化工园区Na-Tech事件定量风险评价与防控体系评述

doi:10.16085/j.issn.1000-6613.2018-2361

摘要/Abstract

摘要：

Na-Tech（natural-technological）事件是典型的HILP（high-impact low-probability）事件，近年来时有发生，尤其是在危险源高度集中的化工园区。Na-Tech事件演化过程和机理的高度复杂性，使其成为风险评价领域的研究难点。对Na-Tech事件统计文献进行分析，理清最频发的自然灾害类别、最脆弱的设备类型及其致损模式等特性和规律，进一步探究Na-Tech事件演绎过程，包括自然灾害和技术灾害。对当前文献中Na-Tech事件定量风险评价方法进行深入剖析，指出自然灾害与技术灾害的设备致损概率计算是其核心问题。从土地使用规划，设备完整性、鲁棒性与本质安全工艺，安全防护设施，安全教育、管理与合作，事故应急响应，灾后恢复与重建等六方面探讨了Na-Tech事件防控体系。指出自然灾害条件下的设备易损性和多致灾因子耦合作用是Na-Tech事件研究的突破方向，也是进行定量风险评价的关键环节。

关键词: 防控体系, 定量风险评价, 多米诺效应, 化工园区, Na-Tech事件

Abstract:

Na-Tech event is a typical HILP (high-impact low-probability) event that has occurred in recent years, especially in Chemical Industry Park with high concentration of hazards. The complexity of the evolution process and mechanism of Na-Tech event makes it a difficult problem in the field of risk assessment. This paper first analyzes the Na-Tech event statistics literatures, clarifies the characteristics and laws of the most frequent natural disaster categories, the most vulnerable equipment types and their damage modes, and further explores the Na-Tech event deduction process, including the natural disaster and technical disaster. Then, the quantitative risk assessment methods for Na-Tech event in the current literatures are deeply analyzed, and it is pointed out that the calculation of equipment damage probability of natural disaster and technical disaster is the core problem. In addition, the Na-Tech event prevention and control system is discussed from six aspects: land use planning, equipment integrity, robustness and intrinsic safety technology, safety protection facilities, safety management, emergency response, post-disaster restoration and reconstruction. Finally, it is pointed out that the vulnerability of equipment under natural disasters and the coupling effect of multi-hazard factors are the breakthrough direction of Na-Tech research, and the key process of quantitative risk assessment.

Key words: pre-control system, quantitative risk assessment, Domino effect, Chemical Industry Park, Na-Tech event

中图分类号:

TQ086
X937

黄孔星, 陈国华, 曾涛, 胡昆. 化工园区Na-Tech事件定量风险评价与防控体系评述[J]. 化工进展, 2019, 38(07): 3482-3494.

Kongxing HUANG, Guohua CHEN, Tao ZENG, Kun HU. Review of quantitative risk assessment and pre-control system of Na-Tech event in Chemical Industry Park[J]. Chemical Industry and Engineering Progress, 2019, 38(07): 3482-3494.

图/表 4

图1 Na-Tech事件演绎流程

表1 Na-Tech事件定量风险评价基本框架[26]

序号	步骤	需求
1	外部事件特征分析	表征自然灾害频率和强度的参数
2	目标设备识别	考虑的目标设备目录
3	损坏状态和参考场景识别	损坏状态的定义；事件树分析
4	损伤概率计算	设备损伤模型
5	参考场景后果评估	后果分析模型
6	可能事件组合识别	可能事件组合的集合
7	每种组合概率计算	事件组合的概率
8	每种组合后果计算	整体脆弱性地图
9	风险指数计算	整体风险指数

表2 自然灾害设备易损性模型

灾种	来源	易损性分析方法及其适用性、准确度、优缺点	致损概率（参数）表征
地震	Lanzano等^[61]	通过数据统计分析，确定峰值地面加速度PGA与埋地管道泄漏频率关系，绘制易损性曲线，用Probit模型表征。该方法对不同结构类型管道的致损程度进行了细化，能分析多情景的易损性，但准确度受统计数据质量的影响较大。	$Y = k p, 1 + k p, 2 l n V$
	Pineda-Porras等^[62]	用单位长度管道所需修复的数目，即修复率（repair rate，RR）表征管道受损情况。该方法简洁高效，但是不同地震强度参数表征的易损性结果差异较大。	$R R = a × I M b$
	O'Rourke等^[58]和ALA^[59,60]	通过数据统计分析，利用逻辑回归等方法，建立不同震害强度下储罐不同致损程度的经验易损性曲线。该方法能够直观呈现储罐在不同存储状态下的易损性，但是没有区分锚固和非锚固情况，并且判别致损程度的依据主观性太强。	$P d s x = e x p (β 0 + β 1 x) 1 + e x p (β 0 + β 1 x)$
	Berahman等^[63]	根据数据库统计信息，利用Bayesian参数评估技术，建立设备地震易损性计算模型。该方法在极限状态方程中同时考虑了统计和模型的不确定性问题，准确度较高，但是模型复杂，需要大量的数学计算。	$F ? (q) = ∫ g (r; θ; q) ≤ 0 f (r) φ (ε 1) φ (ε 2) f (θ) d r d ε 1 d ε 2 d θ$
	Salzano等^[64]	通过数据统计，确定参数分布规律，利用Probit模型表征储罐的致损概率。该方法简单易行，但是模型的系数与统计数据数量和质量直接相关，不同学者统计得出的易损性曲线存在一定差异。	$P r D S = k 1 + k 2 l n (P G A)$
	孙建刚等^[65]	考虑结构和地震荷载的随机性，用设备可靠性的方法，结合串联可靠性表达式，分析储罐易损性。该方法从储罐的多种失效模式进行易损性研究，科学性更强，准确度较高。	$P f = 1 - 1 - P (F 1) × ∏ i = 2 n 1 + (u 0 - 1) × P (F i)$ $u 0 = 0.06 I 0 + 0.30$
洪水、海啸	Landucci等^{[47,48,49,66]}	建立简化力学模型，用最大水深和最大流速两个参数表征洪水或海啸的强度，考虑常压立式储罐和卧式储罐参数特性，推导失效概率方程。该方法从力学的角度建立极限状态方程，适用于非锚固储罐的分析，但是没有考虑不同的失效模式，并且需要确定的变量参数多。	常压立式储罐： $C F L v = (ρ w k w 2 v w 2 + ρ w g h w - p c r) / ρ f g H$ $P c r = J 1 C + J 2$ , $ψ = (C F L - φ m i n) / (φ m a x - φ m i n)$ 卧罐： $C F L h = ρ r e f A ρ l - ρ v ? (h w - h c) + ρ r e f B - ρ v ρ l - ρ v$ $v w, c = E ? (h w - h c - h m i n) F$ $若 v w ≥ v w, c, ψ = 1;$ $若 v w < v w, c, ψ = (C F L - φ m i n) / (φ m a x - φ m i n)$
	Basco等^[67]	建立力学模型，根据碎片和材料特性分析设备受碎块冲击的失效概率。该方法对碎块进行了极大简化，没有考虑碎块形状的影响，与实际场景存在较大差异，精确度不高。	$J = u 02 σ D θ m p r p 2$ $Y = k p 1 + k p 2 l n J$
	Khakzad等^[68]	根据储罐浮离、壳壁屈曲、滑移3种失效模式的力学模型，通过逻辑回归方法分析洪水易损性，利用贝叶斯网络对各类失效模式进行组合。该方法适用于大型常压非锚固储罐的分析，逻辑回归的方法考虑了共因失效和条件相关性，分析结果准确度高，科学性强，但是模型复杂，计算量大。	$P (s) = e ψ (s) 1 + e ψ (s)$ $ψ (s) = β l 0 + β l 1 s$
雷击	Necci等^[69]	基于电弧侵蚀模型（Arc Erosion Modeling），依据峰值电流强度和雷击电荷两个参数的概率分布函数，计算设备雷击后的损伤概率。该方法能够快速计算致损概率，但是没有考虑各类防雷设施的作用，评价的结果会高于实际场景。	$l n P d = 0.8944 - 0.908 l n t$ $D h, a v = 8.5 × 10 - 3 t 2 - 6.6 × 10 - 3 t + 5.23$ $P D D = ∑ i P d, i ? S i S t o t$
火山喷发	Milazzo等^[70]	根据阿基米德原理（Archimedes Principle）与欧拉方法（Eulers Method）建立火山灰与外浮顶罐之间的力学关系，推导罐顶下沉与倾覆的极限状态方程。该模型简洁高效，但在实际应用中，还有更多的参数需要考虑，包括火山喷发的频率和强度、风向、目标储罐与火山口的距离等。	$浮顶罐罐顶下沉 : h = ρ l i q u i d ρ a s h (δ - δ r o o f)$ 浮顶罐罐顶倾覆（浮顶保持稳定的条件为z_M>z_B）： $z M - z B = R 2 4 δ i m m - δ i m m 2$
	Milazzo等^[71]	类比填料塔中压降的原理，推导火山灰导致过滤系统压降的计算公式，得出计算过滤系统失效时间和火山灰浓度超越概率曲线的方法。该方法假定火山灰浓度是定值，忽略了复杂气象条件的影响，评价结果误差较大。	$p 0 - p L L = 150 μ D p 2 ρ ? (1 - ε) 2 ε 3 G 0 + 1.75 D p ρ ? 1 - ε ε 3 G 02$ $t = m a s h / q a i r c$

表2 自然灾害设备易损性模型

灾种	来源	易损性分析方法及其适用性、准确度、优缺点	致损概率（参数）表征
地震	Lanzano等^[61]	通过数据统计分析，确定峰值地面加速度PGA与埋地管道泄漏频率关系，绘制易损性曲线，用Probit模型表征。该方法对不同结构类型管道的致损程度进行了细化，能分析多情景的易损性，但准确度受统计数据质量的影响较大。	$Y = k p, 1 + k p, 2 l n V$
	Pineda-Porras等^[62]	用单位长度管道所需修复的数目，即修复率（repair rate，RR）表征管道受损情况。该方法简洁高效，但是不同地震强度参数表征的易损性结果差异较大。	$R R = a × I M b$
	O'Rourke等^[58]和ALA^[59,60]	通过数据统计分析，利用逻辑回归等方法，建立不同震害强度下储罐不同致损程度的经验易损性曲线。该方法能够直观呈现储罐在不同存储状态下的易损性，但是没有区分锚固和非锚固情况，并且判别致损程度的依据主观性太强。	$P d s x = e x p (β 0 + β 1 x) 1 + e x p (β 0 + β 1 x)$
	Berahman等^[63]	根据数据库统计信息，利用Bayesian参数评估技术，建立设备地震易损性计算模型。该方法在极限状态方程中同时考虑了统计和模型的不确定性问题，准确度较高，但是模型复杂，需要大量的数学计算。	$F ? (q) = ∫ g (r; θ; q) ≤ 0 f (r) φ (ε 1) φ (ε 2) f (θ) d r d ε 1 d ε 2 d θ$
	Salzano等^[64]	通过数据统计，确定参数分布规律，利用Probit模型表征储罐的致损概率。该方法简单易行，但是模型的系数与统计数据数量和质量直接相关，不同学者统计得出的易损性曲线存在一定差异。	$P r D S = k 1 + k 2 l n (P G A)$
	孙建刚等^[65]	考虑结构和地震荷载的随机性，用设备可靠性的方法，结合串联可靠性表达式，分析储罐易损性。该方法从储罐的多种失效模式进行易损性研究，科学性更强，准确度较高。	$P f = 1 - 1 - P (F 1) × ∏ i = 2 n 1 + (u 0 - 1) × P (F i)$ $u 0 = 0.06 I 0 + 0.30$
洪水、海啸	Landucci等^{[47,48,49,66]}	建立简化力学模型，用最大水深和最大流速两个参数表征洪水或海啸的强度，考虑常压立式储罐和卧式储罐参数特性，推导失效概率方程。该方法从力学的角度建立极限状态方程，适用于非锚固储罐的分析，但是没有考虑不同的失效模式，并且需要确定的变量参数多。	常压立式储罐： $C F L v = (ρ w k w 2 v w 2 + ρ w g h w - p c r) / ρ f g H$ $P c r = J 1 C + J 2$ , $ψ = (C F L - φ m i n) / (φ m a x - φ m i n)$ 卧罐： $C F L h = ρ r e f A ρ l - ρ v ? (h w - h c) + ρ r e f B - ρ v ρ l - ρ v$ $v w, c = E ? (h w - h c - h m i n) F$ $若 v w ≥ v w, c, ψ = 1;$ $若 v w < v w, c, ψ = (C F L - φ m i n) / (φ m a x - φ m i n)$
	Basco等^[67]	建立力学模型，根据碎片和材料特性分析设备受碎块冲击的失效概率。该方法对碎块进行了极大简化，没有考虑碎块形状的影响，与实际场景存在较大差异，精确度不高。	$J = u 02 σ D θ m p r p 2$ $Y = k p 1 + k p 2 l n J$
	Khakzad等^[68]	根据储罐浮离、壳壁屈曲、滑移3种失效模式的力学模型，通过逻辑回归方法分析洪水易损性，利用贝叶斯网络对各类失效模式进行组合。该方法适用于大型常压非锚固储罐的分析，逻辑回归的方法考虑了共因失效和条件相关性，分析结果准确度高，科学性强，但是模型复杂，计算量大。	$P (s) = e ψ (s) 1 + e ψ (s)$ $ψ (s) = β l 0 + β l 1 s$
雷击	Necci等^[69]	基于电弧侵蚀模型（Arc Erosion Modeling），依据峰值电流强度和雷击电荷两个参数的概率分布函数，计算设备雷击后的损伤概率。该方法能够快速计算致损概率，但是没有考虑各类防雷设施的作用，评价的结果会高于实际场景。	$l n P d = 0.8944 - 0.908 l n t$ $D h, a v = 8.5 × 10 - 3 t 2 - 6.6 × 10 - 3 t + 5.23$ $P D D = ∑ i P d, i ? S i S t o t$
火山喷发	Milazzo等^[70]	根据阿基米德原理（Archimedes Principle）与欧拉方法（Eulers Method）建立火山灰与外浮顶罐之间的力学关系，推导罐顶下沉与倾覆的极限状态方程。该模型简洁高效，但在实际应用中，还有更多的参数需要考虑，包括火山喷发的频率和强度、风向、目标储罐与火山口的距离等。	$浮顶罐罐顶下沉 : h = ρ l i q u i d ρ a s h (δ - δ r o o f)$ 浮顶罐罐顶倾覆（浮顶保持稳定的条件为z_M>z_B）： $z M - z B = R 2 4 δ i m m - δ i m m 2$
	Milazzo等^[71]	类比填料塔中压降的原理，推导火山灰导致过滤系统压降的计算公式，得出计算过滤系统失效时间和火山灰浓度超越概率曲线的方法。该方法假定火山灰浓度是定值，忽略了复杂气象条件的影响，评价结果误差较大。	$p 0 - p L L = 150 μ D p 2 ρ ? (1 - ε) 2 ε 3 G 0 + 1.75 D p ρ ? 1 - ε ε 3 G 02$ $t = m a s h / q a i r c$

图2 Na-Tech事件防控体系

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