A data-driven narratives skeleton pattern recognition from accident reports dataset for human-and-organizational-factors analysis

Accidents in the process industry involve several interacting factors, including human and organizational factors (HOFs). A long-standing obstacle to HOFs analysis is lack of data. Accident reports are an essential data source to learn from the past and contain HOFs-related data, but they are usually unstructured text in a not standardized format. Some studies have explored the extraction of information automatically from accident reports based on Natural Language Processing (NLP) techniques. However, they were not dedicated to HOFs. Risk communication is considered an essential pillar in safety and risk science. This research develops a HOFs-focused risk communication framework based on the NLP techniques that can support risk assessment and mitigation. The proposed approach automatically extracts the target groups oriented “Who, When, Where, Why” (4Ws) information from accident reports.This framework was applied to explore the eMARS database. The results show that the “4Ws” skeleton of narratives has appreciated performance in pattern recognition and holistic information analysis. The graphical representation interfaces are designed to display the features of HOFs-related accidents, which can better be communicated to the sharp-end operators and decision-makers.     

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.     

爆炸超压场景下危化品社会风险对允许规划人口密度的影响分析*

为研究危化品重大危险源基于社会风险基准的规划管控影响,采用我国标准规定的定量风险评价方法,TNT当量炸药简化方法,针对最大TNT当量炸药、事故发生总累计频率、人口密度分布控制参数等不同工况条件,对比分析国土开发强度的允许人口密度受社会风险约束影响的变化规律。研究结果表明:人口密度指数分布控制参数Nk与Nb的允许取值随最大TNT当量炸药和事故发生总累计频率降低而提高;确定工况下,允许总人口规模受最大TNT当量炸药影响很小;在最大TNT当量炸药大于100 t或事故发生总累计频率小于1×10-8次/a时可按最大事故场景进行规划控制分析。     

深埋水平岩层隧道开挖稳定性分析及控制*

针对深埋高地应力水平岩层掌子面开挖稳定性及支护结构失效问题,以大峡谷隧道为工程背景,通过现场测试、室内试验、数值模拟等方法,探究深埋高地应力水平岩层失稳机理及控制措施。研究结果表明:坚硬岩体被节理面切割后,在高地应力作用下容易发生挤压破碎,破碎岩体遇水发生软化,导致掌子面发生大范围塌方,初支和超前支护失效;隧道开挖后岩层发生不均匀沉降,浅部岩层最先发生弯折破坏,层内块体错动滑移,继而向上方岩层发展,并伴随层间分离和层内裂隙发育,最终形成宏观破裂面;提出的台阶法、2 m开挖进尺、砼喷层、双层小导管、提高初支强度的整体优化控制措施,可有效提高现场支护效果。     

基于数据挖掘的施工危险识别注意投入与分配研究*

为分析施工情境中危险识别注意资源动态投入分配规律,基于动态时间规整算法,挖掘危险识别注视轨迹序列,以表征注意资源投入分配变化,并采用k-means聚类、注视熵、Needleman-Wunsch全局序列对齐算法和统计等方法,深入挖掘注意资源在危险目标中投入和分配等时空变化规律。研究结果表明:当事人危险识别各阶段注意资源呈现从显著目标到高危目标的投入变化趋势,危险识别注意资源分配随情境复杂因素呈现零散、均匀的空间特征,分配无序程度提高。     

Exploring the spatial dimension of community-level flood risk perception: a cognitive mapping approach

Environmental perceptions are central to individuals’ behavioural interactions with the environment. Cognitive maps, portraying a spatial representation of an individual’s environmental perception, can be aggregated to gain insight into the collective environmental perception of groups and populations. This paper uses cognitive mapping techniques to examine one aspect of environmental perception, flood risk perception, within a residential population (n?=?305). Flood risk perception was examined for the whole sample and six subgroup pairs. Using subgroups allowed examination of how factors previously shown to influence flood risk perception influence the cognitive map production in this population. We use a novel technique (slope analysis) to examine how the population’s perception of flood risk compares with expert assessments of flood risk, and compare the results of this novel technique with a commonly used cognitive map analysis technique (majority threshold method). Both methods identify areas where there is consensus within the population as to which areas are at risk of flooding. However, slope analysis usefully identifies areas where the population’s perception of flood risk lacks consensus, and is at odds with expert assessments of flood risk, without the loss of information inherent in the majority threshold method. Thus, this technique provides a novel approach to studies of environmental perception that can be widely applied within many fields.     

Evaluating betterment projects

In the past decade Australia has experienced a series of large‐scale, severe natural disasters including catastrophic bushfires, widespread and repeated flooding, and intense storms and cyclones. There appears to be a prima facie case for rebuilding damaged infrastructure to a more disaster resilient (that is, to ‘betterment’) standard. The purpose of this paper is to develop and illustrate a consistent and readily applied method for advancing proposals for the betterment of essential public assets, which can be used by governments at all levels to determine the net benefits of such proposals. Case study results demonstrate that betterment investments have the potential to deliver a positive economic return across a range of asset types and regions. Results, however, are highly sensitive to underlying assumptions; in particular the probability of the natural disaster affecting the infrastructure in the absence of betterment.     

Sources of organisational resiliency during the Thailand floods of 2011: a test of the bonding and bridging hypotheses

Based on the Institutional Collective Action framework, this research tests the impact of two competing hypotheses—bonding and bridging—on enhancing organisational resiliency. The bonding hypothesis posits that organisational resiliency can be achieved if an organisation works closely with others, whereas the bridging hypothesis argues that such a structure places considerable stress on an organisation and advocates for an organisation to position itself as a central actor to gain access to novel resources from a diverse set of entities to achieve resiliency. The paper analyses data gathered from semi‐structured interviews with 44 public, private, and non‐profit organisations serving communities affected by the Great Floods of 2011 in the Thai capital, Bangkok (urban), and in Pathum Thani (suburban) and Ayutthaya (rural) provinces. The findings suggest that: organisational resiliency was associated with the bridging effect; organisations in the rural province were more resilient than those in the suburban and urban centres; and private and non‐governmental organisations generally were more resilient than public sector organisations. The findings highlight the importance of fostering multi‐sector partnerships to enhance organisational resiliency for disaster response.     

Aggregating high-priority landscape areas to the parcel level: an easement implementation tool

Landscape characteristics and parcel ownership information are often collected on different spatial scales leading to difficulties in implementing land use plans at the parcel level. This study provides a method for aggregating highly resolute landscape planning information to the parcel level. Our parcel prioritization model directly incorporates a Land Trust's conservation goals in the form of a compromise programming model. We then demonstrate the use of our approach for implementation decisions, including parcel selection under a budget constraint and the estimation of a total conservation budget necessary to meet specific conservation goals. We found that these cost constraints significantly alter the composition of the 'best' parcels for conservation and can also provide guidance for implementation. The model's results were integral to a local Land Trust's ability to further define and achieve their goals.     

Prioritizing groundwater remediation policies: a fuzzy compatibility analysis decision aid

The implementation of groundwater remediation strategies in contaminated areas includes not only a cost-benefit analysis and an environmental risk assessment but also another type of study called compatibility analysis. A compatibility analysis targets the interactions between remediation technologies and site characteristics, such as the types of active contaminants and their concentrations, soil composition and geological features, etc. The purpose of this analysis is to identify the most compatible remediation plan for the contaminated site. In this paper, we introduce a decision support system for the prioritization of remediation plans based on their estimated compatibility index. As this model receives data in terms of linguistic judgments and experts' opinions, we use fuzzy sets theory to deal with these uncertainties. First, we break down the concept of compatibility into the measurable factors. Then by using a multiple-attribute decision-making (MADM) outline, we compute a factorial, regional and overall compatibility indicator for each plan. Finally, by comparing these generated indicators, we rank the remediation policies.