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排序方式: 共有597条查询结果,搜索用时 15 毫秒
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Ahmed I. El-Seesy Mohamed Nour Ali M. A. Attia Hamdy Hassan 《International Journal of Green Energy》2020,17(3):233-253
ABSTRACTThis article aims to study the influence of the addition of graphene oxide nanoparticles (GO) to diesel/higher alcohols blends on the combustion, emission, and exergy parameters of a CI engine under various engine loads. The higher alcohols mainly n-butanol, n-heptanol, and n-octanol are blended with diesel at a volume fraction of 50%. Then, the 25 and 50 mg/L concentrations of GO are dispersed into diesel/higher alcohols blends using an ultrasonicator. The GO structures are examined using TEM, TGA, XRD and FTIR. The findings show that there is a reduction in pmax. and HRR when adding higher alcohols with diesel fuel. Regarding engine emission, there is a significant improvement in emissions formation with adding higher alcohols. The addition of GO into diesel/higher alcohols blends improves the brake thermal efficiency by 15%. Moreover, the pmax. and HRR are both enhanced by 4%. The CO, UHC and smoke formation are reduced considerably by 40%, 50 and 20%, respectively, while NOx level is increased by 30% with adding GO. Finally, adding high percentages of n-butanol, n-heptanol, and n-octanol with diesel fuel with the presence of GO has the potential to achieve ultra-low CO, UHC, and smoke formation meanwhile keeping high thermal efficiency level. 相似文献
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遗传算法是近年来迅速发展起来的一种全新的随机搜索与优化算法,但由于其自身固有的缺陷,通常优化过程的收敛速度较慢,局部搜索能力不足,而且算法稳定性较差。而蚁群算法广泛应用在旅行商问题计算中,目前是较好的求解最短路由问题的算法之一。就其自身来说有很多优点,如正反馈性、鲁棒性和智能性,但是在寻优过程中容易陷入局部最佳的缺点。针对上述情况,将遗产算法与蚁群算法相结合,用于实际交通系统寻找最优路径的问题中,并定义了目标函数,以路径可靠性和路径长度为优化目标,寻找最合适的救灾路线。最后通过实际计算结果的对比验证,说明了该方法的有效性。 相似文献
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综述了车辆事故紧急呼救技术的原理,从车辆事故检测识别技术、移动车辆定位技术、无线通信技术和地理信息系统几方面概述车辆事故紧急呼救技术的研究内容。进一步介绍车辆事故紧急呼救技术的国内外研究和应用现状,并从车辆事故识别技术、地图匹配及组合导航、集群通信及通信网络几方面总结并指出车辆事故紧急呼救技术的关键技术和难点。展望了车辆事故紧急呼救技术的发展趋势,并就我国发展车辆事故呼救技术的可行性和发展方向进行探讨。 相似文献
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以武汉市某住宅的智能化系统设计为实例,从需求分析、投资额度、系统选择、设备配置等方面对楼宇对讲系统、视频监控系统、机房工程、电子围栏系统、弱电管网等进行了论述,并就施工中出现的问题进行了说明,以期为类似工程项目提供参考。 相似文献
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为构建更加符合驾驶员认知特性的出行信息环境,提高驾驶员出行信息服务水平,对ATIS环境下驾驶员认知负荷研究进展进行系统分析与评述.首先阐述了认知负荷的理论基础,随后分析了ATIS环境下驾驶员认知负荷的影响因素,同时分类解析了驾驶员内在认知负荷、外在认知负荷与相关认知负荷的产生根源,并对认知负荷的形成机理进行了分析;系统评述了驾驶员认知负荷的测量方法,最后基于驾驶员信息认知负荷提出了ATIS优化对策.结果表明:年龄、性别、受教育程度、月收入、出行经验是影响驾驶员认知负荷的主要因素;道路交通标志的版面设计与驾驶员的标志视认时间关联密切;驾驶过程中拨打手机及使用车载终端均会分散驾驶员注意力,增加驾驶员的信息认知负荷;较高的车速与音频播放等环境会对驾驶员的信息认知能力提出更高要求. 相似文献
59.
为了满足国际海事组织对船舶CO2排放的要求,建立了一种针对船舶尾气CO2的循环吸收系统,利用NaOH溶液吸收CO2.NaOH溶液完成第一步吸收反应后在第二步反应中被还原,从而可以循环利用.分析了初始反应温度、NaOH浓度及溶液中的Na2CO3对CO2吸收率的影响,并计算了循环反应中NaOH的再生率和CaO的过量系数.结果表明,CaO过量系数为1.2时对CO2固化效果最佳,此时NaOH溶液再生率达79.31%.研究表明,NaOH溶液吸收船舶尾气中CO2的循环系统效率高、成本低. 相似文献
60.
Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty. 相似文献