涡电流分选机理及应用

介绍了涡电流分选的物理原理,分析了导体所受的成分力.描述了涡电流分选装置的结构以及涡电流分选的应用领域.研究表明:涡电流分选机具有结构简单、质量轻、斥力强(可调节)、对物料的适应性强、分选效率高以及处理量大等优点,可在环境保护领域,特别是在有色金属再生行业推广使用.     

浅析机动车综合整治对南昌市环境质量的影响

通过对南昌市实施机动车综合整治--禁鸣喇叭、安装尾气净化装置前后环境质量，分析了机动车综合整治对南昌市环境质量的影响，并提出相应的对策和建议。     

电动转向系统助力性能研究

汽车电动转向系统的助力性能直接关系到汽车转向操作的安全 ,笔者以电动转向系统的跟踪性能和对扭矩传感器测量噪声及路面干扰的抑制为控制系统设计的目标 ,将H∞ 控制理论应用于控制系统的设计 ,采用LMI处理方法设计了控制器。计算机仿真结果证实 ,所设计的电动转向系统具有良好的跟踪性能 ,并有效地抑制了扭矩传感器测量噪声和路面激励干扰的影响 ,仿真结果为电动转向系统的设计提供了依据     

重型柴油车对空气质量的影响及其排放的控制

通过对柴油车污染物排放的特征和机动车排放清单的分析,探讨了重型柴油车对我国城市空气质量的影响及其排放的控制.重型柴油车排放大量的氮氧化物和颗粒物,其中氮氧化物为大气中产生二次细粒子以及臭氧的重要前体物之一,导致区域性灰霾的形成,而柴油颗粒物是影响健康的一个主要有毒空气污染物,尤其是其中粒径为30～100 nm的超细粒子...     

考虑区域特点和车型差异的氢燃料电池汽车全生命周期减碳预测分析

发展氢燃料电池汽车是我国实现“双碳”战略的重要路径之一,目前我国多个区域正在推广应用包括乘用车、客车以及重卡在内的氢燃料电池汽车,如何量化研究未来不同车型和不同区域的氢燃料电池汽车减碳潜力成为如今的研究热点之一.基于全生命周期的评价方法,考虑了未来的汽车燃油经济性、电力碳排放因子、氢能碳排放因子和氢燃料电池汽车推广规模及制氢方式的区域差异,量化评价了不同类型的氢燃料电池汽车（FCV）、传统燃油汽车（ICEV）和纯电动汽车（BEV）的全生命周期碳排放量（以CO₂当量计）,对比分析了氢燃料电池汽车在不同时间及不同区域的减碳潜力,并对百公里氢耗量进行了不确定性分析.结果发现,到2025年氢燃料电池客车的全生命周期碳排放比传统燃油客车降低36.0%,而氢燃料电池重卡相较于传统燃油重卡并没有减碳效益.随着未来我国氢能来源结构的不断优化,到2035年氢燃料电池重卡的全生命周期碳排放比传统燃油重卡降低36.5%,相较于乘用车和客车两种车型,其减碳效益是最明显的.以2035年京津冀示范群为例,随着百公里氢耗量降低20%,FCV乘用车、客车和重卡的减碳规模分别增加了7.29%、9.93%和19.57%.因此建议氢燃料电池汽车推广应短期以客车为主,长期以重卡为主,乘用车推广作为补充.分区域和分阶段推广氢燃料电池汽车更有助于推进我国汽车领域的低碳化进程.     

Child passenger restraint use and emergency department--reported injuries: a special study using the National Electronic Injury Surveillance System-All Injury Program, 2004

INTRODUCTION: In 2004, more than 180,000 child passengers aged 相似文献   

Two-stage vertex analysis method for planning electric power systems with greenhouse gas abatement consideration

This study presents a two-stage vertex analysis (TSVA) method for the planning of electric power systems (EPS) under uncertainty. TSVA has advantages in comparison to other optimization techniques. Firstly, TSVA can incorporate greenhouse gas (GHG) abatement policies directly into its optimization process, and, secondly, it can readily integrate inherent system uncertainties expressed as fuzzy sets and probability distributions directly into its modeling formulation and solution procedure. The TSVA method is applied to a case study of planning EPS and it is demonstrated how the TSVA efficiently identify optimal electricity-generation schemes that could help to minimize system cost under different GHG-abatement considerations. Different combinative considerations on the uncertain inputs lead to varied system costs and GHG emissions. Results reveal that the total electricity supply will rise up along with the time period due to the increasing demand and, at the same time, more non-fossil fuels should be used to satisfy the increasing requirement for GHG mitigation. Moreover, uncertainties in connection with complexities in terms of information quality (e.g., capacity, efficiency, and demand) result in changed electricity-generation patterns, GHG-abatement amounts, as well as system costs. Minimax regret (MMR) analysis technique is employed to identify desired alternative that reflects compromises between system cost and system-failure risk.     

石墨炉原子吸收光谱法测定农产品中痕量铍

采用石墨炉原子吸收光谱法测定农产品中痕量铍,比较了微波消解和电热板消解两种前处理方法,选择了基体改良剂。方法在0μg／L—4.00μg／L范围内线性良好,微波消解法和电热板消解法的检出限分别为0.002mg／kg和0.0002mg／kg,标样平行测定的RSD为2.4％—4.1％,农产品加标回收率为80.0％—95.0％。     

基于故障物理的集成控制器电路板可靠性预计

目的实现商用电动汽车集成控制器的可靠性预计与提升,采用应力仿真与故障物理相结合的方法对其关键电路板进行可靠性预计。方法针对集成控制器的数字样机,开展热、振动仿真应力分析,采用故障模式机理及影响分析(FMMEA)方法,分析电路板可能存在的故障模式和故障机理,确定潜在故障模式的故障物理模型。将应力分析结果作为故障物理模型的输入,进行基于故障物理的可靠性预计,寻找设计薄弱环节,并提出改进措施。结果找到了电路板的8个高温器件和热集中区域,振动仿真分析表明,电路板顶端与中心振动强度较大,可能引起疲劳失效,需要给予关注。通过FMMEA分析,得到电路板的主要故障模式为焊点开裂,主要受温度循环影响,造成热疲劳失效。最后采用Coffin-Mason模型,计算得到电路板的平均故障间隔时间为15869 h,找出了电路板的可靠性设计的薄弱环节。结论该方法基于故障物理,相对传统基于手册的可靠性预计方法精度更高,同时能够在产品研制阶段与性能设计并行,通过分析和改进产品设计,达到正向可靠性设计的目的,为新能源汽车领域电子产品的可靠性预计提供新的思路。     

State-level seat belt use in the United States, 2011–2016: Comparison of self-reported with observed use and use by fatally injured occupants

Introduction: Despite 49 states and the District of Columbia having seat belt laws that permit either primary or secondary enforcement, nearly half of persons who die in passenger vehicle crashes in the United States are unbelted. Monitoring seat belt use is important for measuring the effectiveness of strategies to increase belt use. Objective: Document self-reported seat belt use by state seat belt enforcement type and compare 2016 self-reported belt use with observed use and use among passenger vehicle occupant (PVO) fatalities. Methods: We analyzed the Behavioral Risk Factor Surveillance System (BRFSS) self-reported seat belt use data during 2011–2016. The Pearson correlation coefficient (r) was used to compare the 2016 BRFSS state estimates with observed seat belt use from state-based surveys and with unrestrained PVO fatalities from the Fatality Analysis Reporting System. Results: During 2011–2016, national self-reported seat belt use ranged from 86–88%. In 2016, national self-reported use (87%) lagged observed use (90%) by 3 percentage points. By state, the 2016 self-reported use ranged from 64% in South Dakota to 93% in California, Hawaii, and Oregon. Seat belt use averaged 7 percentage points higher in primary enforcement states (89%) than in secondary states (82%). Self-reported state estimates were strongly positively correlated with state observational estimates (r = 0.80) and strongly negatively correlated with the proportion of unrestrained PVO fatalities (r = −0.77). Conclusion: National self-reported seat belt use remained essentially stable during 2011–2016 at around 87%, but large variations existed across states. Practical Applications: If seat belt use in secondary enforcement states matched use in primary enforcement states for 2016, an additional 3.98 million adults would have been belted. Renewed attention to increasing seat belt use will be needed to reduce motor-vehicle fatalities. Self-reported and observational seat belt data complement one another and can aid in designing targeted and multifaceted interventions.