was determined by the factors of laminar burning velocity, explosion limit, and density. The theoretical model, describing the mathematical relationship between the combustible gas cloud volume and leak rate and liquefied hydrocarbon gas density, was established. The critical leakage velocity of liquefied hydrocarbon was defined as 48 kg/s. When the leak rate was higher than or lower than 48 kg/s, the different mechanism of the leakage and dispersion between the gas driven by heavy gas and buoyancy was obtained. The blockage rate of geometric obstacles near the leakage source and in the direction of the leakage played a great role in the formation of the gas cloud. The gas cloud volume in ethylene leak at the tank group with a lower blockage rate was significantly lower than that in the complex oil and gas pipeline network with a higher blockage rate. The wind speed below 3 m/s was the breeze condition was defined theoretically. The research has shown that under the breeze condition, the released gas will be strongly diluted and the leak risk will be momentously reduced.

(2) Based on the simulation results of liquefied hydrocarbon leakage and dispersion, the experiments of gas cloud explosion were carried out from the two aspects of gas cloud formation conditions and gas cloud distribution conditions. It was found that the maximum explosive overpressure (P_max) increased with the increase in the volume of ethylene gas cloud in the complex oil and gas pipe network. When the height of the gas cloud was higher than the oil and gas pipe network, the P_max did not further increase, which proved that obstacles are the main reason for the acceleration of flame propagation. Among various liquefied hydrocarbons, ethylene has the fastest laminar burning velocity, corresponding explosion overpressure on the strongest, and the highest corresponding risk. When the equivalence ratio was 1.2, P_max reached the maximum. It was found that the blank area before the two modules can interrupt the turbulent feedback. The flame accelerates in the geometric obstacle and decelerates in the barrier-free area. Therefore, the flame propagation velocity between the two modules shown a process of acceleration-deceleration-acceleration. The research resulted provide a theoretical basis for the following research on the safety distance effect.

(3) Based on the most dangerous scenario and probability analysis method of leakage, dispersion, and explosion, the effects of safety distance between storage tanks, between modules, and blast wall height on the leakage and dispersion-explosion consequences were studied. With the increase in safety distance between storage tanks, the overall concentration and the volume of propylene gas cloud were significantly reduced, and the explosion overpressure was weakened. As the safety distance between the oil and gas network modules increased from 50 m to 60 m, the combustible gas cloud in the protected module was diluted and the volume of the gas cloud decreased. The overpressure probability curve analysis presented that the overpressure frequency distribution of ethylene explosion corresponding to the safety distance of 60 m was significantly lower than that corresponding to 50 m. A blast wall in front of important buildings or areas can effectively reduce the risk of leakage, dispersion, and explosion in the protected areas. However, the height parameters of a blast wall can only be determined by the assessment of leakage, dispersion, and explosion in specific scenarios.

The research results of this paper provided typical design parameters and a complete evaluation scheme, which can be employed as a reference for risk assessment and safety design of engineering projects.

[1] 王志刚, 蒋庆哲, 董秀成, 等. 中国油气产业发展分析与展望报告蓝皮书（2019—2020）[M]. 北京：中国石化出版社，2020.

[2] Tauseef S M, Abbasi T, Pompapathi V, et al. Case studies of 28 major accidents of fires/explosions in storage tank farms in the backdrop of available codes/standards/models for safely configuring such tank farms[J]. Process Safety and Environmental Protection, 2018, 120: 331–338.

[3] Darbra R M, Palacios A, Casal J. Domino effect in chemical accidents: Main features and accident sequences[J]. Journal of Hazardous Materials, 2010, 183(1–3): 565–573.

[4] Turney R. Flixborough: Lessons which are still relevant today[J]. Loss Prevention Bulletin, 2014.

[5] Pietersen C M. Analysis of the LPG-disaster in mexico city[J]. Journal of Hazardous Materials, 1988, 20: 85–107.

[6] Grim L, Tillema D, Cutchen S, et al. CSB investigation of Chevron Richmond refinery pipe rupture and fire[J]. Process Safety Progress, 2015, 34: 355–359.

[7] CSB. ExxonMobil Refinery Chemical Release and Fire[R]. US: Chemical Safety Board, 2017.

[8] Johnson J. CSB to investigate Philadelphia refinery fire[J]. Chemical & Engineering News, 2019, 97(26): 16.

[9] Coglianese C. Confronting complexity with regulatory excellence: Recommendations in the wake of the philadelphia refinery explosion[J]. SSRN Electronic Journal, 2019, (20-08): 1‒7.

[10] Chou H C, Yeh C T, Shu C M. Fire accident investigation of an explosion caused by static electricity in a propylene plant[J]. Process Safety and Environmental Protection, 2015, 97: 116‒121.

[11] Chang J I, Lin C C. A study of storage tank accidents[J]. Journal of Loss Prevention in the Process Industries, 2006, 19(1): 51–59.

[12] Zhang M, Dou Z, Liu L, et al. Study of optimal layout based on integrated probabilistic framework (IPF): Case of a crude oil tank farm[J]. Journal of Loss Prevention in the Process Industries, 2017, 48: 305–311.

[13] Clough I. The 100 largest losses 1972-2009: Large property damage losses in the hydrocarbon industries[M]. London: Marsh Global Energy Risk Engineering, cop. 2011.

[14] GB 50160-2008. 石油化工企业设计防火规范（2018年版）[S]. 北京：中国计划出版社，2018.

[15] Meroney R, Ohba R, Leitl B, et al. Review of CFD guidelines for dispersion modeling[J]. Fluids, 2016, 1(2): 14.

[16] I Y P, Shu C M, Chong C H. Applications of 3D QRA technique to the fire/explosion simulation and hazard mitigation within a naphtha-cracking plant[J]. Journal of Loss Prevention in the Process Industries, 2009, 22(4): 506–515.

[17] Zhao M, Huang T, Liu C, et al. Leak localization using distributed sensors and machine learning for hydrogen releases from a fuel cell vehicle in a parking garage[J]. International Journal of Hydrogen Energy, 2021, 46(1): 1420–1433.

[18] Shen R, Jiao Z, Parker T, et al. Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review[J]. Journal of Loss Prevention in the Process Industries, 2020, 67: 104252.

[19] Koopman R P, Cederwall R T, Ermak D L, et al. Analysis of Burro series 40-m3 lng spill experiments[J]. Journal of Hazardous Materials, 1982, 6(1–2): 43–83.

[20] Chan S T, Ermak D L. Recent results in simulating LNG vapor dispersion over variable terrain. Revision 1[M]. Atmospheric Dispersion of Heavy Gases and Small Particles. Springer Berlin Heidelberg, 1984.

[21] Puttock J S, Blackmore D R, Colenbrander G W. Field experiments on dense gas dispersion[J]. Journal of Hazardous Materials, 1982, 6(1-2): 13–41.

[22] McQuaid J. Proceedings of the symposium on heavy gas dispersion trials at Thorney Island[M]. Amsterdam: Elsevier, 1985.

[23] Goldwire Jr H, Mcrae T, Johnson G. et al. Desert Tortoise series data report: 1983 pressurized ammonia spills[R]. Lawrence Livermore National Lab., CA(USA); 1985.

[24] Blewitt D, Yohn J, Koopman R. et al. Conduct of anhydrous hydrofluoric acid spill experiments[C]. Proceedings, International Conference on Vapor Cloud Modeling, American Institute of Chemical Engineers. 1987.

[25] Hanna S R, Chang J C, Strimaitis D G. Hazardous gas model evaluation with field observations[J]. Atmospheric Environment Part A, 1993, 27(15): 2265–2285.

[26] NFPA 59A. Standard for the production, storage, and handling of liquefied natural gas (LNG)[s]. Quincy: NFPA, 2019.

[27] Havens J, Spicer T. LNG vapor dispersion prediction with the DEGADIS dense-gas dispersion model. Topical report, April 1988-July 1990. Documentation[R]. Arkansas University, 1990.

[28] Spicer T O, Havens J A, Walker H L. Evaluation of mitigation methods for accidental lng releases: Volume 5/5–using FEM3A for LNG accident consequence analysis[J]. Topical Report for Gas Research Institute, 1997.

[29] Ivings M J, Jagger S F, Lea C J, et al. Evaluating vapor dispersion models for safety analysis of LNG facilities[J]. The Fire Protection Research Foundation, 2007, 44(0): 275.

[30] Fay J A, Zemba S G. Integral model of dense gas plume dispersion[J]. Atmospheric Environment (1967), 1986, 20(7): 1347–1354.

[31] Hankin R K S. Heavy gas dispersion: integral models and shallow layer models[J]. Journal of hazardous materials, 2003, 103(1–2): 1–10.

[32] Bjerketvedt D, Bakke J R, Van Wingerden K. Gas explosion handbook[J]. Journal of Hazardous Materials, 1997, 52(1): 1–150.

[33] Panowicz R, Konarzewski M, Trypolin M, et al. Analysis of criteria for determining a TNT equivalent[J]. Strojniški vestnik-Journal of Mechanical Engineering, 2017, 63(11): 666–672.

[34] Alonso F D, Ferradás E G, Pérez J F S, et al. Characteristic overpressure–impulse–distance curves for vapour cloud explosions using the TNO Multi-Energy model[J]. Journal of hazardous materials, 2006, 137(2): 734–741.

[35] Sari A. Comparison of TNO multienergy and Baker–Strehlow–Tang models[J]. Process Safety Progress, 2011, 30(1): 23–26.

[36] Lees F. Lees' Loss prevention in the process industries: Hazard identification, assessment and control[M]. Butterworth-Heinemann, 2012.

[37] Witlox H W M, Fernández M, Harper M, et al. Verification and validation of Phast consequence models for accidental releases of toxic or flammable chemicals to the atmosphere[J]. Journal of loss prevention in the process industries, 2018, 55: 457–470.

[38] Matsson J. An Introduction to ANSYS Fluent 2020[M]. SDC Publications, 2020.

[39] Gexcon A S. FLACS v10. 9 User’s Manual[M]. Bergen: GexCon A S, 2019.

[40] Moen A, Mauri L, Narasimhamurthy V D. Comparison of k-ε models in gaseous release and dispersion simulations using the CFD code FLACS[J]. Process Safety and Environmental Protection, 2019, 130: 306–316.

[41] Hanna S R, Hansen O R, Dharmavaram S. FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations[J]. Atmospheric Environment, 2004, 38(28): 4675–4687.

[42] Hansen O R, Gavelli F, Ichard M, et al. Validation of FLACS against experimental data sets from the model evaluation database for LNG vapor dispersion[J]. Journal of Loss Prevention in the Process Industries, 2010, 23(6): 857–877.

[43] Middha P, Hansen O R, Storvik I E. Validation of CFD-model for hydrogen dispersion[J]. Journal of Loss Prevention in the Process Industries, 2009, 22(6): 1034–1038.

[44] Middha P, Ichard M, Arntzen B J. Validation of CFD modelling of LH2 spread and evaporation against large-scale spill experiments[J]. International Journal of Hydrogen Energy, 2011, 36(3): 2620–2627.

[45] Schleder A M, Martins M R. Experimental data and CFD performance for CO2 cloud dispersion analysis[J]. Journal of Loss Prevention in the Process Industries, 2016, 43: 688–699.

[46] Xin B, Yu J, Dang W, et al. Dynamic characteristics of chlorine dispersion process and quantitative risk assessment of pollution hazard[J]. Environmental Science and Pollution Research, 2021: 1‒15.

[47] Wang Q, Sun Y, Li X, et al. Process of natural gas explosion in linked vessels with three structures obtained using numerical simulation[J]. Processes, 2020, 8: 52.

[48] li J, Hao H, Shi Y, et al. Experimental and computational Fluid Dynamics study of separation gap effect on gas explosion mitigation for methane storage tanks[J]. Journal of Loss Prevention in the Process Industries, 2018, 55: 359–380.

[49] Ma G, Li J, Abdel-Jawad M. Accuracy improvement in evaluation of gas explosion overpressures in congestions with safety gaps[J]. Journal of Loss Prevention in the Process Industries, 2014, 32: 358–366.

[50] 文虎, 高慧慧, 王秋红, 等. 泄爆口强度对管内天然气爆炸流场的影响仿真[J]. 天然气工业, 2019, 39(8): 126–136.

[51] SKARSBØ L R. An experimental study of pool fires and validation of different CFD fire models[D]. Department of Physics and Technology University of Bergen, 2011.

[52] Middha P, Hansen O R, Grune J, et al. CFD calculations of gas leak dispersion and subsequent gas explosions: Validation against ignited impinging hydrogen jet experiments[J]. Journal of Hazardous Materials, 2010, 179(1–3): 84–94.

[53] Lucas M, Atanga G, Hisken H, et al. Simulating vented hydrogen deflagrations: Improved modelling in the CFD tool FLACS-hydrogen[J]. International Journal of Hydrogen Energy, 2021, 46(23): 12464–12473.

[54] Rengel B, Mata C, Pastor E, et al. A priori validation of CFD modelling of hydrocarbon pool fires[J]. Journal of Loss Prevention in the Process Industries, 2018, 56: 18–31.

[55] Middha P, Hansen O R. Using computational fluid dynamics as a tool for hydrogen safety studies[J]. Journal of Loss Prevention in the Process Industries, 2009, 22(3): 295–302.

[56] Hansen O R, Kjellander M T, Martini R, et al. Estimation of explosion loading on small and medium sized equipment from CFD simulations[J]. Journal of Loss Prevention in the Process Industries, 2016, 41: 382–398.

[57] Dasgotra A, Varun Teja G V V, Sharma A，et al. CFD modeling of large-scale flammable cloud dispersion using FLACS[J]. Journal of Loss Prevention in the Process Industries, 2018, 56: 531–536.

[58] Li J, Ma G, Abdel-Jawad M, et al. Gas dispersion risk analysis of safety gap effect on the innovating FLNG vessel with a cylindrical platform[J]. Journal of Loss Prevention in the Process Industries, 2016, 40: 304–316.

[59] Li J, Ma G, Hao H, et al. Gas explosion analysis of safety gap effect on the innovating FLNG vessel with a cylindrical platform[J]. Journal of Loss Prevention in the Process Industries, 2016, 44: 263–274.

[60] Li J, Ma G, Hao H, et al. Optimal blast wall layout design to mitigate gas dispersion and explosion on a cylindrical FLNG platform[J]. Journal of Loss Prevention in the Process Industries, 2017, 49: 481–492.

[61] Huang Y, Ma G, Li J. Multi-level explosion risk analysis (MLERA) for accidental gas explosion events in super-large FLNG facilities[J]. Journal of Loss Prevention in the Process Industries, 2017, 45: 242–254.

[62] 李静媛, 赵永志, 郑津洋. 加氢站高压氢气泄漏爆炸事故模拟及分析[J]. 浙江大学学报(工学版), 2015, 49(7): 1389–1394.

[63] 王志寰, 李成兵, 周宁. 大型LNG接收站泄漏事故灾害效应分析与预测[J].天然气工业, 2019, 39(5): 145–153.

[64] 张强, 陈国华, 薛永志, 等.甲类仓库戊烷爆炸特性三维模拟及防爆策略[J].华南理工大学学报(自然科学版), 2019, 47(9): 139–146.

[65] 牛志远, 金阳, 孙磊, 等. 预制舱式磷酸铁锂电池储能电站燃爆事故模拟及安全防护仿真研究[J/OL]. 高电压技术，2021: 1–10. https://doi.org/10.13336/j.1003-6520.hve.20201465.

[66] 郑晓云, 陈国明, 付建民, 等. 沼气制油橇装装置的燃爆风险分析与优化设计[J]. 天然气工业, 2019, 39(10): 118–126.

[67] GB50183-2015. 石油天然气工程设计防火规范[s]. 北京：中国计划出版社，2015.

[68] 王秋红，孙艺林，李鑫，等. 乙烯储罐气体泄漏诱发蒸气云爆炸的数值模拟[J]. 爆炸与冲击，2020, 40(12): 121–133.

[69] Ferrara G, Di Benedetto A, Salzano E, et al. CFD analysis of gas explosions vented through relief pipes[J]. Journal of Hazardous Materials, 2006, 137(2): 654‒665.

[70] Hjertager B H. Computer Simulation of Turbulent Reactive Gas Dynamics[J]. Modeling, Identification and Control, 1984, 5(4):211–236.

[71] Hjertager B H. Computer modeling of turbulent gas explosions in complex 2D and 3D geometries[J]. Journal of Hazardous Materials, 1993, 34(2): 173–197.

[72] Arntzen B J. Modelling of turbulence and combustion for simulation of gas explosions in complex geometries[D]. Trondheim: Norges teknisk-naturvitenskapelige universitet, 1998.

[73] Scheiner B J, Jordan C E, Kuchta J M, et al. Investigation of fire and explosion accidents in the chemical, mining, and fuel-related industries: a manual[M]. US Department of the Interior, Bureau of Mines, 1985.

[74] Launder B E, Spalding D B. The numerical computation of turbulent flows[J]. Computer Methods in Applied Mechanics and Engineering, 1974, 3: 269‒289.

[75] Kuo K K. Principles of combustion[M]. New York: Wiley, 1986.

[76] Bray K N C. Studies of the turbulent burning velocities[J]. Proceedings of the Royal Society of London, Series A: Mathematical and Physical Sciences. 1990, 431(1882): 315‒335.

[77] Abdel-Gayed R G, Bradley D, Lawes M. Turbulent burning velocities: a general correlation in terms of straining rates[J]. Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences, 1987, 414(1847): 389‒413.

[78] Patankar S. Numerical heat transfer and fluid flow[M]. London: Taylor & Francis, 2018.

[79] Hjertager B H. Simulation of transient compressible turbulent reactive flows[J]. Combustion Science and technology, 1982, 27(5‒6): 159‒170.

[80] Bakke J R, Hjertager B H. The effect of explosion venting in obstructed channels[J]. Modeling and simulation in engineering, 1986: 237–241.

[81] Kee R J, Miller J A, Jefferson T H. CHEMKIN: A general purpose, problem-independent, chemical kinetics code package[J]. SANDIA Report SAND80–8003, Sandia National Laboratories, Albuquerque, NM, 1980.

[82] Hansen O R, Gavelli F, Davis S G, et al. Equivalent cloud methods used for explosion risk and consequence studies[J]. Journal of Loss Prevention in the Process Industries, 2013, 26(3): 511–527.

[83] Atkinson G, Cowpe E, Halliday J, et al. A review of very large vapour cloud explosions: Cloud formation and explosion severity[J]. Journal of Loss Prevention in the Process Industries, 2017, 48: 367–375.

[84] NORSOK Z-013. Risk and emergency preparedness analysis[S]. Oslo: Norwegian Technology Standards Insfitufion, 2001.

[85] Grachev A A, Andreas E L, Fairall C W, et al. The critical Richardson number and limits of applicability of local similarity theory in the stable boundary layer[J]. Boundary-layer meteorology, 2013, 147(1): 51‒82.

[86] Lea C J, Ledin H S. A review of the state-of-the-art in gas explosion modelling[M]. Health and Safety Laboratory Buxton, UK, 2002.

[87] Zhang S, Zhang Q. Influence of geometrical shapes on unconfined vapor cloud explosion[J]. Journal of Loss Prevention in the Process Industries, 2018, 52: 29–39.

[88] Li J, Abdel-Jawad M, Ma G. New correlation for vapor cloud explosion overpressure calculation at congested configurations[J]. Journal of Loss Prevention in the Process Industries, 2014, 31(1): 16–25.

[89] Wang Q, Sun Y, Shu C M, et al. Effect of separation distance on gas dispersion and vapor cloud explosion in a storage tank farm determined using computational fluid dynamics[J]. Journal of Loss Prevention in the Process Industries, 2020, 68: 104282.

[90] NFPA 30. Flammable and combustible liquids code[s]. Quincy: National Fire Protection Association, 2018.

[91] NFPA 58. Liquefied petroleum gas code[s]. Quincy: National Fire Protection Association, 2020.

[92] Espinosa S N, Jaca R C, Godoy L A. Thermal effects of fire on a nearby fuel storage tank[J]. Journal of Loss Prevention in the Process Industries, 2019, 62: 103990.

[93] Gavelli F, Davis S G, Hansen O R. Evaluating the potential for overpressures from the ignition of an LNG vapor cloud during offloading[J]. Journal of Loss Prevention in the process industries, 2011, 24(6): 908‒915.

[94] 任少云, 夏登友. 火场条件下相邻汽油罐油蒸汽泄漏及爆炸规律[J]. 爆炸与冲击, 2019, 39(7): 12–21.

[95] Vyazmina E, Jallais S. Validation and recommendations for FLACS CFD and engineering approaches to model hydrogen vented explosions: Effects of concentration, obstruction vent area and ignition position[J]. International journal of hydrogen energy, 2016, 41(33): 15101‒15109.

[96] Ibrahim S S, Masri A R. The effects of obstructions on overpressure resulting from premixed flame deflagration[J]. Journal of Loss Prevention in the Process Industries, 2001, 14(3): 213‒221.

[97] Tauseef S M, Rashtchian D, Abbasi T, et al. A method for simulation of vapour cloud explosions based on computational fluid dynamics (CFD)[J]. Journal of Loss Prevention in the Process Industries, 2011, 24(5): 638‒647.

[98] Na'inna A M, Phylaktou H N, Andrews G E. The acceleration of flames in tube explosions with two obstacles as a function of the obstacle separation distance[J]. Journal of Loss Prevention in the Process Industries, 2013, 26(6): 1597‒1603.