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Logistic回归的燃气管网风险因素重要度分析方法研究

为确定燃气管网风险评估的关键风险因素,以A省各地市燃气管网为研究对象,基于燃气专家经验确定燃气管线风险等级,提出基于Logistic回归的燃气管网风险因素重要度分析方法。采用样本增强及随机抽样的方式,选取400个均衡样本作为管网评估数据输入,通过因子分析方法对其进行降维,得到3个公共因子并作为一级指标反向构建燃气管网风险评估指标体系;利用有序多分类Logistic回归方法,根据回归系数绝对值大小对风险因素进行重要度排序。研究结果表明：外界环境对燃气管网风险的贡献程度相对较高,管道自身因素和巡检养护次之。研究结果可为城市燃气风险防控提供理论依据和方法参考。     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

Dynamic-risk-informed safety barrier management: An application to cost-effective barrier optimization based on data from multiple sources

An integrated approach for performance assessment and management of safety barriers in a systemic manner is needed concerning the prevention and mitigation of major accidents in chemical process industries. Particularly, the effects of safety barriers on system risk reduction should be assessed in a dynamic manner to support the decision-making on safety barrier establishments and improvements. A simulation approach, named Simulink-based Safety Barrier Modeling (SSBM), is proposed in this paper to conduct dynamic risk assessment of chemical facilities with the consideration of the degradation of safety barriers. The main functional features of the SSBM include i) the basic model structures of SSBM can be determined based on bow-tie diagrams, ii) multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) may be combined to update barrier failure probabilities and initiating event probabilities, iii) SSBM is able to handle uncertainty propagation in probabilistic risk assessment by using Monte Carlo simulations, and iv) cost-effectiveness analysis (CEA) and optimization algorithms are integrated to support the decision-making on safety barrier establishments and improvements. An illustrative case study is demonstrated to show the procedures of applying the SSBM on dynamic risk-informed safety barrier management and validate the feasibility of implementing the SSBM for cost-effective safety barrier optimization.     

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.     

中国主粮作物生物炭产量效应的Meta分析

为定量评估生物炭对主粮作物产量的影响,收集了公开发表的116篇相关文献,共866对数据,采用Meta分析法定量分析了生物炭对我国主粮作物产量的影响及其影响因子,同时构建结构方程模型(SEM)进一步解释了因子间的交互关系.结果表明,与不施用生物炭相比,生物炭施用后可改善主粮田土壤理化性质,提高主粮作物产量,平均增产率为8.77%.其中,当生物炭pH为7～8时,平均增产率最大,可达26.49%;其C/N<60时,平均增产率为13.73%,显著高于C/N≥60的平均增产率.将生物炭施入酸性或中性土壤中,更能发挥其增产效应.当施炭量为10～20 t·hm^-2时,小麦和玉米的平均增产率最大;施炭量为15～25 t·hm^-2时,水稻平均增产率最大.但是,不同施炭水平的水稻增产率相近,可考虑损失部分产量,适当减施以兼顾经济效益.此外,生物炭增产效应会随施用年限增加而不断减弱,一般3 a后增产不显著.SEM表明生物炭施用量不仅直接影响主粮作物产量,还通过改善土壤肥力间接影响主粮作物产量,而生物炭C/N和pH仅通过改善土壤肥力影响主粮作物产量.因此,今后...     

飞机实验室气候试验风险识别及分析

目的 研究飞机实验室气候试验过程中风险的识别及分析问题.方法 根据飞机实验室气候试验流程,针对试验设计、试验准备、试验实施和试验确认等阶段进行风险识别和分析.结果 及结论识别并分析出实验室气候试验各阶段的风险,并在国内首次某民机实验室气候试验中得到应用.     

大气监测时段优化布点技术研究

基于虚拟仪器技术的空气监测系统中电化学气体传感器价格昂贵且使用寿命短暂,文章利用多目标特征分析法对传感器监测时段进行布点,准确反映实时监测状况,减少传感器使用频率。     

农村环境污染控制区划方法与应用研究

针对农村环境污染发生的广域性、分散性和随机性等特征,采用清单分析法,核算了农村环境污染物COD、TN、TP排放量和排放浓度,并以环境污染敏感性评价和污染类型划分为研究基础,探讨了农村环境污染控制区划方法,提出了区划原则、分区方法和命名方法.采用上述方法,在江苏省进行了应用研究,将江苏省农村环境污染控制区共划分为3个一级区和13个二级区,对不同级区实施分区管理和分类控制,分区结果可以为农村环境污染控制决策提供科学依据.