基于RPN-BN的平台-隔水管系统遇内波风险分析

为保障内孤立波作用下的深水半潜式钻井平台-隔水管系统的安全,同时解决海洋平台系统设备失效数据的缺失问题,提出1种风险优先系数（RPN）与贝叶斯（BN）结合的定量风险分析方法。首先,基于故障树和安全屏障方法,建立平台-隔水管系统Bow tie模型和贝叶斯风险演化模型;其次,根据贝叶斯推断和风险优先系数中的事故发生频度估计,得到平台-隔水管系统失效事故的发生概率;最后,通过贝叶斯网络的逆向推理能力辨识内孤立波作用下引起平台-隔水管系统失效的主要风险节点,实现对平台-隔水管系统失效事故的定量风险分析。结果表明:RPN-BN法可应用于平台-隔水管系统遇内波的定量风险分析;加强对平台漂移量的控制,提高动力定位系统控制设备的可靠性可有效抵御内波对系统造成的影响。     

Resilience-based approach to safety barrier performance assessment in process facilities

The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly uncertain, making it challenging for the static indicators to assess the performance of safety barriers. This paper proposes a resilience−based performance assessment method for safety barriers to overcome this problem. Safety barriers are classified according to their functions first. The dynamic Bayesian network (DBN) is then introduced to calculate the availability function under normal and disruption conditions. The ratio of the system's availability, when affected by the disruption, to the initial availability, is used to determine the absorption capacity of the system. The ratio of the quantity of availability recovery to the total quantity of system represents the adaptation and restoration capacity of the system. The system's resilience is represented by the sum of absorption, adaptation, and restoration capacities. The wax oil hydrogenation process is used to demonstrate the applicability of the proposed methodology.     

A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks

Organizational factors are the major root causes of human errors, while there have been no formal causal model of human behavior to model the effects of organizational factors on human reliability. The purpose of this paper is to develop a fuzzy Bayesian network (BN) approach to improve the quantification of organizational influences in HRA (human reliability analysis) frameworks. Firstly, a conceptual causal framework is built to analyze the causal relationships between organizational factors and human reliability or human error. Then, the probability inference model for HRA is built by combining the conceptual causal framework with BN to implement causal and diagnostic inference. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual causal model with BN approach can not only qualitatively model the causal relationships between organizational factors and human reliability but also can quantitatively measure human operational reliability, and identify the most likely root causes or the prioritization of root causes causing human error.     

基于故障树与贝叶斯网络的钻井井塌事故的定量分析

井塌事故在钻井过程极其常见,由于钻井液、井身结构等设计不合理,以及钻井过程的误操作均会造成井塌的发生,其后果主要是造成卡钻、卡套管等事故,严重时造成井眼毁坏。为了对井塌事故进行危险性分析,采用贝叶斯网络与故障树相结合的方法,避免传统故障树方法的局限性。首先对井塌事故的所有危险因素进行辨识建立故障树,然后将故障树转化为贝叶斯网络,建立条件概率表,运用贝叶斯网络的推理能力对井塌事故进行危险性分析。对井塌事故各基本事件概率分布的计算分析结果表明,考虑事件的多态性,综合利用故障树分析法和贝叶斯网络法能有效提高井塌事故分析的有效性,推算出井塌事故概率分布更为准确。     

Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

Among the various techniques used for safety analysis of process systems, bow-tie (BT) analysis is becoming a popular technique as it represents an accident scenario from causes to effects. However, the BT application in the dynamic safety analysis is limited due to the static nature of its components, i.e. fault tree and event tree. It is therefore difficult in BT to take accident precursors into account to update the probability of events and the consequent risk. Also, BT is unable to represent conditional dependency. Event dependency is common among primary events and safety barriers. The current paper illustrates how Bayesian network (BN) helps to overcome these limitations. It has also been shown that BN can be used in dynamic safety analysis of a wide range of accident scenarios due to its flexible structure. This paper also introduces the application of probability adapting in dynamic safety analysis rather than probability updating. A case study from the U.S. Chemical Safety Board has been used to illustrate the application of both BT and BN techniques, with a comparison of the results from each technique.     

基于Bayesian网络的常减压装置设备故障概率分析

为分析影响常减压蒸馏装置平稳运行的设备失效模式及故障部件,基于1 151条设备故障数据,采用Bayesian网络分析方法,分别对离心泵、压缩机、电动机构建基于Bayesian网络的设备故障概率分析模型,分析故障部件、失效模式、故障后果之间的定量概率关系。研究结果表明：离心泵、压缩机、电动机停运的关键致因部件分别为轴承箱密封故障、活塞环故障、轴承故障,同时得到导致设备停运的故障部件敏感度排序。研究结果有助于提高设备故障风险防范及检维修工作效率,同时可为备件优化方案提供思路。     

A novel tool for Bayesian reliability analysis using AHP as a framework for prior elicitation

Quantitative risk assessment (QRA) is a powerful and popular technique to support risk-based decisions. Unfortunately, QRAs are often hampered by significant uncertainty in the frequency of failure estimation for physical assets. This uncertainty is largely due to lack of quality failure data in published sources. The failure data may be limited, incompatible and/or outdated. Consequently, there is a need for robust methods and tools that can incorporate all available information to facilitate reliability analysis of critical assets such as pipelines, pressure vessels, rotating equipment, etc. This paper presents a novel practical approach that can be used to help overcome data scarcity issues in reliability analysis. A Bayesian framework is implemented to cohesively integrate objective data with expert opinion with the aim toward deriving time to failure distributions for physical assets. The Analytic Hierarchy Process is utilized to aggregate time to failure estimates from multiple experts to minimize biases and address inconsistencies in their estimates. These estimates are summarized in the form of informative priors that are implemented in a Bayesian update procedure for the Weibull distribution. The flexibility of the proposed methodology allows for efficiently dealing with data limitations. Application of the proposed approach is illustrated using a case study.     

基于BN-CREAM的深水井控压井作业风险诱因研究

深水井控压井作业是有效控制溢流演化为井喷事故的二级井控工艺屏障。为提高深水井控压井作业可靠性,采用 BN-CREAM方法对其风险诱因进行研究。结合深水井控压井作业特点,考虑共因失效等因素,采用贝叶斯网络方法建立深 水井控压井作业风险演化模型。应用人因可靠性分析CREAM法计算深水压井人因失误先验概率,参考海洋可靠性数据手 册OREDA确定深水井控设备失效先验概率。依托贝叶斯网络的逆向推理能力辨识压井作业的主要风险节点,从而实现对 深水井控压井作业风险诱因的有效预测和评估。研究表明:深水井控压井作业共包含6个关键风险根节点,且压井作业人 因可靠性要低于设备可靠性;3级子节点“压井方法选择不合理”对深水压井作业的成功起到至关重要的作用,需进一 步开展风险分析研究。     

Technical,human, and organizational factors affecting failures of firefighting systems (FSs) of atmospheric storage tanks: Providing a risk assessment approach using Fuzzy Bayesian Network (FBN) and content validity indicators

Most risk assessment methods have problems such as uncertainty, static structure, and lack of validation. Also, in most of these studies, less attention has been paid to human, managerial, and organizational issues. Therefore, this study proposes a risk assessment method based on the Fuzzy Bayesian Network (FBN) to prevent failure of firefighting systems (FFSs) in the atmospheric Storage Tanks of a Petrochemical Industry. The first stage of the study is the development of a fault tree (FT) and investigation of basic events (BEs). In this study, content validity indices and brainstorming technique were used to validate the FT structure and reduce the uncertainties of Completeness, Modeling, and Parameter. After determining the probability of basic events (BEs) by the expert team opinions and fuzzy logic, events were transmitted to the Bayesian Network (BN) and then analyzed with deductive and inductive reasoning, followed by sensitivity analysis in the GeNIe software. Finally, results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties. Also, taking account of hidden factors of events, such as organizational and managerial factors, can help managers to prevent FFSs in tanks.     

稠油热采井管柱失效动态风险分析研究

为保证稠油热采井筒管柱的安全运行,采用故障树与贝叶斯网络相结合的方法开展稠油热采井管柱失效风险分析,应用故障树分析方法定性识别管柱失效诱因,建立稠油热采井管柱失效场景演化模型,并将故障树转化为贝叶斯网络模型,应用贝叶斯网络对管柱失效风险进行定量分析,得出热采井管柱失效的关键致因和管柱失效的动态失效概率,以新疆油田某区块热采井的管柱失效为对象进行了案例分析。研究结果表明,该方法可为稠油热采井管柱失效风险分析及井筒完整性管理提供理论支撑和工程设计参考。     

基于BN的FTA在通用航空风险评价中的应用

针对事故树分析法(FTA)在风险评价中的局限性,采用以事故树为基础建立的贝叶斯网络(BN)风险模型,对通用航空中的两机空中相撞事故进行分析和推理,对事故模型进行改进和修正时,注重基事件的多态性和事件间的逻辑合理性。根据贝叶斯推理得出的数据,找到了事故的主要致因。结果表明,基于BN的FTA既能向前预测顶事件的发生概率,又能向后诊断基本事件的后验概率,可以更好地对通用航空风险进行评价。     

Mitigation of operational failures via an economic framework of reliability,availability, and maintainability (RAM) during conceptual design

Abnormal process situation may lead to tremendous negative impact on sustainability, wellbeing of workers and adjacent communities, company's profit, and stability of supply chains. Failure of equipment and process subsystems are among the primary causes of abnormal situations. The conventional approach in handling failure-based abnormal situations has usually focused on operational strategies. Such an approach overlooks the critical role of process design in mitigating failure, while simultaneously considering the effects of such failure on process economic performance. The aim of this work is to introduce a systematic methodology that accounts for failure early enough during the conceptual design stages. Once a base-case design is developed, the methodology starts by identifying the sources of failure that are caused by reliability issues including equipment, operational procedures, and human errors for a given process system or subsystem. This allows for the identification of critical process subsystem(s) that are more failure-prone or cause greater downtime than other subsystems. Bayesian updating and Monte Carlo techniques are utilized to determine the appropriate distributions for the failure and repair scenario(s), respectively, in question. Markov analysis is used to determine the system availability. Next, the process revenue is described as a function of inherent availability. The effects of failures are incorporated into profitability calculations to establish an economic framework for trading off failure and profitability. In the proposed framework, the economic potential of alternative design scenarios is evaluated and an optimization formulation with the objective of maximizing incremental return on investment (IROI) is utilized to make a design decision. A case study on an ethylene plant is solved to demonstrate the applicability and value of the proposed approach.     

API Standard 521 new alternative method to evaluate fire relief for pressure relief device sizing and depressuring system design

Since the 1950's, API Standards have provided guidance on determining relief loads for equipment exposed to pool fires. The API method is empirical based on tests performed in the 1940's. There is increasingly widespread interest in analytical methods based on heat transfer principles to model fire heat input. The API committee agreed to include an analytical method in the 6th edition of API Standard 521 to establish relief loads for pressure relief devices and to design depressuring systems for the fire scenario. The analytical method provides more flexibility than the empirical method but has limitations (e.g., too many permutations are possible leading to potential under-sizing of the pressure relief device).This paper discusses the basis for the empirical method in API Standard 521 and provides comparisons of the empirical and analytical method with two more recent large-scale pool fire tests. This pool fire test data indicates that the empirical method will provide a conservative estimate of pool fire heat input for most applications and is still the method of choice when designing pressure relief systems. However, these recent tests indicate the empirical method needs to be modified when a vessel or equipment is partially confined by adjacent embankments or walls equal or greater than the vessel height. In such cases, the wetted area exponent should be 1.0 instead of 0.82.The analytical method is useful in determining time-versus-temperature profiles for heating unwetted vessels of varying wall thicknesses and materials of construction. These profiles, which depend upon the type of fire (e.g., unconfined pool fire, jet fire, etc.), can be combined with tensile strength and stress-rupture data to specify a depressuring system's pressure-versus-time profile. This will minimize failure and/or mitigate the effects of failure due to overheating from fire exposure.     

A bayesian network-based safety assessment method for solid propellant granule-casting molding process

The safety of the solid propellant molding process is vital for the stable production of high-quality propellants. Failure events caused by abnormal parameters in the molding process may have catastrophic consequences. In this paper, a Bayesian network (BN) model is proposed to assess the safety of the solid propellant granule-casting molding process. Fault tree analysis (FTA) is developed to construct a causal link between process variables and process failures. Subsequently, expert experience and fuzzy set theory (FST) are used to obtain failure probabilities of the basic events (BEs). Based on the mapping rules, FTA provides BN with reliable prior knowledge and a network structure with interpretability. Finally, when new evidence is obtained, the probability is updated with the diagnostic reasoning capability of BN. The results of the sensitivity analysis and diagnostic inference were combined to identify key parameters in the granule-casting molding process, including curing temperature, vacuum degree, extrusion, calendering roll distance, length setting value, holding time, and polish time. The results of this paper can provide effective supporting information for managers to conduct process safety analysis.     

Validation of liquid nitrogen vaporisation rate by small scale experiments and analysis of the conductive heat flux from the concrete

The vaporisation of a liquid nitrogen pool spilled on concrete ground was investigated in small scale field experiments. The pool vaporisation rate and the heat transfer from the concrete ground were measured using a balance and a set of embedded heat flux sensors and thermocouples. The ability to predict the concrete's thermal properties based on these measurements was investigated. This work showed that a simple, one-dimensional theoretical model, assuming heat conduction through a semi-infinite ground with ideal contact between the cryogenic liquid and the ground, commonly used to describe the heat transfer from a ground to the LNG, can be used to match the observed vaporisation rate. Though estimated parameters, thermal conductivity and thermal diffusivity, do not necessary represent real values. Although the observed vaporization rate follows a linear trend, and thus can be well represented by the model, the overall model prediction seems to be overestimated. The temperature profile inside the concrete is slightly over-predicted at the beginning and under-predicted at later stage of the spill. This might be an effect of the dependence of the concrete's thermal properties on the temperature or may indicate an incorrect modelling and a varying temperature of the ground surface.     

基于贝叶斯网络的汽车起重机液压系统的可靠性评估

为评估汽车起重机液压系统的可靠性,首先结合故障树分析法(FTA)、贝叶斯网络(BN)构建液压系统故障树,然后映射成BN,再利用其在多态性和不确定性方面的优势,应用桶排除法,对系统进行可靠性评估。在给出底事件的发生概率后,通过正向推理,得到顶事件发生的概率为0.191 016。针对模型进行多态性和不确定性修正后,得到的顶事件概率为0.228 073,相对提高19.4%。最后利用反向推理,找出系统的薄弱环节并给出改正措施,为更全面高效的可靠性评估提出一种新方法。     

Impact of flood water on the technical condition of natural gas transmission pipeline valves

Maintaining the reliability of a transmission system's operation is an extremely important issue in the context of ensuring the continuity of gas delivery to customers. Threats to maintaining the reliability of a transmission system's operation may appear at any stage of transmission, and the most common reasons for this are corrosion, material defects or accidental damage. The paper presents the impact of flood water on transmission valves in the context of possible threats to ensuring the technical safety of gas supplies. Hazards are described which relate to the chemical composition of flood water, which may cause corrosion of valve elements and risk of loss of gas pipeline stability caused by flooding. In the context of the design of a natural gas transmission network, the strength aspects and the phenomenon of corrosion are described. The results of tests related to a specific example are presented. The finite element method (FEM) is used to build ball valve models. Two types of valves are modelled for nominal pipeline diameters of 50 mm (DN50) and 200 mm (DN200). The results of the presented analysis show that the leak tightness of the tested valve flange connections was mainly influenced by changes in their operating conditions because the occurring additional forces and moments caused significant changes in the load balance of the flange connections.     

石化装置火灾爆炸贝叶斯网络与防护层集成分析

复杂的石油化工装置在运转过程中存在诸多不确定因素,易发生火灾、爆炸等重大事故,给安全生产带来极大威胁。考虑到传统的系统安全分析方法在风险评估中存在一定局限性,引入贝叶斯网络与防护层集成分析模型。应用GeNIe软件将系统故障树转成贝叶斯网络,根据贝叶斯双向推理进行故障预测和诊断,快速识别系统薄弱环节并确定为风险贝叶斯故障节点,结合防护层分析提出相应的独立防护层,确定剩余风险水平。实例应用表明,所构建的贝叶斯网络与防护层集成分析模型对复杂系统进行风险评估是可行的,较传统的事件树、故障树分析方法更加科学、合理。     

Risk assessment of safety level in university laboratories using questionnaire and Bayesian network

Accidents in university laboratories not only create a great threat to students’ safety but bring significant negative social impact. This paper investigates the university laboratory safety in China using questionnaire and Bayesian network (BN) analysis. Sixteen influencing factors for building the Bayesian net were firstly identified. A questionnaire was distributed to graduate students at 60 universities in China to acquire the probability of safe/unsafe conditions for sixteen influencing factors, based on which the conditional probability of four key factors (human, equipment and material, environment, and management) was calculated using the fuzzy triangular theory and expert judgment. The determined conditional probability was used to develop a Bayesian network model for the risk analysis of university laboratory safety and identification of the main reasons behind the accidents. Questionnaire results showed that management problems are prominent due to insufficient safety education training and weak management level of management personnel. The calculated unsafe state probability was found to be 65.2%. In the BN analysis, the human factor was found to play the most important role, followed by equipment and material factor. Sensitive and inferential analysis showed that the most sensitive factors are personnel incorrect operation, illegal operation, and experiment equipment failure. Based on the analysis, countermeasures were proposed to improve the safe management and operation of university laboratories.