Importance of incorporation of personal communication devices in evacuation simulators

The importance of the incorporation of personal communication devices in emergency evacuation simulators will be discussed. Four case studies are examined to identify usage statistics and human behavior when using the devices in an emergency. The case studies are: 9/11 World Trade Center Attacks, London train bombings, Virginia Tech shooting and United Flight #93. The case studies’ findings are implemented into the Vacate evacuation simulator, which uses particle swarm optimization to mimic human pedestrian behavior. The physical actions of using a device, as well as the reaction to the information transmitted during usage, are examined. Findings show that the effects of the personal communication devices can affect individuals that are close to the user of the device, as well as those not in the local vicinity of the user. These effects, combined with the rapid mainstream acceptance of communication technologies, justify the implementation of personal communication devices into evacuation simulators.     

报废梯黑铝装药提取制备硫酸铝工艺研究

为回收梯黑铝混合装药中的铝,通过单因素试验及五因素四水平正交试验对提取工艺进行优化。结果表明,五因素影响顺序为:酸液浓度>颗粒尺寸>反应温度>液固比>反应时间;提取最佳工艺条件为:酸液浓度0.8 mol/L,炸药颗粒尺寸40~50目,反应温度45℃,液固比13 mL/g,反应时间90 min;所得硫酸铝产品品质较优。     

基于证据理论的煤矿瓦斯涌出组合预测

为提高煤矿瓦斯涌出量预测的准确度,引入证据理论组合预测方法。根据瓦斯涌出量及其主要影响因素间的实验数据,采用3个不同的粒子群神经网络模型对涌出量进行初步预测。并由BP、RBF网络对预测误差及预测点的影响因素进行分析建模,以获取每个模型的可信度。再利用证据理论对其进行合成,确定组合模型的权值,最终实现对瓦斯涌出量的组合预测。实例结果表明,该组合预测方法的平均绝对误差、均方误差分别为18.5%、5.8%,均小于神经网络组合法及等权平均法的相应预测误差,适用于煤矿瓦斯涌出量预测。     

火灾环境中油罐罐壁冷却优化部署研究

对油罐火灾中着火罐罐壁和邻近罐罐壁的温度分布进行了科学分析,并进行了罐壁冷却实验研究,研究不同油罐罐壁材质对冷却效果的的影响,以及有热源作用和无热源作用罐壁在不同流量冷却水作用下的温度变化规律。结果表明,不同罐壁材质对冷却效果的影响不大,在实际火灾中可忽略罐壁材质的影响;流量越大,冷却速度越快,但达到火灾冷却要求时,不同大小流量冷却水的冷却效果差异并是很大,合适的供水强度是油罐高效冷却的前提。对油罐火灾冷却力量的部署提出了优化原则,为防灭火工作提供了一定的科学依据。     

Factors contributing to US chemical plant process safety incidents from 2010 to 2020

Process safety incidents can result in injuries, fatalities, environmental impacts, facility damage, downtime & lost production, as well as impacts on a company's and industry's reputation. This study is focused on an analysis of the most commonly reported contributing factors to process safety incidents in the US chemical manufacturing industry. The database for the study contained 79 incidents from 2010 to 2019, partly investigated by the Chemical Safety Board (CSB). To be included in the study, the CSB archive of incident investigations were parsed to include only incidents which occurred at a company classified as 325 in the North American Industry Classification System (NAICS), assigned to businesses that participate in chemical manufacturing. For each incident, all of the identified contributing factors were catalogued in the database. From this list of identified contributing factors, it was possible to name the ‘top three’ contributing factors. The top three contributing factors cited for the chemical manufacturing industry were found to be: design; preventive maintenance; and safeguards, controls & layers of protection. The relationship between these top contributing factors and the most common OSHA citations was investigated as well. The investigation and citation history for NAICS 325 companies in the Occupational Safety & Health Administration (OSHA) citations database was then analysed to assess whether there was any overlap between the top reported contributing factors to process safety events and the top OSHA citations recorded for the industry. A database consisting of the inspection and citation history for the chemical manufacturing industry identified by NAICS code 325 was assembled for inspections occurring between 2010 and 2020 (August). The analysis of the citation history for the chemical manufacturing industry specifically, identified that the list of the top contributing factors to process safety incidents overlapped with the most common OSHA violations. This finding is relevant to industry stakeholders who are considering how to strategically invest resources for achieving maximum benefit – reducing process safety risk and simultaneously improving OSHA citation history.     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

Minimizing opportunity costs to aquatic connectivity restoration while controlling an invasive species

Controlling invasive species is critical for conservation but can have unintended consequences for native species and divert resources away from other efforts. This dilemma occurs on a grand scale in the North American Great Lakes, where dams and culverts block tributary access to habitat of desirable fish species and are a lynchpin of long‐standing efforts to limit ecological damage inflicted by the invasive, parasitic sea lamprey (Petromyzon marinus). Habitat restoration and sea‐lamprey control create conflicting goals for managing aging infrastructure. We used optimization to minimize opportunity costs of habitat gains for 37 desirable migratory fishes that arose from restricting sea lamprey access (0–25% increase) when selecting barriers for removal under a limited budget (US$1–105 million). Imposing limits on sea lamprey habitat reduced gains in tributary access for desirable species by 15–50% relative to an unconstrained scenario. Additional investment to offset the effect of limiting sea‐lamprey access resulted in high opportunity costs for 30 of 37 species (e.g., an additional US$20–80 million for lake sturgeon [Acipenser fulvescens]) and often required ≥5% increase in sea‐lamprey access to identify barrier‐removal solutions adhering to the budget and limiting access. Narrowly distributed species exhibited the highest opportunity costs but benefited more at less cost when small increases in sea‐lamprey access were allowed. Our results illustrate the value of optimization in limiting opportunity costs when balancing invasion control against restoration benefits for diverse desirable species. Such trade‐off analyses are essential to the restoration of connectivity within fragmented rivers without unleashing invaders.     

Subcritical water oxidation of propham by H2O2 using response surface methodology (RSM)

This study was conducted to investigate the degradation of propham, which is a compound that pollutes water and seriously threatens human health, by subcritical water oxidation and using H₂O₂ as an oxidising agent. The maximum total organic carbon removal rate of propham was obtained as 73.65% at 40 min of treatment time and 60 mM of H₂O₂ concentration and 373 K of temperature. In addition, response surface method based on the Box-Behnken design was applied to design the degradation experiments of propham for determination of the combined effects of process variables, namely temperature, concentration of oxidising agent and treatment time. The proposed quadratic model of propham degradation, which was examined with the analysis of variance, was used for navigating the design space. The R² and adjusted R² values of the model were determined as 0.9921 and 0.9819 respectively. It was shown that propham was effectively degraded, thus could be removed from the water by using an environmentally friendly method.     

How can process safety and a risk management approach guide pandemic risk management?

The coronavirus disease (COVID-19) brought the world to a halt in March 2020. Various prediction and risk management approaches are being explored worldwide for decision making. This work adopts an advanced mechanistic model and utilizes tools for process safety to propose a framework for risk management for the current pandemic. A parameter tweaking and an artificial neural network-based parameter learning model have been developed for effective forecasting of the dynamic risk. Monte Carlo simulation was used to capture the randomness of the model parameters. A comparative analysis of the proposed methodologies has been carried out by using the susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD) model. A SEIQRD model was developed for four distinct locations: Italy, Germany, Ontario, and British Columbia. The learning-based approach resulted in better outcomes among the models tested in the present study. The layer of protection analysis is a useful framework to analyze the effect of different safety measures. This framework is used in this work to study the effect of non-pharmaceutical interventions on pandemic risk. The risk profiles suggest that a stage-wise releasing scenario is the most suitable approach with negligible resurgence. The case study provides valuable insights to practitioners in both the health sector and the process industries to implement advanced strategies for risk assessment and management. Both sectors can benefit from each other by using the mathematical models and the management tools used in each, and, more importantly, the lessons learned from crises.