Practical safety management for small or medium enterprises

The article is intended for those who are not safety professionals but are responsible for safety management in a small or medium enterprise (SME) of the process industry. It assumes that a SME is loosely coupled and of low complexity and has a small number of major hazards present in it. The article describes Elementary Safety Management (ESM) as a combination of activities that maintain openness to safety impulses with Elementary Risk Control (ERC). ERC uses four milestones and three rules to get to the necessary and sufficient selection of control measures, which will achieve an acceptable level of risk. To make the ESM scheme as simple as possible, the term causal event is used, which is derived from the term causal factor. Practical Safety Management (PrSM) adds to the ESM the knowledge and skills that a person, who is supposed to design and implement a safety management system, needs. The PrSM procedure is developed to identify optimum controls. The procedure recognizes the unavoidable role of commitment to safety, respects the role of hazard identification, and integrates prospective and retrospective analyses and current knowledge of safety management systems. Examples of application of the procedure are given in the article.     

A Long View of Southern California Water Supply: Perfect Droughts Revisited

The impact of drought on water resources in arid and semiarid regions can be buffered by water supplies from different source regions. Simultaneous drought in all major source regions — or perfect drought — poses the most serious challenge to water management. We examine perfect droughts relevant to Southern California (SoCal) water resources with instrumental records and tree‐ring reconstructions for the Sacramento and Colorado Rivers, and SoCal. Perfect droughts have occurred five times since 1906, lasting two to three years, except for the most recent event, 2012–2015. This number and duration of perfect droughts is not unusual in the context of the past six centuries. The modern period stands out for the relatively even distribution of perfect droughts and lacks the clusters of perfect drought documented in prior centuries. In comparison, perfect droughts of the 12th Century were both longer (up to nine years) and more widespread. Perfect droughts of the 20th and 21st Centuries have occurred under different oceanic/atmospheric patterns, zonal and meridional flow, and ENSO or non‐ENSO conditions. Multidecadal coherence across the three regions exists, but it has varied over the past six centuries, resulting in irregular intervals of perfect drought. Although the causes of perfect droughts are not clear, given the long‐term natural variability along with projected changes in climate, it is reasonable to expect more frequent and longer perfect droughts in the future.     

Comparative degradation between heavy and light crude oil mediated by nitrogen‐induced cell‐surface hydrophobicity

A bacterial strain UKMP‐10M2 isolated from a Malaysian petroleum refinery was able to degrade 84% of heavy Khafji sour crude and 68% of light Tapis sweet crude within seven days. Analysis of gas chromatography‐flame ionization detector chromatograms show the strain UKMP‐10M2 degraded up to 90% pristane and 50% phytane in heavy crude, but significantly lower pristane (50%) and phytane (30%) were degraded from the light crude. A mixture of aliphatic hexadecane and three‐ring phenanthrene better supported the growth of isolate UKMP‐10M2 compared to using phenanthrene alone, suggesting cometabolism influenced how crude oil with different individual hydrocarbon contents affected the degradation. Peptone as the source of nitrogen increases the emulsifying index in UKMP‐10M2 exposed to heavy Khafji sour crude 20% higher than in light Tapis sweet crude. However, BATH assay showed the same nitrogen source increases bacterial cell surface hydrophobicity of UKMP‐10M2 up to 14% higher in light Tapis crude oil compared to heavy Khafji. This study suggest the nitrogen source plays a decisive role in elevating UKMP‐10M2 bacterial cells hydrophobicity, and in correlation with types of crude oil. Phylogenetic tree analysis based on 16S rDNA sequence results identified the strain to be Rhodococcus ruber.     

Classification of driving workload affected by highway alignment conditions based on classification and regression tree algorithm

Objective: Guaranteeing a safe and comfortable driving workload can contribute to reducing traffic injuries. In order to provide safe and comfortable threshold values, this study attempted to classify driving workload from the aspects of human factors mainly affected by highway geometric conditions and to determine the thresholds of different workload classifications. This article stated a hypothesis that the values of driver workload change within a certain range.

Methods: Driving workload scales were stated based on a comprehensive literature review. Through comparative analysis of different psychophysiological measures, heart rate variability (HRV) was chosen as the representative measure for quantifying driving workload by field experiments. Seventy-two participants (36 car drivers and 36 large truck drivers) and 6 highways with different geometric designs were selected to conduct field experiments. A wearable wireless dynamic multiparameter physiological detector (KF-2) was employed to detect physiological data that were simultaneously correlated to the speed changes recorded by a Global Positioning System (GPS) (testing time, driving speeds, running track, and distance). Through performing statistical analyses, including the distribution of HRV during the flat, straight segments and P-P plots of modified HRV, a driving workload calculation model was proposed. Integrating driving workload scales with values, the threshold of each scale of driving workload was determined by classification and regression tree (CART) algorithms.

Results: The driving workload calculation model was suitable for driving speeds in the range of 40 to 120 km/h. The experimental data of 72 participants revealed that driving workload had a significant effect on modified HRV, revealing a change in driving speed. When the driving speed was between 100 and 120 km/h, drivers showed an apparent increase in the corresponding modified HRV. The threshold value of the normal driving workload K was between ?0.0011 and 0.056 for a car driver and between ?0.00086 and 0.067 for a truck driver.

Conclusion: Heart rate variability was a direct and effective index for measuring driving workload despite being affected by multiple highway alignment elements. The driving workload model and the thresholds of driving workload classifications can be used to evaluate the quality of highway geometric design. A higher quality of highway geometric design could keep driving workload within a safer and more comfortable range. This study provided insight into reducing traffic injuries from the perspective of disciplinary integration of highway engineering and human factor engineering.     

Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

Abstract

Objective: The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury.

Methods: All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (<2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level.

Results: The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (n?=?4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (n?=?651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases.

Conclusion: This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.     

基于ISM—CRITIC法的通用航空可控飞行撞地影响因素分析

为了研究通用航空可控飞行撞地的影响因素,提出针对性的预防措施,采用基元事件分析法对中国民航安全办公室不安全数据库中2006—2015年间发生的30起通用航空可控飞行撞地事件进行分析,建立通用航空可控飞行撞地影响因素体系;运用解释结构模型对影响因素进行两两对比分析,建立3层阶梯有向模型;运用CRITIC法计算各影响因素权重并排序。结果表明:影响通用航空可控飞行撞地事件的表层直接原因分别是注意力分配不当、违反标准运行程序、安全意识淡薄、应急能力弱、导航设备失效、发动机失效、其他天气意外、飞行保障不利和组织混乱;中层间接原因分别是驾驶技能不足、航前准备不足、机组资源管理欠缺、地形复杂、能见度和光线刺激;深层根本原因分别是疲劳驾驶、公司违规和违法组织飞行;影响通用航空可控飞行撞地事件发生的主要因素分别是飞行保障不利和组织混乱、航前准备不足、安全意识淡薄、驾驶技能不足和违反标准运行程序。     

碳交易机制下可再生能源投资价值与投资时机研究

中国承诺2017年启动全国性碳排放交易系统,在碳交易机制下,可再生能源项目可以通过CCER交易获得额外收益。由于碳价格是随着市场条件而随机波动的,碳价波动性使得可再生能源发电项目投资具有了期权性质的权利,即未来不确定性可能包含更高的价值。可再生能源企业在做投资决策时,可以选择立即投资,也可以选择推迟投资,等待更多信息来提高项目收益,而立即投资的项目回报必须足够高以克服等待期权的蕴含价值。为了研究碳价波动下可再生能源项目投资,本文采用实物期权法的三叉树模型,测算了三类可再生能源发电项目投资的npv及其实物期权价值(ROV)。根据延迟实物期权决策规则,三类项目均执行期权延迟投资决策。本文还计算了在无政府补贴和有政府补贴两种情形下,三种可再生能源项目在不同时点的栏杆价格,以确定项目的投资时机。栏杆价格随着政府补贴的增加而逐步下降,说明政府补贴会促进可再生能源项目投资;栏杆价格随着时间的推移而逐步上升,意味着时间跨度越大,不确定性越大,需要更高碳市场价格来确定投资时机。本文对影响可再生能源项目投资因素敏感性进行了分析,结果表明碳价波动率与可再生能源发电项目的栏杆价格呈现正相关的关系,说明碳价波动性增加了企业投资的期权价值,却推迟了企业开展投资的时间。随着中国碳交易体系的不断完善,碳价波动幅度会趋于平稳,从而促进发电企业进行可再生能源发电项目投资。     

沙尘天气发生频率对大气能见度方差的影响研究:以北京及其沙尘过往路径典型站点为例

利用1971～2000年北京及其沙尘过往路径典型站点日能见度和各种沙尘天气发生日资料,分析了沙尘天气发生频率与能见度方差的关系.发现当沙尘天气频率减少(增加)1次时,能见度方差就偏强(偏弱)1个标准差.沙尘天气发生频率对日能见度变率的影响主要是通过风速的高频变率实现的,当风速变率偏强(偏弱)1个标准差时,沙尘天气发生频率增强(减弱)约30%,近地面风场的高频变率影响了沙尘天气的产生,从而影响日能见度方差的波动.异常低能见度事件(日能见度距平<-2σ,σ为各站各日能见度距平的标准差)频次与能见度方差之间存在显著的正相关性.风速距平频次增加,使得沙尘天气发生频次增加,从而导致低能见度事件频次上升;反之,异常低能见度事件下降.浮尘、沙尘暴和扬沙与低能见度事件的相关程度是不同的.     

基于决策树技术及在线监测的水质预测

利用北方某城市水源的水质在线监测系统,建立了基于决策树技术,具有较强可视性和实际应用,以及能预测次日源水中叶绿素水平的决策树模型.该模型将某城市水源在线监测的溶解氧和太阳辐射照度数据转换计算为每日平均标准偏差及均值,并与每日定时取样测定的叶绿素含量一起作为预测因子,通过将115组数据的前100组数据作为训练集建立预测次日叶绿素水平决策树模型,并采用后15组数据进行模型的仿真预测检验,结果只有3 d的预测出错,预测准确率达80%.并讨论了模型建立对数据的要求及解读预测规则等问题.     

故障树分析法及其在导弹故障近似计算中的应用

介绍了故障树分析法的主要分析过程,指出故障树分析法是进行产品设计和系统故障诊断的有效方法,并利用Visual C 语言进行蒙特卡罗仿真,得到了近似计算故障树顶事件发生概率时应选取的最优权因子,最后指出该因子可以用在导弹等特殊设备故障的近似计算中。