With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train ...With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.展开更多
基于系统行为过程的效能概念框架及度量方法,建立了系统目标树的层级模型以及反映系统内、外因素行为关联关系的系统贡献度模型,根据该模型推导出了一组系统效能指数和效能因子的计算公式,通过对系统内外因素状态变化对系统效能贡献度...基于系统行为过程的效能概念框架及度量方法,建立了系统目标树的层级模型以及反映系统内、外因素行为关联关系的系统贡献度模型,根据该模型推导出了一组系统效能指数和效能因子的计算公式,通过对系统内外因素状态变化对系统效能贡献度影响的过程分析计算,验证了所建立的模型和方法的合理性.所给出的通过系统行为贡献度模型求解系统效能指数和效能因子的方法.可以简称为贡献度模型法,或SEIF(System effectiveness index and factor)法,适用于对系统效能变化规律的分析和实际运行效能的量化评估.展开更多
目的探究客观因素和主观因素对急性脑梗死患者病情预后的影响,从而为改善急性脑卒中患者的预后提供理论依据。方法选取海南医学院第二附属医院2022年9月至11月就诊的急性脑梗死患者75例作为研究对象进行回顾性分析。根据美国国立卫生研...目的探究客观因素和主观因素对急性脑梗死患者病情预后的影响,从而为改善急性脑卒中患者的预后提供理论依据。方法选取海南医学院第二附属医院2022年9月至11月就诊的急性脑梗死患者75例作为研究对象进行回顾性分析。根据美国国立卫生研究院卒中量表(National Institute of Health stroke scale,NIHSS)、神经功能恢复状态量表(modified Rankin scale,mRS)、Barthel量表(Barthel index)(日常生活能力评定)对患者出入院前的神经功能缺损进行评估。对急性脑梗死患者的预后结局的相关因素进行回归性分析,探究上述因素是否对急性脑梗死患者的预后有着临床影响。结果接触过中风120知识宣传(是vs.否)(OR=0.276,95%CI:0.097~0.784)、就诊时间(OR=1.108,95%CI:1.009~1.216)、居住方式(合居vs.独居)(OR=0.259,95%CI:0.08~0.841)皆是急性脑梗死患者预后的影响因素。接触过中风120宣传的急性脑梗死患者出院前NIHSS评分、mRS评分要低于未接触过中风120宣传的患者[(5.50±2.33)分vs.(6.94±2.36)分、2.50(2.00,3.00)分vs.3.00(2.00,4.00)分](P均<0.05);同时出院前学习过中风120知识宣传的患者的Barthel评分要高于未学习过中风120急救知识宣传的患者[65.00(51.25,80.00)分vs.50.00(25.00,75.00)分](P<0.05)。结论中风120急救知识宣传可强化患者及家属对急性脑卒中疾病的认识,从而促使患者能够及时就医,最大程度上降低患者的病情延误的概率,对急性脑卒中患者的预后有着极为重要的临床意义。展开更多
基金Project supported by the National Natural Science Foundation of China (No. 50823004)the National Key Technology R&D Program of China (No. 2009BAG12A01-C09)+1 种基金the 2013 Doctoral Innovation Funds of Southwest Jiaotong Universitythe Fundamental Research Funds for the Central Universities, China
文摘With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.
文摘基于系统行为过程的效能概念框架及度量方法,建立了系统目标树的层级模型以及反映系统内、外因素行为关联关系的系统贡献度模型,根据该模型推导出了一组系统效能指数和效能因子的计算公式,通过对系统内外因素状态变化对系统效能贡献度影响的过程分析计算,验证了所建立的模型和方法的合理性.所给出的通过系统行为贡献度模型求解系统效能指数和效能因子的方法.可以简称为贡献度模型法,或SEIF(System effectiveness index and factor)法,适用于对系统效能变化规律的分析和实际运行效能的量化评估.
文摘目的探究客观因素和主观因素对急性脑梗死患者病情预后的影响,从而为改善急性脑卒中患者的预后提供理论依据。方法选取海南医学院第二附属医院2022年9月至11月就诊的急性脑梗死患者75例作为研究对象进行回顾性分析。根据美国国立卫生研究院卒中量表(National Institute of Health stroke scale,NIHSS)、神经功能恢复状态量表(modified Rankin scale,mRS)、Barthel量表(Barthel index)(日常生活能力评定)对患者出入院前的神经功能缺损进行评估。对急性脑梗死患者的预后结局的相关因素进行回归性分析,探究上述因素是否对急性脑梗死患者的预后有着临床影响。结果接触过中风120知识宣传(是vs.否)(OR=0.276,95%CI:0.097~0.784)、就诊时间(OR=1.108,95%CI:1.009~1.216)、居住方式(合居vs.独居)(OR=0.259,95%CI:0.08~0.841)皆是急性脑梗死患者预后的影响因素。接触过中风120宣传的急性脑梗死患者出院前NIHSS评分、mRS评分要低于未接触过中风120宣传的患者[(5.50±2.33)分vs.(6.94±2.36)分、2.50(2.00,3.00)分vs.3.00(2.00,4.00)分](P均<0.05);同时出院前学习过中风120知识宣传的患者的Barthel评分要高于未学习过中风120急救知识宣传的患者[65.00(51.25,80.00)分vs.50.00(25.00,75.00)分](P<0.05)。结论中风120急救知识宣传可强化患者及家属对急性脑卒中疾病的认识,从而促使患者能够及时就医,最大程度上降低患者的病情延误的概率,对急性脑卒中患者的预后有着极为重要的临床意义。
