A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

煤矿火灾烟气流动传播过程仿真研究

煤矿发生火灾后会生成大量有毒气体并产生火风压,烟气在火灾动力的影响下出现状态紊乱,研究煤矿火灾烟气流动传播过程对控制火情有着重要意义。基于国内外研究现状,对燃烧及风流特点进行分析,建立了煤矿火灾烟气流动数学模型,并利用CFD软件进行仿真。研究表明:无通风工况下的烟气为对称流动;随着风速增加,出口处温度降低,烟气向风流入口处的流速减小。     

Network analysis of a stakeholder community combatting illegal wildlife trade

The illegal wildlife trade has emerged as a growing and urgent environmental issue. Stakeholders involved in the efforts to curb wildlife trafficking include nongovernmental organizations (NGOs), academia, and state government and enforcement bodies. The extent to which these stakeholders work and communicate among each other is fundamental to effectively combatting illicit trade. Using the United Kingdom as a case study, we used a social network analysis and semistructured interviews of stakeholders to assess communication relationships in the counter wildlife trafficking community. The NGOs consistently occupied 4 of the 5 most central positions in the generated networks, whereas academic institutions routinely occupied 4 of the 5 most peripheral positions. However, NGOs were the least diverse in their communication practices compared with the other stakeholder groups. Stakeholders identified personal relationships as the most important aspect of functioning communication. Participant insights also showed that stakeholder-specific variables (e.g., ethical and confidentiality concerns), competition, and fundraising can have a confounding effect on intercommunication. Evaluating communication networks and intrastakeholder communication trends is essential to creating cohesive, productive, and efficient responses to the challenges of combatting illegal wildlife trade. Article impact statement: Communication among those combatting illegal wildlife trade is confounded by stakeholder variables (ethics, confidentiality), competition, and fundraising.     

Bibliometric analysis of simulated driving research from 1997 to 2016

Objective: The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

Methods: The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

Results: A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

Conclusions: This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.     

Performance evaluation of reverse logistics enterprise – an agent-based simulation approach

Reverse logistics (RL) has been applied in many industries and sectors since its conception. Unlike forward logistics, retracing consumer goods from the point of consumption to the point of inception is not a well-studied process. It involves many uncertainties such as time, quality and quantity of returns. The returned products can be remanufactured, have parts harvested, or be disposed safely. It is important to implement these activities in a cost-effective manner. The aim of this research is to measure the performance of the RL enterprise with the help of an agent-based simulation model. The major entities in the RL network are considered as Agents that can act independently. There are several different agents: collector agent, sorting-cum-reuse agent, remanufacturing agent, recycler agent, supplier agent and distributor agent. The individual performances of the agents are measured and recommendations are given to improve their performance, leading to the enhancement of the total performance of the RL enterprise. The approach is applied to a case study involving cell phone remanufacturing.     

An investigation on the fuel savings potential of hybrid hydraulic refuse collection vehicles

Refuse trucks play an important role in the waste collection process. Due to their typical driving cycle, these vehicles are characterized by large fuel consumption, which strongly affects the overall waste disposal costs. Hybrid hydraulic refuse vehicles offer an interesting alternative to conventional diesel trucks, because they are able to recuperate, store and reuse braking energy. However, the expected fuel savings can vary strongly depending on the driving cycle and the operational mode. Therefore, in order to assess the possible fuel savings, a typical driving cycle was measured in a conventional vehicle run by the waste authority of the City of Stuttgart, and a dynamical model of the considered vehicle was built up. Based on the measured driving cycle and the vehicle model including the hybrid powertrain components, simulations for both the conventional and the hybrid vehicle were performed. Fuel consumption results that indicate savings of about 20% are presented and analyzed in order to evaluate the benefit of hybrid hydraulic vehicles used for refuse collection.     

微气泡臭氧催化氧化-生化耦合工艺深度处理煤化工废水

采用微气泡臭氧催化氧化-生化耦合工艺对煤化工废水生化出水进行深度处理,考察耦合系统处理性能及不同臭氧投加量和进水COD量比值的影响.结果表明,微气泡臭氧催化氧化处理能够有效降解废水中难降解含氮芳香族污染物,去除部分COD并释放氨氮,显著提高废水可生化性,臭氧利用率接近100%,无需进行臭氧尾气处理;同时为生化处理提供充足溶解氧(DO),实现生化处理对COD和氨氮的进一步有效去除,生化处理无需曝气.在系统出水回流比为30%、臭氧投加量和进水COD量之比为0.44 mg·mg~(-1)的运行条件下,耦合系统处理性能较好.微气泡臭氧催化氧化处理对COD去除率为42.5%,臭氧消耗量与COD去除量比值为1.38 mg·mg~(-1),臭氧利用率为98.0%;生化处理对COD去除率为42.3%;耦合系统整体COD去除率为66.7%,最终平均出水COD浓度为91.5 mg·L~(-1),估算整体臭氧消耗量与COD去除量比值为0.68 mg·mg~(-1),具有较优的技术经济性能.     

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

煤制烯烃废水处理与回用技术解析

针对煤制烯烃项目废水的来源及水质特点,从生化处理技术与回用处理技术方面阐述了煤制烯烃废水处理现状及存在问题,展望了煤制烯烃废水处理与回用技术未来发展方向,指出了新型脱氮工艺、膜集成工艺及分质结晶技术在煤制烯烃废水处理中的可行性,为煤化工废水处理与资源化利用提供理论参考。     

基于遗传神经网络的除湿机故障诊断与寿命预测

目的识别除湿机的性能状态和预测吸附剂的剩余寿命。方法针对除湿机故障过程缓变的特点,提出一种基于数据驱动的遗传神经网络模型。首先,为解决设备失效程度划分模糊的问题,由5个热力参数组成反映吸附剂劣化程度的特征向量,关联分析得到除湿机的5类故障模式。其次,利用遗传神经网络建立状态参数和故障模式的映射关系。最后,对表征设备吸附能力的主参数进行外推预测。结果训练好的诊断网络可准确地识别出设备的劣化程度及其演变过程,预测网络的预测精度非常高。结论该方法可有效地实现对除湿机的故障诊断与预测。。