A proactive process risk assessment approach based on job hazard analysis and resilient engineering

Complex systems often experience a long period of incubation before accidents occur. Therefore, a proactive risk assessment is essential for process safety. The conventional job hazard analysis (JHA) method has been an effective tool to conduct a process risk assessment in the high-risk industrial field. However, the conventional JHA is inadequate for the proactive risk assessment since it is usually conducted during and before one specific operation process. Operations such as startup and maintenance are performed repeatedly on the lifecycle of a plant. Therefore, the risk reduction measures for the industrial process should include not only preventive actions obtained from the conventional JHA but also recovery ones. Resilience engineering (RE) has proven to be helpful for the recovery analysis of a complex system. The objective of this paper is to propose a proactive and comprehensive process risk assessment approach based on JHA and RE. The mechanism of applying RE to address operation process risk is illustrated. The integrated approach can provide guidelines to establish proactive risk reduction measures as well as maintain a low-risk level. Finally, a gas transmission startup process risk assessment case is presented to demonstrate its applicability.     

Fast,cheap, and imperfect? US public opinion about solar geoengineering

ABSTRACT

Solar geoengineering, which seeks to cool the planet by reflecting a small fraction of sunlight back into space, has drawn the attention of scientists and policymakers as climate change remains unabated. Unlike mitigation, solar geoengineering could quickly and cheaply lower global temperatures. It is also imperfect. Its environmental impacts remain unpredictable, and its low cost and immediate effects may result in ‘moral hazard,’ potentially crowding out costly mitigation efforts. There is little understanding about how the public will respond to such tradeoffs. To address this, a 1000-subject nationally representative poll focused on solar geoengineering was conducted as part of the Cooperative Congressional Election Study (CCES) of the US electorate in October–November 2016. The importance that individuals place on solar geoengineering’s speed and cost predicts their support for it, but there is little to no relationship between their concerns about its shortcomings and support for its research and use. Acquiescence bias appears to be an important factor for attitudes around solar geoengineering and moral hazard.     

A novel driver hazard perception sensitivity model based on drivers’ characteristics: A simulator study

Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.

Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers’ attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.

Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.

Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers.     

井下光谱多参数分析系统开发

本系统基于气体浓度光学分析方法理论朗伯-比尔(Lambert-Beer)定律、光谱气体检测技术开发,实现了对煤矿火灾与瓦斯灾害超前预警、灾害产生的有毒有害气体实时监测和煤矿环境气体爆炸危险性辨识,对于煤矿灾害防治、救灾过程中杜绝次生灾害,保障煤矿工人及救护队员的生命安全,促进煤矿安全生产具有重要意义。     

矿热炉炉壳安装作业危险性分析

为减少事故损失,必须对矿热炉安装施工危险源进行分析。基于此,对矿热炉安装工序中最重要工序炉壳安装应用作业危险性分析进行分析。将炉壳安装作业分成3大部分,用鱼刺图分析方法进行分析,总结出矿热炉炉壳安装中事故发生的主要原因并提出对策措施,以预防和减少事故的发生。     

Effect of admixture of solid inertant on fire hazard of dust layers oriented at varying degrees of inclination

Unlike metallic dust layers, the layer flammability levels (LFL) of non-metallic dust layers exhibit a wide range from Class 1 (No self-sustained combustion) to Class 6 (explosive combustion). However, determinations of layer flammability have not considered the effect of inclination angle, thereby potentially underestimating fire hazard of combustible dust layers in many industrial situations. In this research, inclined dust layers showed greater fire hazard than did horizontally oriented dust layers. For example, LFL of wood dust jumped from class 3 to class 5 when layers were positioned with an incline. Flame spread rate of PMMA dust layers increased from 1.8 to 3.6 mm/s when the angle of inclination increased from 0 to 40°. Even small amounts of solid inertant significantly decreased surface layer fires. The required amount of inertant to completely inert layer fires was far less than that for smoldering layer fires or dust explosions.     

某矿低铜废石综合回收利用项目职业病危害预评价

为了对某矿业有限公司低铜废石综合回收利用项目可能产生的职业病危害因素进行辨识、分析和评价，采用检查表、类比法相结合的原则对该项目的铲装、破碎、运输、筑堆等工艺进行分析评价，并利用经验法对浸出、萃取电积工艺进行分析评价。结果表明:类比工程中绝大部分粉尘、噪声检测点的浓（强）度符合国家标准；化学毒物、工频电场接触浓（强）度符合国家标准；电积车间的通风满足要求；萃取车间的事故通风能力不足。评价方法及通风计算方法对同类项目具有借鉴意义。     

A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

Framing of Geoengineering Affects Support for Climate Change Mitigation

The growing recognition that climate change mitigation alone will be inadequate has led scientists and policymakers to discuss climate geoengineering. An experiment with a US sample found, contrary to previous research, that reading about geoengineering did not reduce conservatives’ skepticism about the existence of anthropogenic climate change. Moreover, depending on how it is framed, geoengineering can reduce support for mitigation among both conservatives and non-conservatives. When geoengineering is framed as a major solution, people worry less about climate change, leading to reduced mitigation support. When framed as disastrous, people perceived geoengineering as riskier, also leading to a decrease in mitigation support. A more moderate framing of geoengineering as a partial solution is less susceptible to moral hazard effects. Overall, results suggest that geoengineering will not lessen political polarization over anthropogenic climate change, and could undercut support for mitigation efforts. Instead, framing geoengineering as a small piece to solving a big puzzle seems to be the best strategy to weaken this potential moral hazard.     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.