Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

基于社会技术系统的复工企业疫情防控风险路径研究*

为对复工企业疫情防控中的风险致因因素进行分析,探寻复工企业疫情防控的风险路径,基于社会技术系统理论,建立宏观工效学模型,通过查阅并分析国家、地方政府、企业文件以及相关文献,从人员、技术、组织管理、内部环境及外部环境5个子系统出发,识别出16个复工企业疫情失控致因因素;运用社会网络分析（SNA）构建复工企业疫情防控关系网络,对各因素节点中心度进行计算,分析各节点在网络中的位置及影响程度;采用贝叶斯网络（BN）进行参数学习和推理学习,找出复工企业疫情失控的最大致因链。结果表明:复工企业疫情失控关系网络中,存在政府监督管理不力→防疫物资筹备不足→日常监管不到位,政府监督管理不力→ 防疫宣传、培训缺失→员工防疫知识欠缺,政府监督管理不力→防疫宣传、培训缺失→日常监管不到位3条最长风险路径。研究结果可帮助复工企业针对最长风险路径中的因素进行管理,从而有效地为复工企业防疫提供理论支持。     

Rainfall Interception Based on Indirect Methods: A Case Study in Temperate Forests in Oaxaca,Mexico

Rainfall interception represents the amount of water trapped in natural cover that is not drained directly to the ground. Intercepted rainfall may evaporate after a rain event, making it one of the main drivers of water balance and hydrologic regionalization. This process can be affected by factors such as climate, altitude, vegetation type, and topography. Here is a simple method of calculating rainfall interception in temperate forests using in Santa Maria Yavesia, Oaxaca, and Mexico as an illustrative study area. We used two rain gauges to measure net precipitation (N_p) under the canopy at each study site and one gauge outside the canopy to obtain gross precipitation (G_p). Throughfall (T_h) was indirectly measured using hemispherical photographs. Rainfall interception was obtained through a combination T_h and G_p and N_p. The mean rainfall interception was 50.6% in the Abies forests, 23%–40% in the coniferous‐mixed forests, and 27.4% in the broad‐leaved forests. We classified rainfall events by intensity to determine the effect of canopy structure and precipitation and found that 75% of the events were weak events, 24% were moderate events, and 1% were strong events. In addition, we found that rainfall interception was lower when the intensity of precipitation was higher. Our method can be replicated in different ecosystems worldwide as a tool for assessing the influence of rainfall interception in terms of ecological services.     

A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

Techno-economic and environmental analysis of an integrated standalone hybrid solar hydrogen system to supply CCHP loads of a greenhouse in Iran

The techno-economic and environmental performance of hybrid solar hydrogen energy systems was investigated to provide combined cooling, heating and power (CCHP) demands of a standalone greenhouse in Iran to achieve sustainable agriculture based on an optimization procedure. From the environmental point of view, by deploying hybrid energy systems, 83%, to 100% of emissions can be avoided. Also a sensitivity analysis was performed on the hybrid energy systems in order to study the effect of major parameter variation on the systems justification. It was concluded that hybrid solar systems are economically competitive with conventional systems, for high solar intensity locations with high diesel fuel prices and decreased prices for PV and hydrogen storage technology.     

表土剥离对土地整治项目收益的影响研究

为了揭示表土剥离对土地整治项目收益的不同影响,作者采用采样分析、调查问卷、地统计分析、空间分析等方法对这种影响进行了分析。研究表明,表土剥离是土地整治工程必不可少的一步。通过土壤质量空间分布和作物投入一产出值比较分析,土地整治可有敬减少农业生产成本,而表土剥离可最大限度地保护土壤表层,通过追肥和田间管理,在2—3年时间可基本恢复耕地肥力。     

浅析物联网在环保产业中的应用

随着国际经济的迅速发展,物联网技术的发展呈现出不可阻挡的势头。本文阐述了物联网的概念和发展趋势,并从环保产业领域切入,探讨了物联网技术在环保产业领域的应用意义,通过物联网技术在环保产业中的应用案例,指出物联网技术在环保产业上的应用与发展是必然趋势。     

Inverse modeling of Asian Rn flux using surface air Rn concentration

When used with an atmospheric transport model, the ²²²Rn flux distribution estimated in our previous study using soil transport theory caused underestimation of atmospheric ²²²Rn concentrations as compared with measurements in East Asia. In this study, we applied a Bayesian synthesis inverse method to produce revised estimates of the annual ²²²Rn flux density in Asia by using atmospheric ²²²Rn concentrations measured at seven sites in East Asia. The Bayesian synthesis inverse method requires a prior estimate of the flux distribution and its uncertainties. The atmospheric transport model MM5/HIRAT and our previous estimate of the ²²²Rn flux distribution as the prior value were used to generate new flux estimates for the eastern half of the Eurasian continent dividing into 10 regions.The ²²²Rn flux densities estimated using the Bayesian inversion technique were generally higher than the prior flux densities. The area-weighted average ²²²Rn flux density for Asia was estimated to be 33.0 mBq m⁻² s⁻¹, which is substantially higher than the prior value (16.7 mBq m⁻² s⁻¹). The estimated ²²²Rn flux densities decrease with increasing latitude as follows: Southeast Asia (36.7 mBq m⁻² s⁻¹); East Asia (28.6 mBq m⁻² s⁻¹) including China, Korean Peninsula and Japan; and Siberia (14.1 mBq m⁻² s⁻¹). Increase of the newly estimated fluxes in Southeast Asia, China, Japan, and the southern part of Eastern Siberia from the prior ones contributed most significantly to improved agreement of the model-calculated concentrations with the atmospheric measurements. The sensitivity analysis of prior flux errors and effects of locally exhaled ²²²Rn showed that the estimated fluxes in Northern and Central China, Korea, Japan, and the southern part of Eastern Siberia were robust, but that in Central Asia had a large uncertainty.     

Probability of intellectual disability is associated with soil concentrations of arsenic and lead

Background

The association between metals in water and soil and adverse child neurologic outcomes has focused on the singular effect of lead (Pb), mercury (Hg), and arsenic (As). This study describes the complex association between soil concentrations of As combined with Pb and the probability of intellectual disability (ID) in children.

Methods

We used a retrospective cohort design with 3988 mother child pairs who were insured by Medicaid and lived during pregnancy and early childhood in South Carolina between 1/1/97 and 12/31/02. The children were followed until 6/1/08, using computerized service files, to identify the diagnosis of ID in medical records and verified by either school placement or disability service records. The soil was sampled using a uniform grid and analyzed for eight metals. The metal concentrations were interpolated using Bayesian Kriging to estimate concentration at individual residences.

Results

The probability of ID increased for increasing concentrations of As and Pb in the soil. The Odds Ratio for ID, for one unit change in As was 1.130 (95% confidence interval 1.048-1.218) for Pb was 1.002 (95% confidence interval 1.000-1.004). We identified effect modification for the infants based on their birth weight for gestational age status and only infants who were normal size for their gestational age had increased probability of ID based on the As and Pb soil concentrations (OR for As at normal weight for gestational age = 1.151 (95% CI: 1.061-1.249) and OR for Pb at normal for gestational age = 1.002 (95% CI: 1.002-1.004)). For normal weight for gestational age children when As = 22 mg kg⁻¹ and Pb = 200 mg kg⁻¹ the risk for ID was 11% and when As = 22 mg kg⁻¹and Pb = 400 mg kg⁻¹ the probability of ID was 65%.

Conclusion

The probability of ID is significantly associated with the interaction between Pb and As for normal weight for gestational age infants.