On the application of the window of opportunity and complex network to risk analysis of process plants operations during a pandemic

To quantify the pandemic specific impact with respect to the risk related to the chemical industry, a novel risk analysis method is proposed. The method includes three parts. Firstly, the two types of “window of opportunity” (WO) theory is proposed to divide an accident life cycle into two parts. Then, a qualitative risk analysis is conducted based on WO theory to determine possible risk factors, evolution paths and consequences. The third part is a quantitative risk analysis based on a complex network model, integrating two types of WO. The Fuzzy set theory is introduced to calculate the failure probabilities of risk factors and the concept of risk entropy is used to represent the uncertainty. Then the Dijkstra algorithm is used to calculate the shortest path and the corresponding probability of the accident. The proposed method is applied to the SCR denitrition liquid ammonia storage and transportation system. The results show that it is a comprehensive method of quantitative risk analysis and it is applicable to risk analysis during the pandemic.     

带混合时间窗的多目标危险化学品运输路径优化

为降低危险化学品运输风险,使路径选择更加科学、切合实际,从责任主体、社会影响等方面综合考虑危险化学品运输相关主体,根据各主体目标对影响运输路径选择的指标进行重新识别和细分,提出5大指标体系。应用熵权法计算出各指标权重,建立混合时间窗条件下的多目标危化品运输路径优化模型,通过改进的多目标遗传算法求出Pareto最优解。结果表明,不同时间点出发会产生不同的Pareto最优解,并且可得到每条最优路径的出发时间窗,每个最优解代表了某项指标达到相对最优时的路径。混合时间窗较符合实际情况,基于出发时间窗及生成的多条最优路径,决策者可根据决策偏好及关注重点以较高效率选出最合适的路径。     

基于组合权重模糊物元模型的船桥碰撞风险评价

为了定量评价船桥碰撞风险,确定不同桥梁的安全程度,通过头脑风暴法对影响船舶通过桥区水域安全的因素进行辨识,构建了包含10个Ⅰ级指标的指标体系,采用AHP法和熵权法分别从主、客观的角度计算各指标的权重,并依据最小鉴别原理进行权重组合,得到兼顾主、客观因素的权重。将各项评价指标划分为低危险度、较低危险度、中等危险度、较高危险度和高危险度5个安全等级,结合组合权重构建船桥碰撞风险模糊物元评价模型。最后利用该模型对长江干线6个典型桥梁的船撞桥风险进行了评价。结果表明,除"C"桥梁处于"中等危险度"外,其他5座桥梁均处于"较低危险度",该模型应用于船桥碰撞综合评价具有较好的适应性。     

事故与熵──事故发生可能性计算的新方法

从熵增加的观点描述了事故的本质，剖析了人机系统的实质与特性，提出了风险熵与事故势的概念，给出了计算机风险熵与事故势的方法。结果表明，系统具有二重性。在系统运行期间，系统具有封闭体系的特性；在休整期间，系统具有开放体系的特性。事故是运行系统的必然发展趋势，是运行系统的固有属性，是一种自发过程。由于在系统熵增加的过程中信息及能量的交换，可以把事故定义为系统熵增加的结果。避免事故发生的原理是不断地向系统输入信息或负熵以抵消系统内部的熵增加。     

仓面浇筑立体空间冲突致灾过程建模与伤害评价*

为定量评价大坝浇筑过程空间冲突致灾事故后果,通过对缆机运输典型情景进行危害能量运动分解,确定在水平和竖直方向运动方式,阐述危害能量在流动路径相互转化形式;根据能量守恒定律,分析危害能量在吊罐与承灾体碰撞接触之间转移规律,将吊罐与人头部接触过程抽象为带强阻尼的弹簧振子系统,建立危害能量与碰撞冲量相等的动量方程,量化空间冲突致灾后果。结果表明:吊罐坠落危害能量极大,产生的碰撞冲击力与吊罐的运输速度、高度呈正相关,与阻力系数呈负相关,风速、载重对其影响较大。对比2种不同碰撞情景发现,机械碰撞因顶部承载力缓冲,对人头部产生伤害远小于直接碰撞,并对碰撞结果分级评价,研究结果可为大坝浇筑交叉作业空间冲突致灾风险评价提供参考。     

Critical aspects for collision induced oil spill response and recovery system in ice conditions: A model-based analysis

The recovery effectiveness for oil spills in ice conditions depends on a complex system and has not been studied in depth, especially not from a system risk control perspective. This paper aims to identify the critical aspects in the oil spill system to enable effective oil spill recovery. First, a method is developed to identify critical elements in a Bayesian Network model, based on an uncertainty-based risk perspective. The method accounts for sensitivity and the strength of evidence, which are assessed for the different Bayesian Network model features. Then, a Bayesian Network model for the mechanical oil spill recovery system is developed for the Finnish oil spill response fleet, contextualized for representative collision accident scenarios. This model combines information about representative sea ice conditions, ship-ship collisions and their associated oil outflow, the oil dispersion and spreading in the ice conditions, and the oil spill response and recovery of the fleet. Finally, the critical factors are identified by applying the proposed method to the developed oil spill response system model. The identified most critical system factors relates collision aspect: Forcing Representative Scenario, Representative Accident Location, Impact Speed, Impact Location, Impact Angle and response aspect: Response Vessel Operability.     

基于灾变的人群疏散避灾路径优化及应用

突发事件条件下的应急疏散是一个复杂的过程，不仅要考虑时间因素，而且要考虑疏散网络中各路段的受灾风险水平。因此，对于人群快速转移避灾路径的解算结果，不仅要求快速，还要求避灾。基于灾害预测的疏散路径优化理论模型，在求解时变灾害条件下，集成考虑实时与未来灾害影响的转移避灾路径优化算法。采用C#程序设计语言和Visual studio 2013平台，开发了进行模型算法实现的原型系统，并通过算例进行了说明。结果表明:在预先设置的灾害情景中，提出的模型算法可以提前规划出避开灾害且疏散时间较短的路径，为制定应急预案提供参考依据。     

Fast Calculating Surrogate Models for Leg and Head Impact in Vehicle–Pedestrian Collision Simulations

Objective: In previous research, a tool chain to simulate vehicle–pedestrian accidents from ordinary driving state to in-crash has been developed. This tool chain allows for injury criteria-based, vehicle-specific (geometry, stiffness, active safety systems, etc.) assessments. Due to the complex nature of the included finite element analysis (FEA) models, calculation times are very high. This is a major drawback for using FEA models in large-scale effectiveness assessment studies. Therefore, fast calculating surrogate models to approximate the relevant injury criteria as a function of pedestrian vehicle collision constellations have to be developed.

Method: The development of surrogate models for head and leg injury criteria to overcome the problem of long calculation times while preserving high detail level of results for effectiveness analysis is shown in this article. These surrogate models are then used in the tool chain as time-efficient replacements for the FEA model to approximate the injury criteria values. The method consists of the following steps: Selection of suitable training data sets out of a large number of given collision constellations, detailed FEA calculations with the training data sets as input, and training of the surrogate models with the FEA model's input and output values.

Results: A separate surrogate model was created for each injury criterion, consisting of a response surface that maps the input parameters (i.e., leg impactor position and velocity) to the output value. In addition, a performance test comparing surrogate model predictions of additional collision constellations to the results of respective FEA calculations was carried out. The developed method allows for prediction of injury criteria based on impact constellation for a given vehicle. Because the surrogate models are specific to a certain vehicle, training has to be redone for a new vehicle. Still, there is a large benefit regarding calculation time when doing large-scale studies.

Conclusion: The method can be used in prospective effectiveness assessment studies of new vehicle safety features and takes into account specific local features of a vehicle (geometry, stiffness, etc.) as well as external parameters (location and velocity of pedestrian impact). Furthermore, it can be easily extended to other injury criteria or accident scenarios; for example, cyclist accidents.     

Fuzzy risk modeling of process operations in the oil and gas refineries

Operating several assets has resulted in more complexity and so occurrence of some major accidents in the refining industries. The process operations risk factors including failure frequency and the consequence components like employees' safety and environment impacts, operation downtime, direct and indirect cost of operations and maintenance, and mean time to repair should be considered in the analysis of these major accidents in any refinery. Considering all of these factors, the risk based maintenance (RBM) as a proper risk assessment methodology minimizes the risk resulting from asset failures. But, one of the main engineering problems in risk modeling of the complex industries like refineries is uncertainty due to the lack of information. This paper proposes a model for the risk of the process operations in the oil and gas refineries. The fuzzy logic system (FLS) was proposed for risk modeling. The merit of using fuzzy model is to overcome the uncertainty of the RBM components. This approach also can be accounted as a benchmark for future failures. A unified risk number would be obtained to show how the criticality of units is. The case study of a gas plant in an oil refinery is performed to illustrate the application of the proposed model and a comparison between the results of both traditional RBM and fuzzy method is made.For the case study, 26 asset failures were identified. The fuzzy risk results show that 3 failures have semi-critical level and other 23 failures are non-critical. In both traditional and fuzzy RBM methods, some condenser failures had the highest risk number and some pumps were prioritized to have the lowest risk level. The unit with unified risk number less than 40 is in the non-critical conditions. Proposed methodology is also applicable to other industries dealing with process operations risks.     

Impact of safety attitude,safety knowledge and safety leadership on chemical industry workers’ risk perception based on Structural Equation Modelling and System Dynamics

In chemical industry, major accidents occur occasionally. Past research has demonstrated that risk perception was relevant to safety as it might affect the behavior, which could exert influence on the probability of accidents. It is important to adjust workers' risk perception to reduce accidents in chemical industry. To achieve this goal, some key influencing factors of workers’ risk perception of were identified from 3 aspects including safety attitude, safety knowledge and safety leadership. This was accomplished by gathering empirical data from 287 workers employed in 6 Chemical plants in Jiangsu, China. The model of influencing factors of risk perception for workers was established based on Structural Equation Modelling (SEM), and the path coefficients and weights were analyzed by the SEM. On that basis, the System Dynamics (SD) model of risk perception for workers was established. The study findings revealed safety attitude and safety leadership have a direct positive impact on perception of risk probability and perception of risk severity, safety knowledge has a direct positive impact on perception of risk severity, while safety knowledge has no direct positive impact on perception of risk probability. The findings of the study can provide theoretical supports and method guidance for adjusting the risk perception of workers in chemical industry.     

Risk characterisation indicators for risk comparison in the energy sector

The paper presents and discusses steps in the development of a set of risk characterisation indicators (RCIs) to be applied for the comparison of risk expressions from different energy systems across their fuel/life cycle to obtain a fair risk evaluation. The Joint Research Centre of the European Commission (EC-DG JRC), and specifically its Institute for Energy in Petten/Netherlands (JRC-IE), initiated a PhD study activity entitled European Energy Risks Monitor (ERMON), to assess and compare different energy technologies. The comparison is based, among others, on a set of risk indicators, developed on the backbone of a causal structure for energy technologies. The development of the RCIs is a process which aims at the identification of the input for the development, starting with the recognition of possible stakeholders for ERMON, the detection of possible risk scenarios available from different energy systems, and concluding with the development of the indicators. This paper mainly focuses on the latter. The main characteristics of the resulting set of indicators are presented and discussed, together with their application, and limits.     

Joint applicability test of software for laboratory assessment and risk analysis

Most of the available risk management methods are not directly applicable to academic research laboratories. One solution to systematically perform risk analyses in this environment is the Laboratory Assessment and Risk Analysis (LARA) method. This method was developed to allow untrained personnel to identify of possible risks and rank them according to their importance. The purpose of this study was to find out, if this method can be used as a holistic risk management technique in different environments, and which are the differences when comparing the results to other, well established risk analysis techniques. The risk analyses were performed at two European universities and for various procedures. The results show, that the LARA procedure is more easily performable than the other methods and gives comparably adequate results. Being applicable by non-experts, this holistic risk analysis method for research laboratories can help to reduce the accident rate in the academic environment.     

An approach to estimating the individual risk for toxic-gas releases using the load-resistance model

A new approach to quantify the uncertainty of the individual risk for toxic releases is presented in this paper. The individual risk is defined as the probability of fatality per year. The probability of fatality is calculated by a classical load-resistance model based on reliability (survivability) theory. The load effect is defined as the concentration intensity to which a human is exposed. Furthermore, the resistance is defined as the human tolerance to a certain concentration load in this study. The Monte Carlo method is used to obtain the probability distributions of outputs (the load effect and resistance) propagated from the uncertainties of the input variables. The fatality probability exceeding a limit state can then be obtained by comparing pairs of samples from the load effect and the resistance distributions. The separation of sampling from the load and resistance distributions is also proposed to allow more efficient calculation than that achieved by the classical Monte Carlo method. The analytical risk estimates computed by the load-resistance model are compared to conventional risk estimates that correspond to the upper-end percentile of the load-effect distribution. A case study shows that the conventional risk estimates can be directed to wrong decisions when the load-effect distribution has upper-end tail heaviness.     

Assessment model for equipment risk management: Petrochemical industry cases

This study presents an assessment model that examines quantity and quality factors for equipment risk management in the petrochemical industry. The proposed model has five dimensions—financial performance, logistical support, service level, learning and innovation, and risk control. This evaluation model uses 13 strategy subjects and 78 performance-measurement indicators. Performance assessment indicators are initially established and revised based on expert opinions collected via a questionnaire. Further, the analytical network process (ANP) is utilized to calculate the weights of indicators in each layer and to construct assessment models with applicable and valuable references. To determine model practicability, this study assesses four subsidiaries of the case company. Each subsidiary has a capitalization exceeding TWD 50 billion. In addition to evaluating company performance in terms of each dimension and indicator, the proposed model provides a valuable reference for decision-making in equipment risk management.     

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision-avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.     

Modeling crash severity by considering risk indicators of driver and roadway: A Bayesian network approach

Introduction: Traffic crashes could result in severe outcomes such as injuries and deaths. Thus, understanding factors associated with crash severity is of practical importance. Few studies have deeply examined how prior violation and crash experience of drivers and roadways are associated with crash severity. Method: In this study, a set of risk indicators of road users and roadways were developed based on their prior violation and crash records (e.g., cumulative crash frequency of a roadway), in order to reflect certain aspect or degree of their driving risk. To explore the impacts of those indicators on crash severity and complex interactions among all contributing factors, a Bayesian network approach was developed, based on citywide crash data collected in Kunshan, China from 2016 to 2018. A variable selection procedure based on Information Value (IV) was developed to identify significant variables, and the Bayesian network was employed to explicitly explore statistical associations between crash severity and significant variables. Results: In terms of balanced accuracy and AUCs, the proposed approach performed reasonably well. Bayesian modeling results indicated that the prior crash/violation experiences of road users and roadways were very important risk indicators. For example, migrant workers tend to have high injury risk due to their dangerous violation behaviors, such as retrograding, red-light running, and right-of-way violation. Furthermore, results showed that certain variable combinations had enhanced impacts on severity outcome than single variables. For example, when a migrant worker and a non-motorized vehicle are involved in a crash happening on a local road with high cumulative violation frequency in the previous year, the probability for drivers suffering serious injury or fatality is much higher than that caused by any single factor. Practical applications: The proposed methodology and modeling results provide insights for developing effective countermeasures to reduce crash severity and improve traffic system safety performance.     

军民航空域安全评估中的碰撞风险研究

碰撞风险是空域安全评估的重要内容。为保证军民航的安全飞行,通过对民航Event模型碰撞风险的研究,构建了军航训练空域与民航航路的碰撞风险模型;根据军航飞机的飞行特点,建立了军航飞机侧向位置偏差概率模型;结合民航飞机的横向位置偏差概率模型重新计算Event模型中的碰撞盒穿越间隔片频率(GERh);选取某一战术动作对军民侧向碰撞风险进行仿真,确定其安全间隔;通过对飞行过程中各个关键点碰撞风险的研究,对空域的使用提出建议,并验证了理论的实用性。结果表明,当前10 km的安全间隔标准并不能符合规定的安全目标等级,至少需要再增加7 km的安全间隔才能使整个飞行过程均满足要求。     

A new multiple-risk map approach to solve process plant layout considering safety and economic aspects

Mathematical models used to optimize the process plant layout (PPL) with risk reduction have four primary objectives, which are related to the minimization of land, pumping (pipe system), protection system devices, and risk costs. Moreover, these models are of two types: continuous plane models (CPM) and grid-based models (GBM); however, the nonconvexity of the CPM models makes difficult to achieve the global optimum, because it is formulated as Mixed-Integer Nonlinear Programming (MINLP). Thus, the risk map approach has been implemented with the grid-based models to solve problems of process plant layout focused on finding the best possible solution. However, these risk map formulations present important limitations, mainly related with the use of protection devices and the occupied area. Therefore, a new GBM-MILP formulation is proposed to optimize the selection of protection devices and minimize the occupied area. The risk is reduced through the investment on safety devices instead of considering the increase of separation distances. The proposed model was used to solve the layout problem of an ethylene oxide process, and the results was compared with a process layout reported in the literature. The results show that the model can provide the best possible solution; however, the time spent in the calculation is considerably greater than that reported for continuous plane models. Finally, the model can be used by decision-makers to evaluate different layout options for several explosion scenarios, during the early stages of the plant design.     

A new simple methodology for evaluation of explosion risk in underground coal mines

The key objective of this paper is the presentation of a new risk assessment tool for underground coal mines based on a simplified semi-quantitative estimation and assessment method.In order to determine the risk of explosion of any work process or activity in underground coal mines it is necessary to assess the risk. The proposed method is based on a Risk Index obtained as a product of three factors: frequency of each individual scenario P_ucm, associated severity consequences C_ucm and exposure time to explosive atmospheres E_ucm. The influence of exposure time is usually not taken into account up to now. Moreover, the exposure to explosive atmospheres may affect factors of hazardous event probability as much as its consequences. There are many definitions of exposure to explosive atmospheres but in the case of underground coal mines the exposure is defined as frequency risk of firedamp and coal dust. The risk estimation and risk assessment are based on the developed of a risk matrix.The proposed methodology allows not only the estimation of the explosion risk but also gives an approach to decide if the proposal investment is well-justified or not in order to improve safety.     

烟花爆竹烟火药剂危险性评价方法

为预防涉及烟花爆竹用烟火药剂的事故,应当在大规模制造、使用、储存之前,初步评估其危险性。在大量文献调研和专家建议基础上,选取机械感度(撞击和摩擦)和热感度作为烟火药安全性的最主要的指标。基于危险度的定义,用摩擦感度、撞击感度和热感度表征可能性,用最大放热量原则计算的放热量表征严重度,提出一种简便的,对烟花爆竹用烟火药剂的危险性进行评价的方法。运用此种方法得到的几种药剂的危险性等级比较符合实际情况。