Effects of EGR on performance and emissions of a diesel engine fuelled with balanites aegyptiaca/diesel blends

In this study, balanites Aegyptiaca (L.) Del biodiesel was blended in proportions of 10% and 20% on the volume basis with diesel fuel and tested in a single cylinder, VCR diesel engine under measured load conditions with varied EGR rates (0, 10 and 20%). The results showed that B10 and B20 blends shown a significant reduction rate in terms of NO_x emissions that were familiar with biodiesel blends. At peak load conditions, BTE increased slightly for test fuel blends compared with pure diesel fuel while the BSFC rate and EGT suffered from increasing and decreasing nature with respect to blending percentage. From the emissions point of view, with the increase in blends percentage, a significant reduction rate is observed in terms of CO and HC concentrations (up to 12.34 and 17.5%, respectively) while NOx emissions decreased at peak load conditions (up to 24.34%). HC and CO emissions decreased with increase in blends percentage. However, lower levels of NO_x and EGT (up to 21.37 and 8.47%, respectively) and the average increase in terms of BTE and BSFC (up to 2.83 and 2.9%, respectively) can be realised with B20 test fuel blend under 20% EGR rate.     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.     

生理因素对驾驶人行为及风险感知影响研究综述

为全面认识驾驶人行为及风险感知并分析行为成因，从驾驶人生理因素着手，从驾驶人视力、阻塞性睡眠呼吸暂停综合征和肌肉骨骼疾患3个方面梳理国内外驾驶人行为及风险感知的研究成果与研究不足。研究结果表明:驾驶人的生理疾病对其驾驶能力和危险感知存在显著影响;生理疾病严重程度与异常驾驶行为中的一般性失误、危险性失误行为之间具有显著正相关关系，疾病严重程度越高，出行失误行为的频率越高；之后可从理论和实验两方面着手，针对驾驶人的不同属性进行研究。     

Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.     

Metabolic uncoupler, 3,3′,4′,5-tetrachlorosalicylanilide addition for sludge reduction and fouling control in a gravity-driven membrane bioreactor

• Effects of metabolic uncoupler TCS on the performances of GDMBR were evaluated. • Sludge EPS reduced and transformed into dissolved SMP when TCS was added. • Appropriate TCS increased the permeability and reduced cake layer fouling. • High dosage aggravated fouling due to compact cake layer with low bio-activity. The gravity-driven membrane bioreactor (MBR)system is promising for decentralized sewage treatment because of its low energy consumption and maintenance requirements. However, the growing sludge not only increases membrane fouling, but also augments operational complexities (sludge discharge). We added the metabolic uncoupler 3,3′,4′,5-tetrachlorosalicylanilide (TCS) to the system to deal with the mentioned issues. Based on the results, TCS addition effectively decreased sludge ATP and sludge yield (reduced by 50%). Extracellular polymeric substances (EPS; proteins and polysaccharides) decreased with the addition of TCS and were transformed into dissolved soluble microbial products (SMPs) in the bulk solution, leading to the break of sludge flocs into small fragments. Permeability was increased by more than two times, reaching 60–70 L/m²/h bar when 10–30 mg/L TCS were added, because of the reduced suspended sludge and the formation of a thin cake layer with low EPS levels. Resistance analyses confirmed that appropriate dosages of TCS primarily decreased the cake layer and hydraulically reversible resistances. Permeability decreased at high dosage (50 mg/L) due to the release of excess sludge fragments and SMP into the supernatant, with a thin but more compact fouling layer with low bioactivity developing on the membrane surface, causing higher cake layer and pore blocking resistances. Our study provides a fundamental understanding of how a metabolic uncoupler affects the sludge and bio-fouling layers at different dosages, with practical relevance for in situ sludge reduction and membrane fouling alleviation in MBR systems.     

基于3S技术对太湖底质及水质总磷的研究

应用3S技术研究了太湖底质与水质总磷(TP)的分布情况,并结合水华频次分析了其相关性。结果表明:2016—2018年,太湖底质TP年均值在433~537 mg/kg波动,水质TP年均值从0.064 mg/L上升至0.087 mg/L。从空间分布来看,底质TP、水质TP和水华频次均呈现“西高东低”的规律,太湖西部区尤其是竺山湖区是需要开展治理的重点区域。3年间,太湖西部区水质TP上升,而底质TP与入湖河流TP下降,说明内源磷污染是太湖西部区水质TP升高的主要原因,须加强科学清淤。     

基于等级全息建模的输油泵机组风险根源辨识*

为“挖掘”输油泵机组风险根源，降低设备预知性维护难度，结合输油泵多准则风险评价，提出1种基于等级全息建模的输油泵机组风险根源辨识方法，运用等级全息建模方法将输油泵系统分解为泵体结构、管理因素、环境因素、操作因素、技术因素、运行因素、设备安装7个子系统进行定性和定量分析。结果表明:相比危险与可操作性分析（HAZOP）、事故树分析（FTA）等传统风险辨识方法，等级全息建模（HHM）对轴承等关键部件以及压力等运行参数的监测更为深入，能够有效辨识输油泵机组高风险情景，提升输油泵的风险辨识效率。     

煤矿水害风险量化评价方法

为提高煤矿防治水管理水平，预防和消除矿井水害，在层次分析法的基础上建立中性值作为参照对象对矿井水害风险进行实时评判的方法。根据《煤矿防治水细则》建立以矿井水文地质类型、矿井涌水量标准分数、突水预兆、采掘面位置、探水结果为准则层的层次结构模型，并对各评价指标赋权。依据制定的水害风险评价指标的评分细则和监测监控数据并结合其权重得到水害评价总得分。通过总得分与中性参照分数比较得出预测结果:水害评价总得分大于中性参照分数，证明水害的威胁小，分数越高越安全；反之则水害的威胁较大，分数越低越危险，这时需要加强防治水的力度，令评价分数管控大于中性参照分数。这种方法依赖于井下监测监控数据进行量化评价，能实时、客观、全面且准确地反映煤矿水害的风险情况。     

中国南海高温高压井钻完井损失工时事件统计分析

为研究我国南海高温高压井钻完井、测试损失工时事件规律，对2009—2018年中国南海高温高压探井钻井日志进行分析，汇总501起海上高温高压井钻完井损失工时事件，并将其划分为复杂情况及事故停工、自然停工、修理停工3大类进行研究。结果表明:复杂情况及事故停工事件数与年份无明显关联，但与地质资料准确度关系密切，修理停工事件数随年份呈现震荡下降趋势；复杂情况及事故停工总损失工时最多，其中卡钻损失工时占比最高；修理停工总损失工时最少，其中钻井设备故障损失工时占比最高；灾难天气、洋流或地质活动是造成损失工时最多的原因，不安全行为是单起事件平均损失工时最多的原因，设备老化是修理停工最主要原因。研究结果可为后续高温高压井钻完井非生产时间成本估计模型提供数据基础。     

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。