基于模糊评判人工神经网络的重大危险源辨识研究

国家已经制定了重大危险源辨识标准,辨识依据是危险物质的数量,主要适用于化工行业.本文对于国家重大危险源辨识标准不适合的行业,结合各行业发生事故的特点和工艺特征,综合利用模糊评判法和人工神经网络,辨识企业内存在的重大危险源.在某化工厂进行了检验,实践证明了方法的科学性和合理性.     

高效复合菌在木薯酒精废液处理中的应用研究

对酒精废液生物处理反应器内颗粒污泥中的微生物进行分离纯化.分离出的8株高效优势菌,初步鉴定结果:1号为皮杆菌属;2号为棒杆菌属;3号、4号为微小杆菌属;5号为乳杆菌属;6号为纤维单胞菌属;7号为丙酸杆菌属;8号为红长命菌属.对8种纯化后的菌株进行混合培养,确定了复合菌群生长最佳培养温度为37℃,最适pH值为6.8.在处理过程中投加适量葡萄糖、硝酸铵和微量元素能够提高复合菌群的处理效果.最佳添加量为:葡萄糖0.5g/L,硝酸铵1g/L,Fe2 5mg/L和Ca2 25mg/L.在日处理量100 m3的UASB生物反应器中投加该复合菌群后,木薯酒精废液的COD去除率明显提高,达到90%以上.处理系统运行稳定.     

基于数据库的煤矿危险源辨识系统研究

目前,煤矿大多采用的是检查项和检查内容固定的安全检查表法,为提高煤矿危险源辨识效率和准确性,遏制煤矿事故的发生,从职业安全健康管理体系角度,探讨了煤矿危险源辨识问题,并设计了以煤矿安全信息管理系统为基础的危险源辨识系统,模拟煤矿现场实际情况;依据职业安全健康管理体系中危险源管理的模式筛选出数据库中的相关信息,动态生成与之相适应的安全检查表。同时对煤矿安全信息管理系统的结构、功能以及辨识程序进行了分析。     

论焦化行业环境风险防范措施及应急预案

本文对焦化行业的原辅材料及产品的理化性质、生产过程中潜在的环境风险进行了识别,并在此基础上有针对性的提出了焦化行业环境风险防范措施及应急预案。     

化学品危险性鉴别分类研究的现状与展望

从对GHS(化学品分类及标记全球协调制度)化学品危险性鉴别分类的分析出发,归纳和总结了联合国、欧盟、美国以及中国的化学品危险性鉴别分类研究现状;提出化学品危险性鉴别分类是获取化学品安全信息、评估化学品的固有危险性的重要手段;给出化学品危险性鉴别分类试验必须满足OECD(经济合作与发展组织)的各项标准和准则;对化学品危险性鉴别分类的应用前景及未来工作进行评述和展望;指出为化学品安全管理、事故应急救援、事故调查及做好基础数据的积累是今后研究工作的努力方向;提出了借鉴GHS,REACH(化学品注册、评估、许可和限制)等先进化学品安全监管法规,对完善我国的化学品安全监管制度,化学品鉴别分类标准的重要现实意义。     

Comparison of Microscopic and Macroscopic Modeling Approaches for Subsurface Contaminant Transport

The practice of contaminant transport and remediation has shown significant progress in recent years. However, despite the significant progress made, remediation efforts are often delayed by extremely long breakthrough curve tails that render efforts to bring the level of contaminants below the regulatory standards inefficient. One hypothesis is that these long tails are due to the reservoir-like slow diffusive processes in soil micropore zones. This study compares the effects of micropores at macroscopic and microscopic levels and establishes a link between these approaches for validation and calibration purposes. The link between macroscopic and microscopic levels is established through comparisons and testing of the two models while incorporating appropriate scale and boundary effects. Despite the differences in conceptual approaches and simulation time, the two approaches rendered meaningful results. The link helps forecast the effects of micropore zone transport processes in the subsurface efficiently and thus allows development of numerical tools that could contribute towards more efficient remediation design.     

An improved vehicle-pedestrian near-crash identification method with a roadside LiDAR sensor

Problem: Potential conflicts between pedestrians and vehicles represent a challenge to pedestrian safety. Near-crash is used as a surrogate metric for pedestrian safety evaluations when historical vehicle–pedestrian crash data are not available. One challenge of using near-crash data for pedestrian safety evaluation is the identification of near-crash events. Method: This paper introduces a novel method for pedestrian-vehicle near-crash identification that uses a roadside LiDAR sensor. The trajectory of each road user can be extracted from roadside LiDAR data via several data processing algorithms: background filtering, lane identification, object clustering, object classification, and object tracking. Three indicators, namely, the post encroachment time (PET), the proportion of the stopping distance (PSD), and the crash potential index (CPI) are applied for conflict risk classification. Results: The performance of the developed method was evaluated with field-collected data at four sites in Reno, Nevada, United States. The results of case studies demonstrate that pedestrian-vehicle near-crash events could be identified successfully via the proposed method. Practical applications: The proposed method is especially suitable for pedestrian-vehicle near-crash identification at individual sites. The extracted near-crash events can serve as supplementary material to naturalistic driving study (NDS) data for safety evaluation.     

Beyond demographic identities and motivation to learn: The effect of organizational identification on diversity training outcomes

There is a pressing need for better explanations of diversity training effectiveness so that organizations can administer training programs that facilitate positive intergroup interactions. In this paper, we consider the unique predictive effect of organizational identification on diversity training outcomes beyond the effects of the traditional predictors of demographic-based identities and motivation to learn across two samples of employees involved in diversity-related training at their employing organizations. Organizational identification predicted unique variance in voluntary participation in diversity training, diversity training-related knowledge application, motivation to transfer diversity training, and diversity training-related organizational citizenship behavior intentions. Research and practitioner implications are discussed based on our findings.     

安全风险分级防控在油气开发领域的探索与应用

为推动油气开发领域安全风险分级防控有效落地,提高风险预控能力,本文基于风险防控现状评估结果,探索性地研究安全风险分级防控思路,构建了油气开发领域安全风险分级防控体系推进模型,提出了逆向与正向危害因素识别方法,明确了风险评价关键隐性过程原则,构建了"风险—后果—能资"分级防控决断模型。选取典型试点单位进行实践,结果证明,油气开发领域安全风险分级防控体系推进模型是科学合理的,其他领域也可借鉴该模型开展安全风险分级防控工作。     

新型冠状病毒肺炎疫情期间企业生产安全风险管理

本文在分析新型冠状病毒肺炎疫情期间企业安全风险特点的基础上,建立了疫情期间安全风险管理模型,分析了这一特殊时期企业外部变化,以及企业内部人、物、环境、管理变化带来特殊安全风险,提出了针对性的风险管控措施。