Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

乘性O-U噪声驱动下基因选择模型的定态性质

从乘性O—U噪声驱动下的基因选择模型出发,讨论了O—U噪声参数对模型定态性质的影响。数值计算结果表明O-U噪声的噪声强度比噪声关联时间对基因单倍体定态几率分布有更大影响,噪声的有色性有利于分离不同基因的单倍体。     

船舶主动式减摇鳍的分布定位设计

船舶减摇鳍的使用工况包括航行状态和零航速状态,当船舶在航行过程中,减摇鳍与流体发生相互运动,在减摇鳍表面产生抗倾覆力矩,保证船舶的航行稳定性;当船舶处于零航速状态下,由于海浪、海风等干扰力矩的作用,同样会使船舶发生横摇、纵倾等运动,因此也必须进行减摇控制,此时船舶的减摇是利用机械结构使减摇鳍运动,产生抗倾覆力矩。本文针对船舶横摇和减摇鳍的流体动力学特性进行系统的建模,分别从主动式减摇鳍的翼型、形状、分布定位等内容进行展开,有助于提升现有船舶减摇鳍的设计水平。     

汽车侧翻和滚翻事故建模研究

分析汽车在侧翻和滚翻过程中的受力状态和轮胎或车身与路面的相互作用方式,建立汽车侧翻和滚翻的运动学和动力学模型,揭示汽车临界侧翻碰撞力与持续作用时间等参数的关系,推导侧翻车辆侧向速度的范围,确定滚筒模型中关键参数的选取方法。事故案例表明模型在实际应用中效果良好、定量准确、直观性强。     

典型DHT拓扑结构的研究

从代数角度研究了主要的DHT（分布式哈希表）拓扑结构,为方便、深入地理解DHT拓扑结构,运用群论和图论的方法重点对其拓扑结构的数学性质作了详细的分析,这些数学性质在改进现有拓扑结构或设计新的拓扑结构时有很大的应用价值．     

基于PMS理论的常规潜艇任务可靠性研究

针对常规潜艇功能复杂、任务多变的特点,将多阶段任务系统(phased mission system,PMS)理论引入到其任务可靠性的分析中.深入分析常规潜艇的鱼雷攻击任务,建立任务可靠性模型,用马尔可夫过程法进行了任务可靠度计算,为常规潜艇任务可靠性模型的建立提供一种新方法.     

港口集装箱码头的盈亏平衡分析

盈亏平衡分析又被称为本量利分析,即“成本一业务量（生产量或销售量）一利润分析法（cost—volumeprofit analysis）”,它是在变动成本法的基础上,以数量化的会计模型来揭示固定成本、变动成本、销售量、销售单价、销售收入和利润等变量之间的内在规律性联系,为会计预测和决策提供必要财务信息的一种技术方法。集装箱码头运用盈亏平衡分析,是以集装箱吞吐箱量为基本业务量,通过对各项单箱指标的研究,寻找作业箱量与主营收入、成本控制和利润实现之间的关系,为集装箱码头提高管理水平、改善经营方式提供财务分析上的支持。     

基于前置信号的单交叉口多相位模糊控制

在城市道路网络中,交通拥挤或阻塞往往发生在道路交叉口处,应用进口道渠化优化设置与模糊控制相互协调的方法控制信号交叉口,能够有效地利用城市交叉口空间与时间资源,并提高信号交叉口的通行能力.     

与交通标志信息有关的驾驶人短时记忆衰减研究

研究驾驶人交通标志信息记忆量随时间的变化规律,能够为城市道路交通标志设计及实施应用提供有力支撑。在分析短时记忆时间规律、交通标志信息传输及度量的基础上,以一条有交通信息标志的实验路段为例,采用实验车调查法,结合心理学记忆理论,分析交通标志信息量对驾驶人短时记忆的影响,探究交通标志信息记忆量随时间变化的规律。结果表明,驾驶人对交通标志信息的短时记忆衰减规律符合艾定浩斯遗忘曲线。     

钢-铝石墨半固态铸轧复合的数值模拟

铸轧区的温度分布直接影响着铸轧过程的稳定性和复合板材的质量.针对实验室复合板半固态铸轧试验的特点建立了数学模型,采用有限元法对钢-铝石墨半固态铸轧复合过程的热流耦合问题进行了数值模拟计算,分析了不同浇注温度和铸轧速度下熔池内温度场变化的情况.模拟结果表明,当浇注温度为620℃,铸轧速度在0.6～0.8 m/min的范围内可保证铸轧稳定进行,此结论与试验数据相吻合.该模型可以有效预测凝固前沿位置,为半固态铸轧复合工艺的进一步研究和钢-铝石墨复合板的数字化生产提供了依据.