公路轻型砌块式挡土墙受力特性及设计计算方法研究

提出一种运用于公路的轻型砌块挡土墙，对其结构体系及组成进行了概述。利用Marc有限元程序对局部砌块单元以及整体结构的变形及受力进行了受力分析，对该挡土结构的整体设计计算及稳定性分析方法进行了探讨。分析结果与工程实用经验表明，H形砌块挡土结构能充分利用材料的抗压性能，施工速度快、排水性能良好、可承受一定的沉降量及沉降差等优点。     

疏散模式下接触轨系统控制方案研究

通过分析地铁火灾事故特点,并结合NFPA 130相关规定,提出接触轨牵引供电系统和整个疏散救援活动的配合方案。在车站、区间等地设置集成式蓝光站,使牵引供电系统能够准确、快速的切换接触轨带电状态,为疏散救援提供安全保障,提高逃生几率。     

考虑输入滞后的磁悬浮列车悬浮系统的鲁棒H_∞容错控制

以磁悬浮列车单模块悬浮系统为对象,考虑系统存在的输入时滞,建立了时滞悬浮系统的数学模型,基于状态反馈和线性矩阵不等式处理方法,设计了在执行器发生故障情况下的鲁棒H∞容错控制器,在此基础上,针对不同执行器故障模式,对悬浮间隙的变化情况进行了仿真。仿真结果表明所设计的控制器在执行器故障条件下能够使磁悬浮列车稳定悬浮与运行。     

路中高架车站的景观设计

论述高架车站景观设计的研究背景;从行人对外部空间的感受入手,对路中高架车站景观设计中首先应当考虑的核心要素(城市、行人、车站功能等)进行分析;通过建立计算机模型、分析建成车站实例、引入D/H理论(D为视点到视觉对象的距离,H为视觉对象的高度)等方法,对这些核心要素进行研究.     

从H.264向H.265的数字视频压缩技术升级

H.264虽然是一个划时代的数字视频压缩标准,但是随着数字视频产业链的高速发展,H.264的局限性逐步显现,并且由于H.264标准核心压缩算法的完全固化,并不能够通过调整或扩充来更好地满足当前高清数字视频应用。通过描述H.264的关键技术,重点分析H.264的优缺点,并指出H.264向H.265数字视频压缩技术升级带来的变化和技术提升。     

二酯酰甘油-蛋白激酶C信号传导系统和细胞因子与糖尿病肾病的关系

目的研究糖尿病大鼠肾小球中蛋白激酶C(PKC)的活性变化及转化生长因子-β1(TGF-β1)和血管内皮细胞生长因子(VEGF)的表达情况,探讨3者之间的相互关系及其与糖尿病肾病(DN)发生、发展的相关性。方法选用雄性SD大鼠,用链脲佐菌素制备大鼠糖尿病实验模型,随机分为正常对照组、糖尿病2周(DM2)组和糖尿病4周(DM4)组。大鼠断头处死,分离肾小球,提取纯化胞浆及胞膜蛋白。利用[r-32P]-ATP底物磷酸化的方法检测胞浆及胞膜PKC活性;用免疫组织化学法检测VEGF和TGF-β1在各组大鼠肾小球及肾小管中的表达。结果①DM2、DM4组肾小球细胞内总的PKC活性与对照组无显著性差异,胞浆PKC活性略有下降,但相差不显著(P>0.05);DM2、DM4组肾小球细胞膜PKC活性均明显高于正常对照组(P<0.05),且细胞膜PKC活性与肾脏肥大指数(肾重/体质量)和内生肌酐清除率(Ccr)呈正相关。②DM2、DM4组VEGF和TGF-β1的表达均高于正常对照组(P<0.01)。③肾小球细胞膜PKC活性与VEGF和TGF-β1的表达呈正相关。结论高血糖慢性刺激可引起肾小球PKC活性增高,并上调TGF-β1和VEGF的表达,进一步导致肾小球滤过膜通透性和滤过率增加,这在糖尿病早期肾内血流动力学改变中发挥着重要的调控作用。     

基于GPSS／H仿真软件的沥青路面机群施工系统仿真模型研究

在对沥青路面施工系统分析的基础上,建立了基于GPSS/H系统仿真软件的沥青路面机械化施工仿真模型.对某路段沥青路面施工实例进行了仿真分析,确定了沥青路面机群施工机械的优化配置方案,该方案实现了沥青路面施工机械的最佳配置,提高了施工效率.     

用~3H和地高辛配基标记TNF—α cDNA探针进行原位杂交的比较

用~3H和地高辛配基标记肿瘤坏死因子-αcDNA探针以及原位杂文技术检测33例子宫颈癌和28例阴道尖锐湿疣活检标本中的TNF mRNA。结果表明,两种标记探针原位杂交结果基本一致,~3H标记探针敏感性稍高于地高辛配基标记探针。但放射性核素探针的固有缺点及非同位素探针的安全、快速、方便使非同位素探针有着日益广泛的应用前景。     

Designing H ∞/GH 2 static-output feedback controller for vehicle suspensions using linear matrix inequalities and genetic algorithms

This paper presents an approach to design the H _∞/GH ₂ static-output feedback controller for vehicle suspensions by using linear matrix inequalities (LMIs) and genetic algorithms (GAs). Three main performance requirements for an advanced vehicle suspension are considered in this paper. Among these requirements, the ride-comfort performance is optimized by minimizing the H _∞ norm of the transfer function from the road disturbance to the sprung mass acceleration, while the road-holding performance and the suspension deflection limitation are guaranteed by constraining the generalized H ₂ (GH ₂) norms of the transfer functions from the road disturbance to the dynamic tyre load and the suspension deflection to be less than their hard limits, respectively. At the same time, the controller saturation problem is considered by constraining its peak response output to be less than a given limit using the GH ₂ norm as well. A four-degree-of-freedom half-car model with active suspension system is applied in this paper. Several kinds of H _∞/GH ₂ static-output feedback controllers, which use the available sprung mass velocities or the suspension deflections as feedback signals, are obtained by using the GAs to search for the possible control gain matrices and then resolving the LMIs together with the minimization optimization problem. These designed H _∞/GH ₂ static-output feedback controllers are validated by numerical simulations on both the bump and the random road responses which show that the designed H _∞/GH ₂ static-output feedback controllers can achieve similar or even better active suspension performances compared with the state-feedback control case in spite of their simplicities.     

A novel method for identifying inertial parameters of electric vehicles based on the dual H infinity filter

ABSTRACT

Accurate identification of vehicle inertial parameters is essential to the design of vehicle dynamics control systems. In this paper, a novel vehicle inertial parameter identification method based on the dual H infinity filter (DHIF) for electric vehicles (EVs) is proposed. The filter algorithm employs a nonlinear longitudinal vehicle model with three vehicle states. A hierarchical framework is engaged by the DHIF to estimate the vehicle states and inertial parameters concurrently. In order to minimise the disturbance of unknown noise, the vehicle states are estimated by using the linear H infinity filter (LHIF), while the nonlinear H infinity filter (NHIF) utilises the observed states to identify the vehicle inertial parameters. Finally, the proposed estimation method is verified and compared through the dSPACE based hardware-in-the-loop (HIL) simulation experiments. The results indicate that the DHIF-based estimation method is effective to identify the vehicle inertial parameters with high precision, remarkable robustness, and quick convergence.