Application of Bayesian Regularization Artificial Neural Network in explosion risk analysis of fixed offshore platform

Computational Fluid Dynamics (CFD) is routinely used in Explosion Risk Analysis (ERA), as CFD-based ERA offers a good understanding of underlying physics accidental loads. Generally, simplifications were incorporated into CFD-based ERA to limit the number of simulations. Frozen Cloud Approach (FCA) is a frequently used simplification in the dispersion part of the CFD-based ERA procedure. However, its accuracy is questionable in the complex and congested environment such as offshore facility. Furthermore, in explosion part, some specific techniques, e.g. linear/double bin-interpolated techniques have been proposed while the corresponding accuracy is still unknown since the developers did not yet check their accuracy by considering the explosion computational data as the benchmark.This study presents a more accurate algorithm, namely Bayesian Regularization Artificial Neural Network (BRANN) and accordingly proposes the frameworks regarding BRANN-based models for the CFD-based ERA procedure. Firstly, the framework is proposed to develop the Transient-BRANN (TBRANN) model for transient dispersion study. In addition, the framework to determine the BRANN model for explosion study is developed. The proposed frameworks are explained by a case study of the fixed offshore platform. Consequently, this study confirms the more accuracy of the TBRANN model over FCA and the accuracy of BRANN model for CFD-based ERA.     

A CFD based explosion risk analysis methodology using time varying release rates in dispersion simulations

A full probabilistic Explosion Risk Analysis (ERA) is commonly used to establish overpressure exceedance curves for offshore facilities. This involves modelling a large number of gas dispersion and explosion scenarios. Capturing the time dependant build up and decay of a flammable gas cloud size along with its shape and location are important parameters that can govern the results of an ERA. Dispersion simulations using Computational Fluid Dynamics (CFD) are generally carried out in detailed ERA studies to obtain these pieces of information. However, these dispersion simulations are typically modelled with constant release rates leading to steady state results. The basic assumption used here is that the flammable gas cloud build up rate from these constant release rate dispersion simulations would mimic the actual transient cloud build up rate from a time varying release rate. This assumption does not correctly capture the physical phenomena of transient gas releases and their subsequent dispersion and may lead to very conservative results. This in turn results in potential over design of facilities with implications on time, materials and cost of a project.In the current work, an ERA methodology is proposed that uses time varying release rates as an input in the CFD dispersion simulations to obtain the fully transient flammable gas cloud build-up and decay, while ensuring the total time required to perform the ERA study is also reduced. It was found that the proposed ERA methodology leads to improved accuracy in dispersion results, steeper overpressure exceedance curves and a significant reduction in the Design Accidental Load (DAL) values whilst still maintaining some conservatism and also reducing the total time required to perform an ERA study.     

环境风险评价的现状问题及建议初探

在介绍环境风险评价发展概况的基础上,简要探讨了环境风险评价存在的问题,包括环境风险评价与安全评价在技术方法上协调不足,环境风险评价与环境风险评估衔接不够到位,环境风险评价方法体系与国外尚存在差距,部分环境风险防范措施的标准指导有待完善。针对以上问题,建议不同职能部门加强沟通和合作,推动环境风险评价、安全评价技术标准和手段更好地统一;将环境风险评价和环境风险评估有效衔接或合并;加强相关基础研究和数据积累工作;在相关技术导则或评估指南中明确事故应急池等环境风险防范措施的设置依据。     

Numerical study of medium to large scale BLEVE for blast wave prediction

So far, the prediction of blast wave generated from the Boiling Liquid Expanding Vapour Explosion (BLEVE) has been already broadly investigated. However, only a few validations of these blast wave prediction models have been made, and some well-established methods are available to predict BLEVE overpressure in the open space only. This paper presents numerical study on the estimation of the near-field and far-field blast waves from BLEVEs. The scale effect is taken into account by conducting two different scale BLEVE simulations. The expansion of pressurized vapour and evaporation of liquid in BLEVE are both modelled by using CFD method. Two approaches are proposed to determine the initial pressure of BLEVE source. The vapour evaporation and liquid flashing are simulated separately in these two approaches. Satisfactory agreement between the CFD simulation results and experimental data is achieved. With the validated CFD model, the results predicted by the proposed approaches can be used to predict explosion loads for better assessment of explosion effects on structures.     

Fuzzy logic approach to calculation of thermal hazard distances in process industries

In this paper, a general procedure to deal with uncertainties in each stage of consequence modeling is presented. In the first part of the procedure, the sources of uncertainty are identified and confirmed by sensitivity analysis for the source term, dispersion, physical effects and consequence analysis. While the second part comprises an application of the fuzzy logic system to each step of the consequence modeling. The proposed procedure is verified by the case study for a pool fire liquefied natural gas (LNG) on water. The results in terms of thermal radiation distances are compared with calculations obtained using the Monte Carlo method and with experimental data. The consequence model based on fuzzy logic approach provides less uncertain and more precise results in comparison to the deterministic consequence model.     

Validation of geometry modelling approaches for offshore gas dispersion simulations

Computational Fluid Dynamics (CFD) codes are widely used for gas dispersion studies on offshore installations. The majority of these codes use single-block Cartesian grids with the porosity/distributed-resistance (PDR) approach to model small geometric details. Computational cost of this approach is low since small-scale obstacles are not resolved on the computational mesh. However, there are some uncertainties regarding this approach, especially in terms of grid dependency and turbulence generated from complex objects. An alternative approach, which can be implemented in general-purpose CFD codes, is to use body-fitted grids for medium to large-scale objects whilst combining multiple small-scale obstacles in close proximity and using porous media models to represent blockage effects. This approach is validated in this study, by comparing numerical predictions with large-scale gas dispersion experiments carried out in DNV GL's Spadeadam test site. Gas concentrations and gas cloud volumes obtained from simulations are compared with measurements. These simulations are performed using the commercially available ANSYS CFX, which is a general-purpose CFD code. For comparison, further simulations are performed using CFX where small-scale objects are explicitly resolved. The aim of this work is to evaluate the accuracy and efficiency of these different geometry modelling approaches.     

It pays to have an eye for emotions: Emotion recognition ability indirectly predicts annual income

This study integrates the emotion and social influence literatures to examine how emotion recognition ability (ERA) relates to annual income. In a sample of 142 employee–peer–supervisor triads from a broad range of jobs and organizations, we find that people's level of ERA indirectly relates to how much they earn per year. The relationship between ERA and annual income is mediated sequentially through political skill and interpersonal facilitation. The results imply that emotional abilities allow people not only to process affect‐laden information effectively but also to use this information to successfully navigate the social world of organizations in the pursuit of prosperity. Copyright © 2014 John Wiley & Sons, Ltd.     

An Analysis of the Cumulative Uncertainty Associated with a Quantitative Consequence Assessment of a Major Accident

The accident consequence estimation for a particular hazardous installation consists of source term estimation, dispersion simulation, and an assessment of the effects on the people, buildings and equipment. In the article the typical range of the uncertainty of each separate step is assessed and then combined and analysed with the view to understand their cumulative influence on the uncertainty surrounding the resulting consequence value. Certain assumptions and a simple error calculation formula have been applied to produce the analysis of influence of individual error estimates on the final consequence assessment. The data used are partially taken from past benchmarking exercises conducted by the Major Accident Hazards Bureau (MAHB) of the European Commission's Joint Research Centre, and partially from literature sources. The methodology for combining the separate uncertainty values together and the results of the analysis of the combined influence of the uncertainties associated with each step are described.     

环境风险评价内涵与外延研究

在简要介绍环境风险评价(Environmental Risk Assessment,ERA)发展历程的基础上,总结现阶段国内外普遍采用的ERA定义,深入分析ERA的内涵和类型,在重新给出涵盖性更全面的ERA定义的同时,对3种评价内容的评价程序和评价方法进行了横向比较。收集整理了ERA的研究进展和应用现状,从时间、范畴和应用范围3个方面划定了ERA的外延。     

Review of the DESC project

Dust Explosion Simulation Code (DESC) was a project supported by the European Commission under the Fifth Framework Programme. The main purpose of the project was to develop a simulation tool based on computational fluid dynamics (CFD) that could predict the potential consequences of industrial dust explosions in complex geometries. Partners in the DESC consortium performed experimental work on a wide range of topics related to dust explosions, including dust lifting by flow or shock waves, flame propagation in vertical pipes, dispersion-induced turbulence and flame propagation in closed vessels, dust explosions in closed and vented interconnected vessel systems, and measurements in real process plants. The new CFD code DESC is based on the existing CFD code FLame ACceleration Simulator (FLACS) for gas explosions. The modelling approach adopted in the first version entails the extraction of combustion parameters from pressure–time histories measured in standardized 20-l explosion vessels. The present paper summarizes the main experimental results obtained during the DESC project, with a view to their relevance regarding dust explosion modelling, and describes the modelling of flow and combustion in the first version of the DESC code. Capabilities and limitations of the code are discussed, both in light of its ability to reproduce experimental results, and as a practical tool in the field of dust explosion safety.     

Investigating new risk reduction and mitigation in the oil and gas industry

The complexity of the processes and the nature of volatile petroleum products urged the oil and gas industry to utilize various risk assessment techniques to identify potential failure modes that can interrupt operation processes. Consequently, government agencies and nonprofit professional societies guide the industry with regulatory guidelines, standards, and best recommended practices to oversee the operations management, assure safe working environment, and contain failures within tolerable limits. Yet, accidents due to electro-mechanical failures still occur and result in various consequences. Accordingly, critics have raised concerns about the petroleum industry's safety and risk mitigation credentials and question its ability to prevent future major accidents. Therefore, new risk assessment tools need to be introduced to provide decision makers and novice engineers with a diverse perception of potential risks. The aim of this paper is verify the application of Risk in Early Design (RED), a product risk assessment tool, in identifying potential failures in the oil and gas industry. Approximately thirty major accident underwent the RED analysis to verify the software's application to identify and rank potential failure modes.     

Interactions of risk analysis and contingency planning in risk management

Risk management entails knowledge of the risk and how best to reduce it; its objective is to minimize losses arising from existing or potential risk. With effective contingency planning, risk analysis and its corollary, consequence analysis, can contribute synergistically to improved risk management. Until recently, risk analysis and contingency or emergency response planning were considered distinct disciplines with little interactive potential. Fortunately, industry now recognizes that linking the two can help ensure public safety as well as preserve the financial integrity of plant owners. Both areas are receiving increased and well-deserved attention; several incidents in recent years have demonstrated that losses could have been greatly reduced if better precautions and procedures had been in place as a result of risk analysis and contingency planning.     

A systems-theoretic approach for two-stage emergency risk analysis

Coronavirus disease (COVID-19) is an infectious disease that has dramatically spread worldwide. Regarding the safety issues of industries, there is a requirement of dealing with the emergency risk in the period of urgent situations. In this work, we proposed a systems-theoretic approach of the two-stage emergency risk analysis (ERA) based on the systems theory, that is the System-Theoretic Accident Model and Processes (STAMP). The two-stage ERA includes the normal to emergency risk analysis (N2E-RA) and emergency to normal risk analysis (E2N-RA). Besides N2E-RA, we advocate that E2N-RA is also an important and indispensable part of ERA. We elaborated the characteristics of N2E-RA and E2N-RA, separately. Eventually, based on our analysis, we provided recommendations for decision makers in preventing and controlling industrial accidents in the period of COVID-19.     

Smart chemical industry parks in China: Current status,challenges, and pathways for future sustainable development

The chemical industry has been pivotal to the rapid economic expansion and high standards of living in China. As an important carrier of the chemical industry, China has designated as many as 723 chemical industrial parks (CIPs). Unfortunately, safety concerns have become an obstacle to the sustainability of China's CIPs. Ever since the two devastating hazardous chemical accidents, namely “Tianjin Port 8·12 Explosion” and “Jiangsu 3·21 Explosion,” which occurred in 2015 and 2019 respectively, China has prioritized the safety of CIPs. The smart chemical industrial parks (SCIPs) are considered the optimal strategies toward the goal of sustainable development in China's CIPs. However, there has been a lack of research and subsequent discussion on the role of SCIPs in the forthcoming years. The period between 2020 and 2025 is considered a crucial period for the future development of CIPs and SCIPs in China mainly because the country has released a series of important government documents and national standards (such as “Fourteenth Five-Year (2020–2025) Plan for Hazardous Chemical Safety” and “Guidelines of SCIPs construction”) to promote hazardous chemical safety. With the aim of analyzing the future sustainable development for the construction of SCIPs in China, this paper proposes a systematic methodology in order to conduct an integrated and in-depth review on the standardization construction status (framework with Chinese characteristics, key events, spatial features, and national pilots), future tasks, problems, and sustainable development pathways of China's SCIPs. The method is implemented in accordance with the current scenarios of hazardous chemical safety in China and the latest government documents, regulations, and standards. Furthermore, this study provides basic data and a basis for future studies associated with the safety and sustainability of the SCIPs construction and chemical industry, both within China and in other countries.     

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

A method is presented for analysis of reliability of complex engineering systems using information from fault tree analysis and uncertainty/imprecision of data. Fuzzy logic is a mathematical tool to model inaccuracy and uncertainty of the real world and human thinking. The method can address subjective, qualitative, and quantitative uncertainties involving risk analysis. Risk analysis with all the inherent uncertainties is a prime candidate for Fuzzy Logic application. Fuzzy logic combined with expert elicitation is employed in order to deal with vagueness of the data, to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing.The proposed model is able to quantify the fault tree of LPG refuelling facility in the absence or existence of data. This paper also illustrates the use of importance measures in sensitivity analysis. The result demonstrates that the approach is an apposite for the probabilistic reliability approach when quantitative historical failure data are unavailable. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process.     

消防科学技术发展历程回顾及火灾科学与消防工程学科体系探讨

在回顾消防科学技术发展历程的基础上 ,论述了火灾科学与消防工程学科体系与分类。火灾科学与消防工程学是一门以火灾发生与发展规律及其预防与扑救技术为研究对象的新兴交叉性学科。其具备火灾学、消防技术和消防工程所形成的完整知识体系 ;其下属的子学科包括火灾学、防火工程、灭火工程、消防管理工程、灭火指挥工程、火灾原因调查技术及其他相关学科。大力开展火灾科学与消防工程学科体系领域的研究 ,推进消防科学技术学科建设 ,是社会进步与科技发展的必然 ,也是加入WTO后保证经济国际化发展的客观要求。     

Risk assessment methodology for high-pressure CO2 pipelines incorporating topography

This paper presents a risk assessment methodology for high-pressure CO₂ pipelines developed at the Health and Safety Laboratory as part of the EU FP7 project CO2Pipehaz.Traditionally, consequence modelling of dense gas releases from pipelines at major hazard impact levels is performed using integral models with limited or no consideration being given to weather bias or topographical features of the surrounding terrain. Whilst dispersion modelling of CO₂ releases from pipelines using three-dimensional CFD models may provide higher levels of confidence in the predicted behaviour of the cloud, the use of such models is resource-intensive and usually impracticable. An alternative is to use more computationally efficient shallow layer or Lagrangian dispersion models that are able to account for the effects of topography whilst generating results within a reasonably short time frame.In the present work, the proposed risk assessment methodology for CO₂ pipelines is demonstrated using a shallow-layer dispersion model to generate contours from a sequence of release points along the pipeline. The simulations use realistic terrain taken from UK topographical data. Individual and societal risk levels in the vicinity of the pipeline are calculated using the Health and Safety Laboratory's risk assessment tool QuickRisk.Currently, the source term for a CO₂ release is not well understood because of its complex thermodynamic properties and its tendency to form solid particles under specific pressure and temperature conditions. This is a key knowledge gap and any subsequent dispersion modelling, particularly when including topography, may be affected by the accuracy of the source term.     

油气储运设施事故风险指数模糊逻辑评估方法

油气储运设施风险是其事故发生概率和事故后果的综合度量,而事故概率和后果的定量评估结果往往是具有不确定性的数据,以确定性风险评估准则为基础的传统风险矩阵法和风险值法显然难以评估油气储运设施风险。为此提出开展油气储运设施事故风险的模糊逻辑推理法,首先,对风险矩阵的概率语言等级和损失语言等级的边界进行定量划分;然后,建立油气储运设施风险矩阵模糊集和模糊逻辑推理规则;最后,通过风险模糊推理运算和模糊风险解模糊化以确定油气储运设施的风险水平。实例应用与分析表明,利用推荐方法可得到较为详尽的风险数据信息,不但风险指数更加清晰,而且其所属风险等级类别也更加明确,评估结果能更好地指导油气储运设施的风险管理。