基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

社会资本对山区居民山洪灾害应急避险能力的影响研究*

为研究社会资本对山区居民应急避险能力的影响,在广泛调研的基础上采用结构方程模型分析社会资本与山区居民应急避险能力各要素之间的作用关系。结果表明:个人网络对避险知识和避险意识有显著的正向影响,对避险行为影响不显著;信任与避险知识和避险意识呈显著的正向影响,而与避险行为呈反向影响,但信任可以通过避险知识和避险意识间接正向影响避险行为;互惠对避险知识影响不显著,但互惠与避险意识和避险行为存在显著的正向关系;避险知识和避险意识对避险行为呈显著正向影响,其中避险意识对避险行为影响更为显著。因此可以通过增加山区居民社会资本的方式提高山区居民山洪灾害应急避险能力。     

铁路沿线可燃重气储罐最小隔离区域划分探讨*

为保护铁路线,以某化工厂距离高铁路线最近的丙烯球罐为例,提出丙烯球罐泄漏最小隔离区域划分方法以及2种保护高铁线路方案,利用重气扩散模型和定量风险评价（QRA）软件分别进行丙烯扩散模拟、爆炸模拟,并进行危险与可操作性分析（HAZOP）和保护层分析（LOPA）。结果表明:球罐发生泄漏及火灾爆炸等事故,会给附近铁路线带来严重破坏;丙烯泄漏或球罐因周围其他设备设施或可燃物质着火而温度升高时,保护措施不足;隧道的安全可靠性要高于仅设1道防爆墙,隧道长度需覆盖最小隔离区域的可及范围,在扩散区域内也需设立普通挡墙,在极度危险情况下,需要实施高铁停开等保护措施。     

基于社会技术系统的复工企业疫情防控风险路径研究*

为对复工企业疫情防控中的风险致因因素进行分析,探寻复工企业疫情防控的风险路径,基于社会技术系统理论,建立宏观工效学模型,通过查阅并分析国家、地方政府、企业文件以及相关文献,从人员、技术、组织管理、内部环境及外部环境5个子系统出发,识别出16个复工企业疫情失控致因因素;运用社会网络分析（SNA）构建复工企业疫情防控关系网络,对各因素节点中心度进行计算,分析各节点在网络中的位置及影响程度;采用贝叶斯网络（BN）进行参数学习和推理学习,找出复工企业疫情失控的最大致因链。结果表明:复工企业疫情失控关系网络中,存在政府监督管理不力→防疫物资筹备不足→日常监管不到位,政府监督管理不力→ 防疫宣传、培训缺失→员工防疫知识欠缺,政府监督管理不力→防疫宣传、培训缺失→日常监管不到位3条最长风险路径。研究结果可帮助复工企业针对最长风险路径中的因素进行管理,从而有效地为复工企业防疫提供理论支持。     

波浪与抛石潜堤相互作用的MPS法数值模型研究

为了研究波浪与抛石潜堤相互作用过程中大自由表面变形和堤内渗流等强非线性紊流运动问题,利用改进的MPS法,建立了模拟波浪与抛石潜堤相互作用的MPS法数值计算模型。模型将抛石潜堤假定为均质多孔介质,采用Drew的二相流运动方程描述多孔介质内外的流体运动;通过在动量方程中增加非线性阻力项,并引入亚粒子尺度紊流模型,模拟波浪与可渗结构物相互作用过程中的紊流运动。选取“U”型管中多孔介质内渗流过程和孤立波与可渗潜堤相互作用两个典型的渗流问题,通过将数值计算结果与理论解和实测值的对比分析,对所提出的MPS法紊流渗流模型的模拟精度进行验证。结果表明：基于改进的MPS法构建的垂向二维紊流渗流模型可以很好地再现 “U”型管中多孔介质内渗流以及波浪作用下可渗潜堤内外的复杂流场,显著缓解流-固界面处的压力震荡与粒子分布不均匀问题,实现了较高的模拟精度。     

山西省绿色转型发展现状评价及路径研究

从经济、社会、资源、环境保护4个层面构建了切合山西省实际情况的绿色转型发展指标体系,采用熵权法及聚类分析方法对山西省的绿色转型发展现状进行了评价,根据评价结果,结合政策背景,提出了山西省实现绿色转型发展的路径,以实现山西省均衡快速的绿色转型发展。     

Comparative analysis of data reduction techniques for questionnaire validation using self-reported driver behaviors

Introduction: Exploratory data reduction techniques, such as Factor Analysis (FA) and Principal Component Analysis (PCA), are widely used in questionnaire validation with ordinal data, such as Likert Scale data, even though both techniques are indicated to metric measures. In this context, this study presents an e-survey, conducted to obtain self-reported behaviors between Brazilian drivers (N = 1,354, 55.2% of males) and Portuguese drivers (N = 348, 46.6% of males) based on 20 items from the Driver Behavior Questionnaire (DBQ) on a five-point Likert Scale. This paper aimed to examine DBQ validation using FA and PCA compared to Categorical Principal Component Analysis (CATPCA) which is more indicative to use with Likert Scale data. Results: The results from all techniques confirmed the most replicated factor structure of DBQ, distinguishing behaviors as errors, ordinary violations, and aggressive violation. However, after Varimax rotation, CATPCA explained 11% more variance compared to FA and 2% more than PCA. We identified cross-loadings among the component of the techniques. An item changed its dimension in the CATPCA results but did not change the structural interpretability. Individual scores from dimension 1 of CATPCA were significantly different from FA and PCA. Individual scores from factor 1 of CATPCA were significantly different from FA and PCA. Practical applications: The CATPCA seems to be more advantageous in order to represent the original data and considering data constrains. In addition to finding an interpretable factorial structure, the representation of the original data is regarded as relevant since the factor scores could be used for crash prediction in future analyses.     

System safety assessment using safety entropy

Safety assessment has a primary role in hazardous operations. Most studies on safety assessment focus on risk and accident modeling, in which safety is absent. These top-down methods are highly dependent on the occurred accidents to establish accidental scenarios, which may make the assessment approach lagging behind the evolving modern systems. Moreover, this “special to general” logic is scientifically suspect in safety assessment. There is a call for the development of safety assessment methods in the presence of system safety to complement risk-focused safety analysis. These methods should provide a framework based on a bottom-up approach to examine system safety from the operational perspective. This paper has attempted to provide a potential solution. In particular, a novel concept of safety entropy is proposed to integrate with The Functional Resonance Analysis Method (FRAM), which is used to form the qualitative understanding of a system. A formula consisted of safety entropy, functional conformability, and system complexity has been established to determine the spontaneity of the safety state-changing process. The proposed method is applied to the safety assessment of a propane feed-control system. The results show the applicability of the method. Nevertheless, the model still needs to be further improved to fulfill better support for safety-related decision problems.     

Multi-criteria decision-making considering risk and uncertainty in physical asset management

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.     

Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.