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。     

基于贝叶斯网络气化炉供料系统风险分析

为解决当前气化炉供料系统风险分析不完善的状况，提出1种基于贝叶斯网络和HAZOP的风险分析模型。以某单日投煤量3 000 t级气化炉煤化工企业实际运行情况为研究对象，应用HAZOP法对其进行风险分析，并将HAZOP分析结果中各偏差产生原因转化为贝叶斯网络节点；考虑到先验知识的缺乏问题，引入Leaky Noisy OR模型，通过文献资料和相关领域专家经验知识获得先验概率，并利用贝叶斯网络进行风险分析，找出系统运行的薄弱环节。结果表明:未知因素影响会使各节点的后验概率值差异性降低，更加贴合实际；在引入未知因素影响后，系统运行薄弱环节并未发生改变。     

冲击载荷下各向异性煤体渗透-应力敏感性试验研究*

为揭示冲击煤样渗透率的变化规律，通过立式分离式霍普金森（SHPB）冲击装置对不同层理方向煤样进行动态冲击，进而采用渗透仪对冲击后的煤样进行渗透率测试，分析不同冲击荷载下煤岩的渗透率及应力敏感性。结果表明:冲击煤样的渗透率远大于原煤样品，冲击载荷越大，渗透率越大；在相同的冲击载荷和气体压力下，平行于层理方向的煤样渗透率最大，其次是斜交45°层理方向的煤样渗透率，垂直于层理方向的煤样渗透率最小；渗透率受有效应力影响显著；在冲击荷载的作用下，垂直于层理方向煤样渗透率的变化率对孔隙压力更为敏感。     

维修时间不确定性下配电网灾后维修队安排的鲁棒恢复研究*

为最小化灾后配电网损失量，准确描述完整维修队工作时间（分为路途时间与具体维修时间），依据台风路径对维修队所需路途时间进行分类，并利用期望概率描述具体维修时间的不确定性。建立2阶段分布式鲁棒优化模型，采用CCG算法分析国内某地区配电网算例发现:考虑维修时间不确定性可以有效减少配电网损失量。     

Experiment and simulation research of evolution process for LNG leakage and diffusion

The frequent occurrence of LNG leakage accidents has caused serious economic loss and environmental damage. Experiments and simulations can be combined to obtain the transient process of LNG leakage and diffusion. This paper analyzed LNG leakage diffusion rules with experiment results obtained by depleting 1.4t LNG. The vapor clouds and LNG concentration are measured, which can be a comparison with the simulation results. Computational fluid dynamics and gas diffusion theory were chosen as the theoretical basis, simulating the transient process of LNG gasification to obtain the diffusion concentration rules. The simulation of LNG diffusion is divided into two parts: LNG leakage at the source and atmospheric diffusion. The maximum concentration of methane in the experiment was 4.1%, and the maximum concentration in the simulation was 4.6%. The results show good agreement of the deviation statistics, which fall in the standard recommendation value range. Then we make a prediction of the dangerous concentration area and the flammability hazard zone of LNG leakage accident. The simulation results show that the range of the lower wind direction danger area firstly increases and then decreases, and the maximum distance of IDLH increases firstly and arrived at the peak of 52  m at 300s.     

风电场环境影响评价原则及评价重点研究

针对风电场环境影响评价的评价原则及评价重点进行了探讨性的研究。提出了风电场环境影响评价应以早期介入和避让措施优先为基本原则；对风电场环境影响评价重点进行了识别，并提出风电场选址的环境可行性分析是风电场环评的重中之重；风电项目建设对生态环境的影响及风机噪声、光影影响也是风电场环境影响评价的重点，并创造性的提出风机噪声光影联合防护区的概念，以期对风电场环境影响评价提供理论及技术参考依据。     

Confidence-based quantitative risk analysis for offshore accidental hydrocarbon release events

Quantitative risk analysis (QRA) has been widely used to conduct the assessment of offshore accidental risks. However, the accuracy and validity of QRA is significantly affected by uncertainties when subjective judgments are involved. Therefore, it is unrealistic to determine the probability of a hazardous event by using one single explicit value when safety experts have a relatively low confidence level in their judgments. This paper proposes a new methodology for incorporating uncertainties into conventional QRA using the concept of confidence level. Offshore hydrocarbon release hazards are focused on and a barrier and operational risk analysis (BORA-Release) method is selected as the basic model to illustrate the proposed methodology. A left–right (L–R) bell-shaped fuzzy number is employed and its membership curve is able to control its shape to represent different confidence levels. As to the complex geometry of the bell-shaped fuzzy number, an α-cut operation is introduced to conduct the arithmetic operations of the fuzzy number, and a defuzzification method with total integral value is chosen to match the α-cut operations and acquire complete information for the fuzzy numbers. In the meantime, an optimism index is used to describe the attitude of the decision-maker. One case study is provided in this paper to demonstrate the implementation of this method.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.