Methodology for global sensitivity analysis of consequence models

A methodology is presented for global sensitivity analysis of consequence models used in process safety applications. It involves running a consequence model around a hundred times and using the results to construct a statistical emulator, which is essentially a sophisticated curve fit to the data. The emulator is then used to undertake the sensitivity analysis and identify which input parameters (e.g. operating temperature and pressure, wind speed) have a significant effect on the chosen output (e.g. vapour cloud size). Performing the sensitivity analysis using the emulator rather than the consequence model itself leads to significant savings in computing time.To demonstrate the methodology, a global sensitivity analysis is performed on the Phast consequence model for discharge and dispersion. The scenarios studied consist of above-ground, horizontal, steady-state discharges of dense-phase carbon dioxide (CO₂), with orifices ranging in diameter from ½ to 2 inch and the liquid CO₂ stagnation conditions maintained at between 100 and 150 bar. These scenarios are relevant in scale to leaks from large diameter above-ground pipes or vessels.Seven model input parameters are varied: the vessel temperature and pressure, orifice size, wind speed, humidity, ground surface roughness and height of the release. The input parameters that have a dominant effect on the dispersion distance of the CO₂ cloud are identified, both in terms of their direct effect on the dispersion distance and their indirect effect, through interactions with other varying input parameters.The analysis, including the Phast simulations, runs on a standard office laptop computer in less than 30 min. Tests are performed to confirm that a hundred Phast runs are sufficient to produce an emulator with an acceptable degree of accuracy. Increasing the number of Phast runs is shown to have no effect on the conclusions of the sensitivity analysis.The study demonstrates that Bayesian analysis of model sensitivity can be conducted rapidly and easily on consequence models such as Phast. There is the potential for this to become a routine part of consequence modelling.     

Methodology for consequence analysis of LNG releases at deepwater port facilities

A methodology to perform consequence analysis associated with liquefied natural gas (LNG) for a deepwater port (DWP) facility has been presented. Analytical models used to describe the unconfined spill dynamics of LNG are discussed. How to determine the thermal hazard associated with a potential pool fire involving spilled LNG is also presented. Another hazard associated with potential releases of LNG is the dispersion of the LNG vapor. An approach using computational fluid dynamics tools (CFD) is presented. The CFD dispersion methodology is benchmarked against available test data. Using the proposed analysis approach provides estimates of hazard zones associated with newly proposed LNG deepwater ports and their potential impact to the public.     

Methodology for case studies of accidental gas explosions

This paper discusses a procedure for case studies of accidental gas explosions. The procedure for each case study can be subdivided into four steps, i.e., collection of proofs, analyses, confirmation, and inference about the processes of the accident, and the issues in each step are pointed out. Making a guess on the sequence of the accident to be investigated should be avoided during collection of proofs. Misunderstanding of the phenomena in analyses and confirmation is likely caused by inappropriate knowledge on the phenomena and/or use of unsuitable models. The sequence of the accidental gas explosion should be inferred on the basis of confirmed processes. If there are other possibilities, those should be described in the report. The reasonableness of the results of a case study depends on the rationality of the procedure and the quality or plausibility of knowledge to infer the probable sequence.     

Risk-optimal highway design: Methodology and case studies

Highway geometric design in mountainous areas has been a typical challenge. The combination of short horizontal curves and restricted right-of-way is a common ground for contemplating design exception in British Columbia, Canada. In practice, collision modification factors (CMFs) are advocated as quantitative measures of changes in road features on safety. However, in many situations, there are no CMFs in the literature to predict the safety impact of changing particular road features. An important example of these road features is sight distance restriction on horizontal curves. A mechanism for risk measurement has been proposed in earlier work to assist designers in comparing the safety impact of different deviations from sight distance requirements. This paper attempts to answer the questions as to whether it is possible to reduce overall risk and achieve consistency in such reduction without demanding wider right-of-way. This problem was formulated in a multi-objective optimization framework. Following this methodology, it was possible to achieve an average reduction in risk of 25% on the nine critical cross-sections. This reduction in risk was achieved without demanding wider right-of-way and without creating measurable increase in expected collision frequency due to independent re-dimensioning of different geometric elements. On theoretical grounds, this paper represents another step into the direction of developing fully probabilistic geometric design standards. On practical grounds, this paper provides an important decision mechanism that enables the efficient use of available right-of-way for new highway construction. Case studies in this paper have been applied on a major highway development in British Columba, Canada.     

Environmental consequence analysis for resource depletion

Resource depletion is of concern to both present and future generations in terms of access to resources. It is a prominent impact category within life cycle assessment (LCA) and sustainability assessment. This paper examines existing resource depletion approaches and indicators in the context of natural gas depletion, and their limitations in modelling the wider environmental consequences of resource consumption. Some existing models assume substitution of scarce fossil fuels with an alternative fossil fuel or mix, but do not consider all of the subsequent change in impacts. An additional methodology is proposed to measure the impact changes when fossil fuel substitution occurs as a result of scarcity. The methodology will demonstrate the effect of resource scarcity for individual processes but also multiple processes which operate at different levels of resource consumption with varying degrees of impacts. The methodology is applied to a scarcity situation of natural gas in Australia, where black coal is substituted for gas. It is first applied to natural gas consumed for electricity generation only. In the second case, the methodology is applied to the substitution of natural gas for both electricity generation and hydrogen production. The varying impacts on emissions to air and water, together with solid waste generation and water depletion, as a result of the substitution are used to reflect the consequences of fossil fuel depletion. The indicators also provide information on the impacts of substitution in each product, thus enabling users to prioritise products based on the impacts produced during natural gas allocation.     

危险化学品事故后果计算过程探讨

基于事故后果的风险评估方法是国内外进行安全评价和土地使用安全规划的基础方法之一。本文基于危险化学品种类和危险装置类型,对可能发生的事故情景和相应事故后果计算模型的选择方法进行了阐述,针对易燃、易爆、有毒危险化学品的事故后果计算过程进行了系统分析。最后对本文提出的事故后果分析方法进行了实例应用。本文的研究成果可为安全评价或土地使用安全规划等工作的开展提供必要的参考。     

Experimental studies of removing typical VOCs by dielectric barrier discharge reactor of different sizes

This research conducted both lab-scale and pilot-scale tests by selecting toluene as the typical volatile organic compounds (VOCs) and by using the promising non-thermal plasma oxidation technology – dielectric barrier discharge (DBD). To develop baseline engineering data to demonstrate the feasibility of application of self-made DBD reactors, the peak voltage, gas flow speed, initial toluene concentration, discharge frequency and duty ratio were studied. The results showed that toluene removal efficiency improves with increase of electrical voltage, frequency and duty ratio, and declines with increase of polar distance, gas flow speed and toluene initial concentration. When the voltage increases, the energy efficiency rises first and then drops. The energy efficiency reaches the climax when the energy density reaches 150.8 J/L and 101.7 J/L in the lab-scale experiment and pilot-scale experiment respectively.     

Gas leakage consequence modeling for buried gas pipelines

One of conservation transfer methods for such widely-used gases as natural gas and hydrogen is buried pipelines. Safety of these pipelines is of great importance due to potential risks posed by inefficiencies of the pipelines. Therefore, an accurate understanding of release and movement characteristics of the leaked gas, i.e. distribution and speed within soil, the release to the ground surface, the movement of hydrogen gas through the ground, gas underground diffusion, gas dispersion in atmosphere, and following consequences, are very important in order to determine underground dispersion risks. In the present study, consequences of gas leakage within soil were evaluated in two sub-models, i.e. near-field and far-field, and a comprehensive model was proposed in order to ensure safety of buried gas supply pipelines. Near-field model which is related to soil and ground and its output is the gas released at different points and times from ground surface and it was adopted as input of far-field sub-model which is dispersion model in atmosphere or an open space under the surface. Validation of near-field sub-model was performed by the experimental data obtained by Okamoto et al. (2014) on full-scale hydrogen leakage and then, possible scenarios for far-field sub-model were determined.     

Revised fire consequence models for offshore quantitative risk assessment

Offshore oil and gas platforms are well known for their compact geometry, high degree of congestion, limited ventilation and difficult escape routes. A small mishap under such conditions can quickly escalate into a catastrophe. Among all the accidental process-related events occurring offshore, fire is the most frequently reported. It is, therefore, necessary to study the behavior of fires and quantity the hazards posed by them in order to complete a detailed quantitative risk assessment. While there are many consequence models available to predict fire hazards-varying from point source models to highly complex computational fluid dynamic models—only a few have been validated for the unique conditions found offshore.

In this paper, we have considered fire consequence modeling as a suite of sub-models such as individual fire models, radiation model, overpressure model, smoke and toxicity models and human impact models. This comprehensive suite of models was then revised by making the following modifications: (i) fire models: existing fire models have been reviewed and the ones most suitable for offshore conditions were selected; (ii) overpressure impact model: a model has been developed to quantify the overpressure effects from fires to investigate the possible damage from the hot combustion gases released in highly confined compartments; (iii) radiation model: instead of a point/area model, a multipoint grid-based model has been adopted for better modeling and analysis of radiation heat flux consequences. A comparison of the performance of the revised models with the ones used in a commercial software package for offshore risk assessment was also carried out and is discussed in the paper.     

LNG accident dynamic simulation: Application for hazardous consequence reduction

The evaluation of exclusion (hazard) zones around the LNG stations is essential for risk assessment in LNG industry. In this study, computational fluid dynamics (CFD) simulations have been conducted for the two potential hazards, LNG flammable vapor dispersion and LNG pool fire radiation, respectively, to evaluate the exclusion zones. The spatial and temporal distribution of hazard in complex spill scenario has been taken into account in the CFD model. Experimental data from Falcon and Montoir field tests have been used to validate the simulation results. With the valid CFD model, the mitigation of the vapor dispersion with spray water curtains and the pool fire with high expansion foam were investigated. The spray water curtains were studied as a shield to prevent LNG vapor dispersing, and two types of water spray curtain, flat and cone, were analyzed to show their performance for reduction and minimization of the hazard influencing distance and area. The high expansion foam firefighting process was studied with dynamic simulation of the foam action, and the characteristics of the foam action on the reduction of LNG vaporization rate, vapor cloud and flame size as well as the thermal radiation hazard were analyzed and discussed.     

Methodology for Computer-Aided Fault Tree Analysis

Fault tree analysis is a systematic, deductive and probabilistic risk assessment tool which elucidates the causal relations leading to a given undesired event. Quantitative fault tree (failure) analysis requires a fault tree and failure data of basic events. Development of a fault tree and subsequent analysis require a great deal of expertise, which may not be available all the time. Computer-aided fault tree analysis is an easy-to-use approach, which not only provides reliable results but also facilitates the validation and repeatability of the analysis. This enhances the overall results of the fault tree analysis and quantitative risk analysis.This paper presents a revised methodology for computer-aided fault tree analysis. The methodology includes fault tree development, minimal cutsets determination, cutsets optimization and probability analysis. The methodology uses advanced concepts of fault tree development and static and dynamic modularizing for complex and large fault trees. Furthermore, it enables sensitivity analysis of the system for design modification and risk-based decision making. Application of the proposed methodology to a process system is also discussed in the paper.     

Machine learning based quantitative consequence prediction models for toxic dispersion casualty

Incidental release of toxic chemicals can pose extreme danger to life in the vicinity. Therefore, it is crucial for emergency responders, plant operators, and safety professionals to have a fast and accurate prediction to evaluate possible toxic dispersion life-threatening consequences. In this work, a toxic chemical dispersion casualty database that contains 450 leak scenarios of 18 toxic chemicals is constructed to develop a machine learning based quantitative property-consequence relationship (QPCR) model to estimate the affected area caused by toxic chemical release within a certain death rate. The results show that the developed QPCR model can predict the toxic dispersion casualty range with root mean square error of maximum distance, minimum distance, and maximum width less than 0.2, 0.4, and 0.3, which indicates that the constructed model has satisfying accuracy in predicting toxic dispersion ranges under different lethal consequences. The model can be further expanded to accommodate more toxic chemicals and leaking scenarios.     

Advanced multi-perspective computer simulation as a tool for reliable consequence analysis

Major accidents involving hazardous materials are a crucial issue for the chemical and process industries. Many accidental events taken place in the past showed that dangerous substances may pose a severe threat for people and property. Aiming at loss prevention, a series of actions have been instituted through international regulations concerning hazardous installations safety preparedness. These actions involve efficient land-use planning, safety studies execution, as well as emergency response planning drawing up. A key factor for the substantial consideration of the above is the effective prediction of possible accident forms and their consequences, for the estimation of which, a number of empirical models have been developed so far. However, (semi-)empirical models present certain deficiencies and obey to certain assumptions, thus leading to results of reduced accuracy. Another approach that could be used for this purpose and it is discussed in this work, is the utilization of advanced computational fluid dynamics (CFD) techniques in certain accident forms modeling. In particular, composite CFD-based models were developed for the simulation of several characteristic accident forms involving isothermal and non-isothermal heavy gas dispersion, confined and unconfined explosion in environment of complex geometry, as well as flammable cloud fire. The simulation cases were referred to real-scale trials allowing us to conclude about the validity of the quantitative results. Comparisons of the computational predictions with the experimental observations showed that obtained results were in good agreement with the experimental ones, whereas the evaluation of statistical performance measures proved the simulations to be statistically valid.     

工艺流程中氨泄漏事故后果分类研究

氨是重要的化工原料和产品,工艺流程中氨主要以氨气、液氨、氨溶液三种状态存在。氨气、液氨、氨溶液理化特性及危险特性不同,可能造成的事故后果类型不同,分别进行三种相态下氨泄漏的事故情景分析。氨气泄漏主要考虑蒸气云爆炸、中毒,液氨泄漏主要考虑沸腾液体扩展蒸气爆炸、蒸气云爆炸、中毒,氨溶液泄漏主要考虑中毒和腐蚀。运用半球模型和高斯模型计算某尿素企业液氨球罐泄漏的危害范围。半球泄漏模型计算方法较简单,但没有考虑氨本身性质及气象条件等因素;高斯模型计算过程较复杂,其计算结果与风速、大气稳定度等条件相关。该两种方法计算结果对预防氨泄漏事故发生和氨泄漏事故预警均具有一定参考意义,如何提高模拟分析的准确度是今后研究工作的重点。     

人群拥挤踩踏事故后果微观建模及模拟分析

针对人群拥挤踩踏事故风险理论(4阶段)中传统数学模型难以解决的定量问题,分析大型公共场所高密度拥挤人群中的个体受力.依据牛顿第二定律和经典"社会力"模型对人群中的个体受力进行建模.本文提出了引起人群拥挤踩踏事故后果即人员伤亡的"拥挤力"的概念,并在"磁场力"模型基础上依据动量定理构建了拥挤人群中的个体受力微观模拟模型.基于此微观模拟模型并结合多智能体技术开发了人群拥挤踩踏事故模拟系统,对正常及紧急状况下的奥运赛场出口人群疏散模拟的结果表明,该模拟系统不仅能够直观地表示人群拥挤踩踏事故后果,而且还可通过滞留人数随疏散时间的变化情况了解人群疏散状况.该微观模拟模型及模拟系统对大型公共建筑的性能化设计、人群安全疏散及管理等有指导意义.     

CNG加气站事故后果分析方法研究

根据CNG加气站系统运行的实际情况,将CNG加气站中易发生泄漏的设备分为管道阀门、挠性连接器、压缩机、储气设备、放散管5类。建立了CNG泄漏的事件树,将CNG加气站的事故后果类型概括为喷射火、闪火、蒸气云爆炸。总结了CNG加气站事故后果的计算模型,采用美国环保局的ALOHA软件确定事故后果的影响范围。综合运用该两种方法对喷射火和蒸气云爆炸的事故案例进行对比研究,结果表明,计算结果基本一致。该两种事故后果分析方法为CNG加气站安全管理和安全规划提供依据。     

基于环境后果评价的环境风险源分级模型研究

为解决目前环境风险源分级存在的指标单一和不确定性较大的问题,综合考虑危险物质特性、环境迁移规律及环境危害特性,建立较全面的环境后果评价指标体系和评价模型,并应用蒙特卡罗方法分析评价过程中的不确定性,构建以环境后果综合评价为基础的环境风险源分级模型.根据2009年4月对上海市闵行区重点工业企业危险源的调研结果,将模型用于上海某油墨有限公司甲苯储罐的风险源分级评价.结果表明,该风险源的综合评价指数为0.007 9～0.259 4,根据90%的累积概率对应的评价指数值(0.104 0)确定该风险源为重大环境风险源.本文建立的模型可有效评价环境影响后果,为环境风险源的分级管理提供了科学依据.     

基于机器学习的恐怖袭击事件后果预测方法研究

恐怖袭击事件通常会造成严重的人员伤亡、财产损失和社会影响,针对在不同场景下发生恐怖袭击所造成的后果进行预测是目前应对恐怖袭击事件急需解决的问题之一。利用多源数据,首先基于随机森林算法对恐怖袭击事件是否造成死伤进行分类预测,进而基于岭回归算法预测事件造成的具体死伤人数。研究结果表明:随机森林在测试集上对有死伤事件的召回率达到0.85,岭回归预测死亡和受伤人数的平均绝对误差分别小于1人和2人。研究结果可为反恐资源配置优化、预防恐怖袭击事件和减少其造成的损害提供辅助决策支持。     

Methodology for computer aided fuzzy fault tree analysis

Probabilistic risk assessment (PRA) is a comprehensive, structured and logical analysis method aimed at identifying and assessing risks of complex process systems. PRA uses fault tree analysis (FTA) as a tool to identify basic causes leading to an undesired event, to represent logical dependency of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event.To conduct a quantitative fault tree analysis, one needs a fault tree along with failure data of the basic events (components). Sometimes it is difficult to have an exact estimation of the failure rate of individual components or the probability of occurrence of undesired events due to a lack of sufficient data. Further, due to imprecision in basic failure data, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising out of subjectivity of the data.This paper presents a methodology for a fuzzy based computer-aided fault tree analysis tool. The methodology is developed using a systematic approach of fault tree development, minimal cut sets determination and probability analysis. Further, it uses static and dynamic structuring and modeling, fuzzy based probability analysis and sensitivity analysis.This paper also illustrates with a case study the use of a fuzzy weighted index and cutsets importance measure in sensitivity analysis (for system probabilistic risk analysis) and design modification.