履带车辆平台模拟试验谱的建立方法研究与应用

目的建立模拟试验谱推导方法,合理确定车载仪器设备模拟振动试验条件。方法针对履带车辆平台诱发环境实测振动数据,通过履带车辆实测振动谱环境特征分析,提出宽带随机振动背景谱叠加窄带分量作为模拟试验谱的基本谱形,并探讨相应试验量级和试验时间的推导方法。结果建立了由实测振动数据推导模拟试验谱的方法。结论模拟试验谱推导方法实用性强,依据此方法由某履带车辆实测数据得到了相应的模拟试验谱。     

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics

Objective: Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity.

Methods: The NASS-CDS 2000–2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0–4, 5–9, 10–14, and 15–18 years. Next, the National Trauma Databank 2002–2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MR_MAIS) for each injury within 6 age groups: 0–4, 5–9, 10–14, 15–18, 0–18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated.

Results: MR and MR_MAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MR_MAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MR_MAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MR_MAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.

Conclusions: Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.     

Age- and Sex-Specific Thorax Finite Element Model Development and Simulation

Objective: The shape, size, bone density, and cortical thickness of the thoracic skeleton vary significantly with age and sex, which can affect the injury tolerance, especially in at-risk populations such as the elderly. Computational modeling has emerged as a powerful and versatile tool to assess injury risk. However, current computational models only represent certain ages and sexes in the population. The purpose of this study was to morph an existing finite element (FE) model of the thorax to depict thorax morphology for males and females of ages 30 and 70 years old (YO) and to investigate the effect on injury risk.

Methods: Age- and sex-specific FE models were developed using thin-plate spline interpolation. In order to execute the thin-plate spline interpolation, homologous landmarks on the reference, target, and FE model are required. An image segmentation and registration algorithm was used to collect homologous rib and sternum landmark data from males and females aged 0–100 years. The Generalized Procrustes Analysis was applied to the homologous landmark data to quantify age- and sex-specific isolated shape changes in the thorax. The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant model was morphed to create age- and sex-specific thoracic shape change models (scaled to a 50th percentile male size). To evaluate the thoracic response, 2 loading cases (frontal hub impact and lateral impact) were simulated to assess the importance of geometric and material property changes with age and sex.

Results: Due to the geometric and material property changes with age and sex, there were observed differences in the response of the thorax in both the frontal and lateral impacts. Material property changes alone had little to no effect on the maximum thoracic force or the maximum percent compression. With age, the thorax becomes stiffer due to superior rotation of the ribs, which can result in increased bone strain that can increase the risk of fracture. For the 70-YO models, the simulations predicted a higher number of rib fractures in comparison to the 30-YO models. The male models experienced more superior rotation of the ribs in comparison to the female models, which resulted in a higher number of rib fractures for the males.

Conclusion: In this study, age- and sex-specific thoracic models were developed and the biomechanical response was studied using frontal and lateral impact simulations. The development of these age- and sex-specific FE models of the thorax will lead to an improved understanding of the complex relationship between thoracic geometry, age, sex, and injury risk.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

超声辅助法制备新型FeMOR分子筛催化NOx还原反应性能研究

采用超声辅助浸渍法成功合成了高铁含量的Fe MOR-5%-UL催化剂,并且测试其催化还原NO性能.研究发现在超声辅助条件下浸渍制得的催化剂可以引入更高比例的离子交换位上的孤立的Fe~(3+),这些铁离子具有更强的NO还原活性,因此超声辅助浸渍法制备的催化剂催化性能显著高于传统的离子交换法和浸渍法.其中活性最高的FeMOR-5%-UL催化剂在添加SO_2等多种气氛时,催化活性下降不显著.并且在持续100 h的汽车尾气条件下进行的稳定性实验中,FeMOR-5%-UL的催化活性没有明显下降.FeMOR-5%-UL的优异的催化活性和稳定性非常具有应用前景和研究价值.     

地面无人平台电磁兼容及防护技术研究

阐述了地面无人平台电磁兼容性的一些关键问题,介绍了地面无人平台的分类及关键能力。根据系统组成和应用场景,分类研究了各类设备所处的内外电磁环境,剖析了其面临的电磁兼容隐患。最后,从总体设计、频谱规划、测试验证三个方面,给出了针对地面无人平台电磁兼容工作的具体建议。     

一体化的机动车污染防治监管信息系统建设与应用研究

随着机动车保有量的增加,机动车排放已成为大中城市大气污染的主要来源.福建省机动车污染防治监管信息系统,提出了一体化设计的承载网络、逻辑架构、主要功能,加强了机动车污染排放监管力度.通过省级、市级、县级环保部门和检测站四级集中建设和统一部署,节约了投资,实现了数据的完整性、一致性和高度集中,确保了数据与环境保护部的交换和共享.根据两年的运行成果,探讨了进一步发展的方向.     

轻型汽油车排放颗粒物数浓度和粒径分布特征

我国机动车颗粒物排放研究多集中于重型柴油车,对于轻型汽油车的研究相对较少.本研究对3辆缸内直喷(GDI)汽车和1辆进气道喷射(PFI)汽车排放颗粒物的数浓度与粒径分布进行测试,并利用两台不同检测下限的颗粒物冷凝生长计数器(CPC)对轻型汽油车颗粒物实际排放水平进行了探究.结果表明,GDI汽车排放的颗粒物数浓度高于PFI汽车一个数量级,冷启动下颗粒物主要在测试循环前200 s大量产生,GDI汽车排放颗粒物数浓度与工况速度变化关系密切,而PFI汽车变化相对较小.GDI与PFI汽车排放的颗粒物粒径分布均具有核模态和积聚模态两个特征峰,核模态颗粒物峰值粒径约为20~27 nm,积聚模态约为80~95 nm.粒径检测下限为2.5 nm的UCPC测得的颗粒物数浓度比法规使用的粒径测量下限为23 nm的CPC测量结果分别高出35.0%(GDI)和50.4%(PFI).表明喷油技术是影响颗粒物数量排放水平的关键因素,法规测试会低估轻型汽油车实际颗粒物排放水平.     

Vehicle-Induced Lead and Cadmium Contamination of Roadside Soil and Plants in Italy

Lead and cadmium concentrations in spontaneous vegetation and in soil sampled at various distances (0–208 m) from several motorways throughout Italy were measured. Lead and cadmium concentrations appear to be correlated to distance from the motorway and to traffic levels. A comparison with data from a remote and unpolluted site shows that foliar lead concentrations can be up to 40 times higher, and foliar cadmium concentrations up to 3 times higher. Plants behave differently in their accumulation of lead and cadmium; conifers present the highest levels. Also the various receptors and compartments of the roadside ecosystem differ in their accumulation of lead and cadmium; soil and bark have consistently higher concentrations, while the leaves and twigs of trees have consistently lower levels. the data recorded by ad hoc introduced bio-accumulating plants (Lolium multiflorum L.) are consistent with those of the spontaneous vegetation. the concentrations of both lead and cadmium in Lolium vary from June to November, following in part the fluctuation in traffic density.