A risk-based modelling approach to enhance shipping accident investigation

This paper developed a risk-based modelling approach to enhance the execution process of shipping accident investigation (SAI). Specifically, the paper addressed a fuzzy extended fault tree analysis (FFTA) that combines the effects of organizational faults and shipboard technical system failures under a unique risk assessment scheme. The case study illustrates that a novel idea behind the proposed methodology allows relevant accident investigators to clarify the probability of technical failures, operational misapplications, and legislative shortages leading to the shipping accident. The current SAI reports can be extended with an integrated risk assessment section to formulate integrated strategies along with risk control measures onboard ships. Since the consequences of shipping accidents are still a global concern, the paper addresses integration of a FFTA into SAI reports to ensure a consistent database and subsequent decision aid to accident analysis and prevention efforts in the maritime transportation industry.     

低温制高纯氮生产过程危险性分析及安全对策

针对低温冷冻制取高纯度(≥99.999%)氮气和液氮的生产工艺及装置,对其生产过程中存在或潜在的危险、有害因素进行辨识和分类,并作出危险和有害程度评价;明确物料泄漏、设备缺陷、人为因素等事故致因,特别对氮窒息事故进行案例剖析。同时,应用目的树分析方法,从工艺技术和安全管理角度,提出消除或减少生产性危险及职业性危害的安全对策和措施。结果表明:在低温制高纯氮生产过程中,采取技术上和管理上的安全对策与措施,能有效预防火灾、爆炸、氮中毒等事故发生,避免低温冻伤等职业危害,从而防患于未然。     

高空吊架坠落伤亡事故故障树分析

对高空吊架坠落伤亡事故产生的原因进行了分析,应用安全系统工程中的故障树分析方法,编制了故障树,进行定性分析。找出了导致吊架坠落伤亡事故发生的途径,并提出了一些预防措施。     

异质森林火灾模型及火灾扑救对森林生态系统的影响

森林火灾元胞自动机模型是研究自组织临界性的经典模型之一。这一模型中森林用一个二维网格来表示,其中每个格点代表一棵树或代表空地,各节点的树具有相同的生长概率和着火概率,以一定的规则进行演化。这一模型没有考虑树木间的差别,因而是同质的。我们考虑到不同树木间由种类、树龄等原因引起的生长概率与着火概率的不同,改进了经典森林火灾模型,提出了一个异质森林火灾模型,并研究了这一模型的自组织临界性。在新模型的基础上,研究了火灾扑救对森林群落分布的影响,给出了模拟结果,该结果与实际的观测结果得到符合。该文的研究可望对森林火灾预测及研究火灾扑救对森林生态系统的影响具有一定的意义。     

Integrating selected ecological effects of mixed European beech–Norway spruce stands in bioeconomic modelling

The simplicity of many bioeconomic models has been criticised several times, due to their lack of realism resulting from a deterministic nature and a single-species focus. In this context it was interesting to test the financial sensitivity of bioeconomic modelling against fairly well documented ecological effects in mixed forests. For this purpose our study linked existing results of ecological research with bioeconomic modelling. The presented methodological approach could not only show the importance of considering ecological effects in bioeconomic models; it in fact enabled prioritising ecological research from a financial point of view.In a first step, the possible influence of the tree species mixture on forest stand resistance, productivity and timber quality was derived from existing studies. In a second step, the available Monte Carlo simulations for Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.), simulated under site conditions and risks typical of southern Germany, were extended by the mentioned ecological effects and then evaluated from a financial perspective.The results showed a clear influence of all tested ecological effects on the financial indicators, financial risk and return. While testing each ecological effect separately, an increased resistance against wind, snow and insect attacks had the greatest influence on financial risk and return. It over-proportionally enhanced the financial return while simultaneously the financial risk was reduced. In contrast, a degraded timber quality could eliminate the positive effect of risk compensation in mixed forests almost completely. The least influence on the financial indicators finally showed a changed volume growth in mixed forests.A combination of the separately tested ecological effects (increased resistance, changed volume growth and decreased timber quality), between both tree species, underlined the dominating importance of the stand resistance. The integration of ecological effects, induced by interdependent tree species, in our bioeconomic model resulted in significantly lower financial risk than ignoring these effects. Moreover, the financial return of mixed stand variants with a proportion of Norway spruce greater than 60% even exceeded that of the most profitable pure stand.In conclusion this paper clearly confirmed that ignoring ecological effects in bioeconomic models could lead to seriously biased financial results. While a changed volume growth proved rather to be of minor importance for European beech/Norway spruce stands, tree resistance and timber quality may change the financial results significantly.     

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.     

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。     

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.