隧道爆破振动影响因素的灰色关联分析

为优化隧道爆破方案,降低爆破振动危害,采用灰色关联分析法(GRA)对爆破振动的影响因素进行分析。首先确定振动速度、主振频率和振动持续时间作为系统特征变量,确定总药量、最大段药量、掏槽孔最大段药量、雷管段数、爆心距、最小延期间隔时间、临空面数等作为相关因素变量;再结合厦门某隧道爆破实测数据,进行灰色关联计算;然后对计算结果进行排序和优势分析,得到爆破振动影响因素的主次顺序,其中准优因素为爆心距,可控准优因素为雷管段数和掏槽眼最大段药量;最后对隧道爆破参数进行优化,测点爆破振速由1.2 cm/s减小到0.74 cm/s,降振率达38.3%。结果表明,采用GRA确定爆破振动主要影响因素,为有效控制爆破振动提供理论依据。     

建筑施工安全效能ADC计算方法

为计算建筑施工安全系统的效能,基于ADC效能评估模型,尝试构建建筑施工安全系统效能的测算方程,该系统方程包括建筑施工安全可用度A的测算、建筑施工安全可信度D的测算、建筑施工安全固有能力C的测算和建筑施工安全效能干扰因子G的测算,进而推导出建筑施工安全系统效能评估的一般数理模型及特定模型,并以脚手架搭设系统为例进行效能测算。算例表明该数理模型可以较准确计算建筑施工安全子系统的效能。     

堆积体边坡渐进性破坏的随机模型

为精确模拟堆积体边坡变形破坏过程,根据堆积体所固有的非连续性、非均质性、各向异性等特点,以及边坡变形破坏的渐进性特征,采用改进的有限单元法(FEM)对堆积体边坡进行模拟。考虑堆积体边坡从连续位移函数到不连续位移函数的突变。破裂发生前,用连续位移函数进行计算;破裂发生后,引入不连续位移函数。研究结果表明,破裂面上不同点的安全系数(FOS)是不同的,但都随着破坏过程而降低。同时,可以得出不同非均匀程度下安全系数的概率分布。     

企业员工不安全行为影响因素量表的初步开发

本文通过大量资料的搜集,概括出了影响员工不安全行为的众多因素,并根据他们的可控性进行了分类.在此理论研究的基础上,用调查问卷的方法,构建了企业员工不安全行为的影响因素量表,并通过spss16.0软件包对其进行因素分析,检验量表的效度和信度,最终形成了四个企业员工不安全行为影响因素正式量表.其中包括:企业员工不安全行为个人安全素质影响因素量表、企业员工不安全行为领导影响因素量表、企业员工不安全行为组织影响因素量表和企业员工不安全行为工作内容和环境影响因素量表.此外,本文还对中交天航第五经理部的施工人员进行了实证研究,用spss16.0软件包对搜集到的数据进行分析,包括:各量表中包含的题项的内部分析、四个量表中所有题项的整体分析和每个量表中的群体差异性分析,并在以上分析的基础上,最终得出了该企业对员工不安全行为影响因素的管理现状.     

25 years of higher‐order confirmatory factor analysis in the organizational sciences: A critical review and development of reporting recommendations

We discuss how confirmatory factor analysis results should be used to examine potential higher‐order constructs and advocate that researchers present five types of evidence, which are as follows: (1) the ability of the higher‐order model to reproduce the observed covariation among manifest variables; (2) the ability of the higher‐order model to reproduce the observed covariation among manifest variables better than more parsimonious alternative models—and no less well than less parsimonious alternative models; (3) the ability of the higher‐order model to reproduce the observed covariation among lower‐order factors; (4) the ability of the higher‐order factor to explain variation in lower‐order factors; and (5) the ability of the higher‐order factor to explain variation in manifest variables. We illustrate how this type of evidence could be presented with a worked example and contrast our recommendations with the manner in which higher‐order confirmatory factor analysis has been used in the organizational sciences over the past 25 years to support claims regarding higher‐order constructs such as core self‐evaluations and transformational leadership. Our review shows that a substantial proportion of the 44 examined articles failed to present enough evidence to allow readers to understand the size and importance of higher‐order factors. Copyright © 2015 John Wiley & Sons, Ltd.     

软岩隧道塌方事故致灾因素耦合分析*

为减少专家主观判断对软岩隧道塌方事故评估的影响,提出1种从事故出发逆推分析事故致灾因素耦合机制的方法。基于142个隧道施工塌方事故案例,系统总结隧道塌方事故致灾因素,对塌方事故的致灾因素出现频率进行排序;从致灾因素之间关联耦合关系出发,结合隧道施工塌方事故的多因素耦合致灾机理,研究隧道塌方事故产生过程的多因素耦合路径和耦合过程;采用N-K耦合模型开展隧道塌方事故多因素耦合路径下的耦合关联值评估,并对耦合关联值进行排序从而找到控制塌方事故发生的致灾因素组合。结果表明:除4个主要致灾因素的全耦合外,围岩岩性-降雨-地下水的耦合关联值是洞身段中最大值,为17.79%,围岩岩性-偏压-地下水的耦合关联值是洞口段中最大值,为24.02%;洞身段的围岩岩性-地下水因素和洞口段的围岩岩性-偏压因素分别对耦合关联值大小起决定影响;耦合关联值不具备叠加效应,2因素耦合关联值可能比3因素耦合关联值更大。研究结果可为提高隧道事故分析与安全防控提供科学依据。     

川东北三高气田钻完井风险因素分析

分析了三高（高压、高产、高含硫）气田存在的主要有害因素,以及三高气田钻完井作业过程中存在的主要危险及其发生的潜在原因,并提出了相应的控制措施。针对我国三高气田区域地质环境的特殊性,分析了我国三高气田钻完井过程中可能诱发事故的特殊因素,并对应对措施进行了探讨。     

成品油站场工艺管道风险辨识与评价

为保障成品油站场工艺管道的安全平稳运行,在充分辨识风险因素的前提下,提出了一种基于KENT法和RBI的风险评价方法。首先,以风险机理分析为基础,采用SHEL模型从导致风险上升的直接原因（风险内因）和间接原因（风险外因）2个角度辨识了风险因素,并细化各因素指标项;然后借鉴KENT法,对各指标项进行评分量化;依据RBI法,采用风险外因体系修正风险内因体系的方式确定失效可能性;综合环境后果、人员后果与商业后果,明确失效后果的评价体系与计算方法;最后,结合失效可能性与失效后果进行风险评价,从风险等级和风险排序2方面为检维修决策提供依据。应用表明:该评价方法便于工艺管道风险评价的基层实施,可为基于风险的检维修决策提供有效技术支撑。     

Driving anger among motor vehicle drivers in China: A cross-sectional survey

Objective: Driving anger is a common emotion while driving and has been associated with traffic crashes. This study aimed to investigate situations that increase driving anger among Chinese drivers.

Methods: A cross-sectional study was conducted among 3,101 drivers in southern China. The translated version of the 33-item Driving Anger Scale (DAS) was used to measure driving anger. Data were collected by face-to-face interviews between June 2016 and September 2016.

Results: Confirmatory factor analysis showed that the fit of the original 6-factor model (discourtesy, traffic obstacles, hostile gestures, slow driving, illegal driving, and police presence) was satisfactory, after removing 2 items and allowing 5 error pairs to covary. The model showed satisfactory fit: goodness of fit index (GFI) = 0.90, incremental fit index (IFI) = 0.90, root mean square error of approximation (RMSEA) = 0.06, 90% confidence interval (CI) = 0.061–0.064. Driving anger among Chinese drivers was lower than that in some Western countries. Compared to older and experienced drivers, younger and new drivers were more likely to report driving anger. There was no difference in total reported driving anger between males and females. Additionally, the higher the driver’s anger level was, the more likely he or she was to have had a traffic crash.

Conclusion: Driving anger is a common emotion among Chinese drivers and has a strong correlation with aggressive driving behavior and traffic crashes.     

Major accident management in the process industry: An expert tool called CESMA for intelligent allocation of prevention investments

A tool (called CESMA) was developed to carry out cost–benefit analyses and cost-effectiveness analyses of prevention investments for avoiding major accidents. A wide variety of parameters necessary to calculate both the costs of the considered preventive measures and the benefits related with the avoidance of accidents were identified in the research. The benefits are determined by estimating the difference in (hypothetical) major accident costs without and with the implementation of a preventive measure. As many relevant costs and benefits as possible were included into the tool, based on literature and expert opinion, in order to be able to deliver an all-embracing cost–benefit analysis and cost-effectiveness analysis to assist in the investment decision process. Because major accidents are related to extremely low frequencies, the tool takes the uncertainty of the unwanted occurrence of a major accident into account through the usage of a so-called ‘disproportion factor’. Compared with existing software, the CESMA tool is innovative by striving for an as-accurate-as-possible picture of costs and benefits of major accident prevention, and taking the uncertainties accompanying disastrous events into consideration. Furthermore, an illustrative example of CESMA is presented in the paper.