隐伏断裂的地气测量及其意义

传统概念的地气测量是指地下上升到地表并扩散到大气空间的天然状态气体 ,如CO2 、CH4 、Rn、Hg、H2 等。近十多年的研究证实地气还包含着新的内涵 ,即地壳岩石以及地表土壤中还存着痕量的金属与非金属气体 ,通过捕集这些气体 ,可以获得更多的深部地质构造、矿床信息。据报导 ,国内外的研究主要是在已知矿床上做的正演研究。本文是在已知隐伏断层构造上方地表 ,试验金属与非金属地气存在的可能性。     

拉伸加载下老化复合固体推进剂的损伤演化定量分析

目的 定量分析老化对拉伸加载下复合固体推进剂细观损伤演化的影响规律。方法 开展不同老化时间（0、32、74、98 d）下三组元端羟基聚丁二烯（HTPB）复合固体推进剂的热加速老化试验,以及老化后推进剂的微型哑铃形试验件在不同拉伸应变水平（0、5%、10%、20%、40%、50%）下的微CT扫描观测试验,并对扫描重构图像进行定量分析,获得老化对推进剂细观损伤演化的影响规律。结果 随拉伸应变增加,老化前后推进剂微CT图像的灰度均方差、平均孔隙率和图像的分形维数均呈非线性增加趋势,图像的灰度均值呈非线性减小趋势。在较低应变水平（<10%）下,上述参数受老化时间的影响不显著,但随拉伸应变增加（≥10%）和老化时间增长,灰度均方差、平均孔隙率、孔隙率增量和分形维数的数值整体增高,而灰度均值随老化时间的增长而降低,且不同老化时间下,分形维数与平均孔隙率之间存在正线性关系。结论 重构得到微CT图像的灰度均值、平均孔隙率和分形维数可作为表征参数,用于定量分析老化复合固体推进剂在拉伸载荷下的细观损伤和损伤的动态演化规律,推进剂的初始损伤和小应变下的损伤程度受老化的影响较弱,而老化时间对推进剂细观损...     

黄丝郁金不同采收期的产量和质量研究

目的:研究黄丝郁金不同采收期对产量和质量的影响,以确定适宜的采收时期。方法:设定10月、11月、12月、1月2、月5个不同采收时间,定期采收,测产,测试挥发油和姜黄素含量。结果:10—12月郁金产量有明显增加,12月至次年2月产量无明显差异;10—12月郁金的姜黄素和挥发油含量显著增加,12月至次年2月含量无明显差异。结论:总体看来,黄丝郁金的采收期以12月底为宜。     

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。     

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。     

Improved models of failure time for atmospheric tanks under the coupling effect of multiple pool fires

Fire accidents of chemical installations may cause domino effects in atmospheric tank farms, where a large amount of hazardous substances are stored or processed. Pool fire is a major form of fire accidents, and the thermal radiation from pool fire is the primary hazard of domino accidents. The coupling of multiple pool fires is a realistic and important accident phenomenon that enhances the propagation of domino accidents. However, previous research has mostly focused on the escalation of domino accidents induced by a single pool fire. To overcome the drawback, in this study, the failure of a storage tank under the coupling effect of multiple pool fires was studied in view of spatial and temporal synergistic process. The historical accident statistics indicated that the accident scenario of two-pool fires accounted for 30.6% in pool fires. The domino accident scenario involving three tanks is analyzed, and the typical layout of tanks is isosceles right triangle based on Chinese standard “GB50341-2014”. The thermal response and damage of a target tank heated by pool fires were numerically investigated. The volume of 500 m³, 3000 m³, 5000 m³ and 10000 m³ were selected. Flame temperature was obtained by FDS, and then was input onto the finite element model. The temperature field and stress field of target tanks were simulated by ABAQUS. The results showed that the temperature rise rate of the target tanks under multiple pool fires was higher than that under a single pool fire. The failure time of the tank under the coupling effect of multiple fires was lower than that under the superposition of multiple fires without the first stage. The stress and yield strength were compared to judge the failure of the target tank. The model of failure time for the tank under the coupling effect of pool fires was established. Through the verification, the deviation of this model is 4.02%, which is better than the deviation of 15.76% with Cozzani's model.     

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.