外循环厌氧处理工艺中布水和三相分离的改进研究

污水处理中的布水设备和三相分离设备存在很多缺点,通过旋流配水装置和传统配水装置、小间距斜板三相分离装置和传统三相分离装置的比较试验,研究了旋流配水装置和小间距斜板三相分离装置的性能.研究结果表明:在相同膨胀率的条件下,旋流配水装置所需的回流量小,能耗相对较少;在水力上升流速为8 m/h时,采用旋流配水装置进水时,污泥分布曲线较平缓,污泥在高度上分布较均匀,而采用传统配水装置进水时,污泥主要分布在反应器底部,污泥浓度分布不均匀;在上升流速相同的情况下,采用小间距三相分离装置的反应器出水携带的颗粒污泥浓度较小;在相同的进水COD浓度时,小间距三相分离装置分离的沼气量较多.改进的布水和三相分离装置的性能明显优于传统的布水和三相分离装置.     

北京市家具生产企业职业危害抽样调查

本文从北京市家具生产企业最多的区县中,有针对性地选择其中的18家企业进行现场抽样调查,并对其中的11家进行现场检测,研究北京市家具生产企业职业危害现状,通过现场调查和检测结果表明:北京市家具生产企业的管理者对职业危害的重视程度有所提高,但是从业者的自我保护意识仍然淡漠;生产环境不令人满意,作业场所粉尘超标严重;毒物浓度得到较好控制,主要毒物为苯及苯的同系物。该研究可为有关管理部门制定管理政策提供依据。     

基于拉曼光谱的铅致肝细胞生物分子变化研究

利用拉曼光谱技术采集不同铅离子暴露时间(0.5,1.5,3,6,12,24h)、暴露浓度(0.05,0.1,0.5,1,5mg/L)下HepG2细胞的光谱数据,欲探究在不同铅暴露条件下肝细胞的分子变化及其相关机制.研究结果发现,在不同条件下各组细胞的光谱形态基本相同,但部分特征峰的吸光度强度存在差异.经多元统计分析发现,除6h外,同一暴露时间下不同暴露浓度细胞的光谱数据在LD1上均存在离散趋势,并在暴露24h时最明显.细胞内蛋白质、脂质、核酸、类胡萝卜素、碳水化合物等生物分子的特征峰表现出明显差异,但不同类型生物分子发生显著变化的时间并不相同.由此可见铅暴露可损伤肝细胞蛋白质、脂质、核酸、类胡萝卜素的结构并影响其正常功能,这种毒性效应呈剂量-效应关系,且随暴露时间的增加而增加.本研究说明拉曼光谱可以实现铅对肝细胞生物分子变化的相关检测,这不仅为之后的细胞毒理研究提供了新的思路,同时也为环境污染物的安全评价提供了理论依据.     

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。     

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.     

淮河流域安徽段水体和沉积物微塑料赋存特征及风险评估

为探究淮河流域安徽段水体与沉积物微塑料赋存特征及生态风险级别,采用野外采样、体式显微镜、扫描电镜、傅里叶红外光谱（FTIR）以及风险指数（H）和污染负荷指数（PLI）模型等方法,分析了流域水体和沉积物微塑料现状,并进行了微塑料生态风险评估.结果表明,流域各点位微塑料检测率为100%,表层水与沉积物微塑料平均丰度分别为（39800±3367） n ·m^-3和（5078±447） n ·kg^-1,下游微塑料平均丰度要高于上游和中游.水体和沉积物微塑料粒径以20~150 μm为主,占比分别为82.96%和80.77%.微塑料形状主要为纤维（水体76.05%、沉积物84.53%）、薄膜（水体21.83%、沉积物15.43%）和碎片（水体2.12%、沉积物0.04%）.水体和沉积物中微塑料主要以透明颜色为主,占比分别为63.31%和83.69%.水体和沉积物主要以聚乙烯（水体65.74%、沉积物80.62%）和聚丙烯（水体18.43%、沉积物9.71%）为主,微塑料主要来源于农业薄膜、废弃渔具渔网和港口人为废弃的塑料袋.微塑料风险指数（H）模型评估表明部分点位风险指数较高,淮河流域安徽段微塑料风险等级为Ⅱ级,污染负荷指数（PLI）模型评估表明流域地表水体和沉积物总体上生态风险较低.