Florida has the highest number of motorcycle fatalities in the United States and contains the second largest population of registered motorcycles. The COVID-19 pandemic influenced the roads, traffic, and driving behav...Florida has the highest number of motorcycle fatalities in the United States and contains the second largest population of registered motorcycles. The COVID-19 pandemic influenced the roads, traffic, and driving behavior in the continental United States. Motorcycle crashes decreased during the COVID-19 years (2020 and 2021) while the fatality rates increased. The purpose of this study is to 1) investigate motorcycle crashes before and during the Pandemic period to understand the impacts on motorcycle safety and contributing factors to the crash severity levels;2) develop the crash predictive model for different degrees of severity in motorcycle crashes in Florida. Florida statewide crash data were collected. T tests have been conducted to compare the contributing factors between two periods. The injury severities are significantly different among all five levels between those during normal period and the Pandemic period. A crash predictive model has been developed to determine the facts to injury severity levels for motorcycle crashes. A total of eight variables are found to significantly increase the injury severity levels for motorcycle crashes during the Pandemic period.展开更多
新能源汽车转向驱动桥半轴采用空心设计,与燃油汽车的结构形式有很大区别,针对电动汽车转向驱动桥空心半轴的最大等效应力与设计变量呈隐式复杂非线性关系的可靠度分析难题,文中通过将Kriging模型与蒙特卡洛(Monte Carlo Simulation,MCS...新能源汽车转向驱动桥半轴采用空心设计,与燃油汽车的结构形式有很大区别,针对电动汽车转向驱动桥空心半轴的最大等效应力与设计变量呈隐式复杂非线性关系的可靠度分析难题,文中通过将Kriging模型与蒙特卡洛(Monte Carlo Simulation,MCS)法相结合,提出了基于AK-MCS(Active Learning Kriging-Monte Carlo Simulation)法的新能源电动汽车转向驱动桥空心半轴可靠度分析方法。首先,采用Kriging代理模型构建新能源电动汽车转向驱动桥空心半轴的最大等效应力的初始代理模型;其次,通过Kriging提供的学习函数和收敛准则逐步增加样本点,从而对初始最大等效应力的Kriging模型进行更新;最后,对更新后的Kriging代理模型计算新能源电动汽车转向驱动桥空心半轴的可靠度。结果表明:与MCS方法相比,基于AK-MCS方法的可靠度分析在时间上缩短2000余倍;与Kriging+MCS方法相比,基于AK-MCS方法的可靠度分析误差减小了50%。由此验证了基于AK-MCS方法空心半轴可靠度分析的高效性和准确性,为电动汽车转向驱动桥空心半轴可靠性的研究提供了理论依据,具有一定的工程意义。展开更多
增益(Gain)校正有助于消除MC-ICP-MS不同高阻放大器之间的阻值差异,进而提高同位素分析的精度和准确度,但有关Gain的偏移和校正频率对同位素测试的影响和作用原理还缺乏系统认识。本研究结合本实验室Neptune Plus MC-ICP-MS的Gain校正数...增益(Gain)校正有助于消除MC-ICP-MS不同高阻放大器之间的阻值差异,进而提高同位素分析的精度和准确度,但有关Gain的偏移和校正频率对同位素测试的影响和作用原理还缺乏系统认识。本研究结合本实验室Neptune Plus MC-ICP-MS的Gain校正数据,以实际测试的汞同位素数据为例,评估了放大器Gain校正系数偏移对同位素测试的影响。结果显示,当测试标样和样品的校正系数偏移幅度一致时,汞同位素测试结果基本无变化;当偏移幅度存在明显差异且单一放大器校正系数的相对偏移幅度超过–0.070‰~0.058‰时,汞同位素的测试结果大于分析误差。Gain校正系数单日的相对变化幅度(–0.028‰~0.028‰)可保证汞同位素测试结果小于分析误差,但长期的偏移却会导致汞同位素变化远超分析误差。此外,仪器的硬件、温度和真空度等也是Gain校正系数变化的重要影响因素,因此建议定期维护仪器,并每日进行Gain校正,以保证测试结果的稳定和准确。展开更多
文摘Florida has the highest number of motorcycle fatalities in the United States and contains the second largest population of registered motorcycles. The COVID-19 pandemic influenced the roads, traffic, and driving behavior in the continental United States. Motorcycle crashes decreased during the COVID-19 years (2020 and 2021) while the fatality rates increased. The purpose of this study is to 1) investigate motorcycle crashes before and during the Pandemic period to understand the impacts on motorcycle safety and contributing factors to the crash severity levels;2) develop the crash predictive model for different degrees of severity in motorcycle crashes in Florida. Florida statewide crash data were collected. T tests have been conducted to compare the contributing factors between two periods. The injury severities are significantly different among all five levels between those during normal period and the Pandemic period. A crash predictive model has been developed to determine the facts to injury severity levels for motorcycle crashes. A total of eight variables are found to significantly increase the injury severity levels for motorcycle crashes during the Pandemic period.
文摘新能源汽车转向驱动桥半轴采用空心设计,与燃油汽车的结构形式有很大区别,针对电动汽车转向驱动桥空心半轴的最大等效应力与设计变量呈隐式复杂非线性关系的可靠度分析难题,文中通过将Kriging模型与蒙特卡洛(Monte Carlo Simulation,MCS)法相结合,提出了基于AK-MCS(Active Learning Kriging-Monte Carlo Simulation)法的新能源电动汽车转向驱动桥空心半轴可靠度分析方法。首先,采用Kriging代理模型构建新能源电动汽车转向驱动桥空心半轴的最大等效应力的初始代理模型;其次,通过Kriging提供的学习函数和收敛准则逐步增加样本点,从而对初始最大等效应力的Kriging模型进行更新;最后,对更新后的Kriging代理模型计算新能源电动汽车转向驱动桥空心半轴的可靠度。结果表明:与MCS方法相比,基于AK-MCS方法的可靠度分析在时间上缩短2000余倍;与Kriging+MCS方法相比,基于AK-MCS方法的可靠度分析误差减小了50%。由此验证了基于AK-MCS方法空心半轴可靠度分析的高效性和准确性,为电动汽车转向驱动桥空心半轴可靠性的研究提供了理论依据,具有一定的工程意义。
文摘增益(Gain)校正有助于消除MC-ICP-MS不同高阻放大器之间的阻值差异,进而提高同位素分析的精度和准确度,但有关Gain的偏移和校正频率对同位素测试的影响和作用原理还缺乏系统认识。本研究结合本实验室Neptune Plus MC-ICP-MS的Gain校正数据,以实际测试的汞同位素数据为例,评估了放大器Gain校正系数偏移对同位素测试的影响。结果显示,当测试标样和样品的校正系数偏移幅度一致时,汞同位素测试结果基本无变化;当偏移幅度存在明显差异且单一放大器校正系数的相对偏移幅度超过–0.070‰~0.058‰时,汞同位素的测试结果大于分析误差。Gain校正系数单日的相对变化幅度(–0.028‰~0.028‰)可保证汞同位素测试结果小于分析误差,但长期的偏移却会导致汞同位素变化远超分析误差。此外,仪器的硬件、温度和真空度等也是Gain校正系数变化的重要影响因素,因此建议定期维护仪器,并每日进行Gain校正,以保证测试结果的稳定和准确。