Optimal gas detector placement under uncertainty considering Conditional-Value-at-Risk

A stochastic programming formulation considering Conditional-Value-at-Risk (CVaR) is developed for the optimal placement of gas detectors in petrochemical process facilities. A rigorous gas dispersion simulator, FLACS, is used to generate release scenario data for a real process geometry. We consider two problem formulations: minimization of expected detection time and minimization of expected detection time subject to a restriction on CVaR across the scenario set. The extensive form of each stochastic program is formulated in Pyomo and solved using CPLEX. Considering all scenarios, we compare key values and histograms of detection times for both formulations. Minimizing the mean detection time only can lead to optimal detector placements with a good expected behavior, but unacceptable worst-case behavior. The formulations that minimize or constraint CVaR produce sensor placements with significantly better worst-case behavior and fewer scenarios having high detection times. Considering these results, a strong case for the use of optimal sensor placement using stochastic programming considering CVaR is made for improving safety systems.     

原油储罐区可燃气体探测器布置优化方案研究

为有效预警原油储备区储罐气体泄漏,制定气体探测器布置优化方案,以某大型原油站库为例,基于CFD法和FLACS软件模拟原油泄漏及可燃蒸汽云溢散分布,通过分析蒸汽云扩散规律,实现全方位气体探测器优化布置.结果表明:原油储罐区探测器分别布置在区块21-2、6-1、31-1、40-2,且每个罐组总计布置16处;优化设置方案可满...     

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.     

Development of a risk-based maintenance (RBM) strategy for a power-generating plant

The unexpected failures, the down time associated with such failures, the loss of production and, the higher maintenance costs are major problems in any process plant. Risk-based maintenance (RBM) approach helps in designing an alternative strategy to minimize the risk resulting from breakdowns or failures. Adapting a risk-based maintenance strategy is essential in developing cost-effective maintenance policies.The RBM methodology is comprised of four modules: identification of the scope, risk assessment, risk evaluation, and maintenance planning. Using this methodology, one is able to estimate risk caused by the unexpected failure as a function of the probability and the consequence of failure. Critical equipment can be identified based on the level of risk and a pre-selected acceptable level of risk. Maintenance of equipment is prioritized based on the risk, which helps in reducing the overall risk of the plant.The case study of a power-generating unit in the Holyrood thermal power generation plant is used to illustrate the methodology. Results indicate that the methodology is successful in identifying the critical equipment and in reducing the risk of resulting from the failure of the equipment. Risk reduction is achieved through the adoption of a maintenance plan which not only increases the reliability of the equipment but also reduces the cost of maintenance including the cost of failure.     

The TNO multi-energy method combined to mathematical programming and computational fluid dynamics for optimisation of gas detectors

Gas leakage is a matter of concern for several industries such as oil and gas, mining, food, and healthcare. When the industry considers gas detectors, the main questions are: How many gas detectors are required? Where is the best location to install them? To answer these questions Computational Fluid Dynamics (CFD) simulations and optimisation procedures are employed to calculate the plume location and plume volume to better position the gas detectors. We investigated how the optimisation cell size for the set covering problem can be calculated based on a given explosion overpressure threshold. Resorted by the multi-energy explosion model, we calculate the flammable cloud volume associated with a pre-defined overpressure value. The cloud volume is applied in the solution of the set covering problem and an optimal set for the gas detectors is obtained. The final gas detector network (number and location of the devices) is validated against CFD simulations for small releases. The results provide evidence that the optimal gas detector networks is able to detect gas leaks within a feasible time.     

一种关于点型探测器火灾探测能力的评估方法

以探测器火灾信息数据库为依据,通过对目前使用最为广泛的各种点型感烟、感温及CO气体探测器对八种典型试验火响应数据测量及数据挖掘,提出用梯度幅值评估方法,对上述探测器的火灾探测能力作出相应的评估结论,为城市建筑火灾自动探测报警系统的正确设计、选型和使用提供了参考理论依据。     

Research based on double coverage rate and reliability of gas detector layout optimization

The gas detector layout should be highly attuned to combustible gas leakage and attain a good reliability in avoiding detector malfunction, which is an important guarantee for the normal production of the chemical industry and other related enterprises. Herein, a gas detector layout optimization method based on double coverage and reliability is proposed. The key gas leakage monitoring area is determined through layout scene field investigation. To improve the detection probability and detection system reliability, the dual coverage target and voting mechanism are set, and the gas detector layout is determined with the ray-casting algorithm according to the coverage target. Combined with FLACS software to simulate a variety of typical leakage conditions under different layout scenarios, the relationship between the leaked gas concentration detected by gas detectors in each layout scheme and time is obtained, and the gas leakage detection probability in each layout scheme, number of detectors that can trigger the alarm, shortest time to trigger the alarm and reliability are comprehensively evaluated. The decision-maker selects the final gas detector layout plan according to the evaluation results and actual site needs. The study shows that the detection probability of each layout scheme set according to the double coverage is high, and multiple detectors can trigger the alarm (up to 100%), which ensures that the alarm can be triggered within 10 s under all applicable conditions. According to the evaluation results, the decision-maker can obtain a layout scheme that not only agrees with the actual site conditions but also attains a high detection probability, short detection time and strong reliability.     

Developing a risk-based maintenance model for a Natural Gas Regulating and Metering Station using Bayesian Network

During the last decades, the vital role of maintenance activities in industries including natural gas distribution system has cleared up progressively. High costs may induce to reduced maintenance and, in turn, lead to a lower availability and high risk of undesired events. Therefore, a probabilistic model, based on an acceptable level of risk, is required to avoid under and over estimation of maintenance time interval. This paper presents an advanced Risk-based Maintenance (RBM) methodology to optimize maintenance time schedule. Bayesian Network (BN) is applied to model the risk and the associated uncertainty. The developed method can assist the asset managers to work out the exact maintenance time for each component according to the risk level. To demonstrate and discuss the applicability of the methodology, a case study of Natural Gas Reduction and Measuring Station in Italy is considered. Results prove that the most critical components are the calculator and pilots, while the most reliable one is the odorization. Furthermore, the pressure and temperature gauge (PTG), the remote control system (RCS) and the meter are predicted as the components that require less time to transit from minor risk to catastrophic risk.     

火灾探测综合模拟实验平台

针对火灾探测器性能检测准确性，方便性和可重复性的要求，立足国家探测器检测标准，研制了一个火灾探测综合模拟实验平台。该装置设计了开环和闭环两种可切换的工作方式。通过由模拟段与测试段组成的实验通风管道来模拟真实的火灾环境，并可施加一定的环境干扰信号，本平台还设计了集烟装置，从而可对火灾探测器的性能进行全面检测和评价。     

Fuzzy-AHP在LNG接收站风险辨识中的应用

笔者以液化天然气(LNG)接受站的生产工艺、设备、作业环境的特点为背景,提出一种基于模糊层次分析方法(Fuzzy-Analytic Hierarchy Process)的风险评估方法。首先,根据LNG接收站风险事故多层次、多因素及不确定的特点,结合本行业的安全标准,确立了LNG接受站的风险因素和评价指标,建立接受站的安全评价体系;随后,运用Fuzzy-AHP方法确定权重矢量和模糊评价矩阵,并通过模糊运算求出决策矢量,实现对风险因素的排序以达到风险辨识目的;最后,对国内某LNG站进行了实例计算。计算表明该接收站的硬件设施完善,但应加强风险管理,制定相应的措施应对因气候条件、储罐区管理不当及船舶安全保护不到位等引发的事故。结果表明基于LNG站的Fuzzy-AHP风险辨识模型的安全性综合评价是有效的。     

罐区气体泄漏PHOENICS数值模拟研究

基于紊流模式理论,在考虑重力影响的基础上,建立储气罐区气体泄漏扩散数学模型,并采用计算流体力学软件PHOENICS(双曲性,抛物性或椭圆型数值求解综合编码)对该数学模型进行数值求解。在油气安全综合平台上,通过选用二氧化碳作为泄漏物,红外二氧化碳传感器采集来的实验数据与PHOENICS模拟数据进行比较,发现误差较小。同时表明,借用该软件模拟储气罐区气体泄漏的扩散问题是可行的。运用该法也能为气体泄漏、火灾方面的研究提供一条便利的捷径。研究结果还可以为液化气与毒气罐区气体泄漏事故应急处理提供参考依据,同时对罐区浓度探测点位置的安放也有重要指导意义。     

液化石油气球罐泄漏危险的预防和控制探讨

阐述了液化石油气球罐的特点。对液化石油气球罐的泄漏危险性进行了分析,主要存在的泄漏危险有泄漏物质易燃易爆、易发生泄漏、受热易膨胀导致泄漏、泄漏气体易积聚、泄漏事故具有隐蔽性、泄漏物质具有毒害性。根据液化气泄漏危险性分析,提出了预防和控制液化石油气球罐泄漏危害的安全措施:加强设备质量管理,杜绝泄漏现象;合理设置球罐,降低泄漏风险;规范安全操作,减少泄漏量;防止泄漏气体积聚;设置防泄漏安全装置;及时发现泄漏;设置消防给水及灭火设施;妥善处理泄漏事故。     

特种设备应急救援预案的研究

本文分析了特种设备的安全状况、应急救援预案的管理要求和现状,提出了应急救援预案的构成要素及其主要内容,以液化石油气储罐为例阐述了危险源辨识、后果预测以及现场应急处置方法,为企业编制特种设备应急预案提供了参考。     

Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant

Petrochemical facilities and plants require essential ongoing maintenance to ensure high levels of reliability and safety. A risk-based maintenance (RBM) strategy is a useful tool to design a cost-effective maintenance schedule; its objective is to reduce overall risk in the operating facility. In risk assessment of a failure scenario, consequences often have three key features: personnel safety effect, environmental threat and economic loss. In this paper, to quantify the severity of personnel injury and environmental pollution, a failure modes and effects analysis (FMEA) method is developed using subjective information derived from domain experts. On the basis of failure probability and consequence analysis, the risk is calculated and compared against the known acceptable risk criteria. To facilitate the comparison, a risk index is introduced, and weight factors are determined by an analytic hierarchy process. Finally, the appropriate maintenance tasks are scheduled under the risk constraints. A case study of a continuous catalytic reforming plant is used to illustrate the proposed approach. The results indicate that FMEA is helpful to identify critical facilities; the RBM strategy can increase the reliability of high-risk facilities, and corrective maintenance is the preferred approach for low-risk facilities to reduce maintenance expenditure.     

Optimization of gas detector placement considering scenario probability and detector reliability in oil refinery installation

Gas detection system is a critical layer of protection in process safety. Leak scenario probability and detector reliability are two key factors in the optimization of gas detector placement. However, they are easily neglected in previous studies, which may lead to an inaccurate evaluation of the optimization solutions. In this study, a stochastic programming (SP) optimization method is proposed considering these two factors. In order to quantitatively represent the probability of leak scenarios, a complete accident scenario set (CASS) is built combining leak sources and wind fields. Then, the computational fluid dynamics (CFD) method is adopted for consequence modeling of gas dispersion. The Markov model is developed to predict the detector reliability. With the objective of minimal cumulative detection time (MCDT), the SP formulation considering scenario probability and detector reliability (MCDT-SPR) is proposed. By introducing the particle swarm optimization (PSO) algorithm, the optimization formulations can be solved. A case study is investigated on a diesel hydrogenation refining unit. Results validate this approach is promising to improve the detection efficiency. This method is more practical and matching with the actual industrial environment, where the leak scenarios and the detector reliability can change dynamically in real process setting.     

基于MTBF的光电感烟探测器可靠性研究

针对火灾探测报警系统重要组成模块—光电感烟探测器-报警控制器,根据其在实际使用过程中的不完全故障数据,改良了前人对该问题的传统研究方法,并提出了分段定时截尾可靠性参数模型。该模型主要考虑火灾探测报警系统控制器工作时序性和故障处理时间的影响,采用自主提出的原始故障数据筛选统计方法,分别求得光电感烟模块的首次使用寿命与平均故障间隔时间的参数估计。该方法能够减少火灾探测报警系统初始使用寿命过长而产生的平均故障间隔时间的估计偏差,对于火灾探测报警系统整体使用寿命的估计和维修管理有着重要意义。同时基于序贯思想的动态截尾也克服了定时截尾模型无法准确判断试验停止时间的不足,在保证参数较为精确的前提下最大限度地节省时间和资源。     

Fault propagation behavior study and root cause reasoning with dynamic Bayesian network based framework

The Bhopal disaster was a gas leak incident in India, considered the world's worst industrial disaster happened around process facilities. Nowadays the process facilities in petrochemical industries have becoming increasingly large and automatic. There are many risk factors with complex relationships among them. Unfortunately, some operators have poor access to abnormal situation management experience due to the lack of knowledge. However these interdependencies are seldom accounted for in current risk and safety analyses, which also belonged to the main factor causing Bhopal tragedy. Fault propagation behavior of process system is studied in this paper, and a dynamic Bayesian network based framework for root cause reasoning is proposed to deal with abnormal situation. It will help operators to fully understand the relationships among all the risk factors, identify the causes that lead to the abnormal situations, and consider all available safety measures to cope with the situation. Examples from a case study for process facilities are included to illustrate the effectiveness of the proposed approach. It also provides a method to help us do things better in the future and to make sure that another such terrible accident never happens again.     

天然气储气罐破坏效应分析

针对城市天然气储气罐的不断兴建与发展趋势的大型化,对于已建和待建储罐区对周围环境的潜在安全性问题,指出运用破坏伤害范围评价法可直观地预测破坏效应。通过对储罐爆炸释放能量的估算,采用模拟比法结合TNT爆炸试验数据计算出距离储气罐不同距离处爆破冲击波超压值,运用超压准则模拟预测出不同规格、储压下储罐爆破破坏伤害严重程度及危及半径范围;采用世界银行推荐的危害关系式,结合伤害破坏等级分析天然气爆炸破坏效应并与爆破效应比较。5000m3储气罐、储压1.20MPa下,储罐爆破和天然气爆炸危及距离分别可达144.0m和247.7m。依据预测结果,可将罐区周围划分不同区域,为实际工程中罐区选址、建设、安全距离确定及安全预案制定提供参考。