大功率立式电机转子有限元结构分析与优化

基于Pro/Engineer建立了某型号的大功率电机转子的实体模型和虚拟样机模型,在MSC.PATTERN/NASTRAN环境下,利用有限元方法进行了电机转子的动力学仿真、应力位移仿真,得到了转子两端轴承的力学状态、转子的应力、位移等参数值.根据仿真结果,进行了转子的强度和刚度校核,分析了转子的主要破坏形式和危险位置.结果表明现有电机转子的结构基本满足设计要求,并在此基础上优化转子外径和支承结构,减小电机振动,优化工艺,为同类产品的开发和改进提供了参考.     

RTD/HEMT串联型共振隧穿三极管的设计与研制

对RTD/HEMT串联型共振隧穿三极管进行了设计和研制.测量结果表明:最大电流峰谷比为17.6∶1,棚压对峰值电压调控能力在1.5～7.7范围内,-3dB截止频率为4GHz,此种器件可与HEMT在结构和工艺上兼容,可应用于HEMT高速电路.     

Bézier样条曲线改进的近似弧长参数化方法

提出了Bézier样条曲线利用分割技术近似弧长参数化的一种方法，并给出了相应的算法。通过求出曲线上所谓的‘最坏点’并在相应点处进行分割。可得到两条Bézier样条曲线。让这两条Bézier样条曲线具有与它们的近似弧长成比例的权，并对所得到的新的Bézier样条曲线进行同样的工作最终可得到一条由多条Bézier样条曲线所构成的新曲线。将这多条Bézier样条曲线合并成为一条Bézier样条曲线并通过节点插入技术将所得Bézier样条曲线转化为B一样条曲线的形式可得到全局参数域，其中各条Bézier曲线在全局参数域中所占子区间的长度与它们的权成比例，这样使得到了一条近似弧长参数化曲线。     

基于Shear-warp的交互式海量数据场体绘制算法

提出了基于min-max Octree快速分类Shear-warp的交互式海量数据场体绘制算法.主要包括根据海量数据的特征,快速读入数据以及设计适当的不透明度传递函数;建立Summed-Area表与min-max Octree数据结构,并对体数据进行快速分类,然后,利用分类的结果进行快速体绘制.实验证明该方法不仅效率高,而且显示效果好.     

提高电梯运行舒适感的有效途径

本文全面论述了影响电梯运行舒适感的原因，并提出了从电气和机械两个方面解决这些问题的办法。     

关于网络课堂的构建

优化教学手段、改善教学技术是保持高校设计艺术教育先进性的体现。利用网络实现课堂教学的互补也是新时期对教师提出的一项要求。本文介绍了构筑在“你我家”网络真实社区（http：／／www．niwojia．com）平台上的专业合作，交流组织“艺术设计联盟”（http：／／design．niwojia．com）的形成背景、发展历程和主要特点。     

Anisotropic nanowire growth via a self-confined amorphous template process: A reconsideration on the role of amorphous calcium carbonate

Calcium carbonate crystals with various morphologies have been found in a variety of biospecimens and artificially synthesized structures. Usually, the diversity in morphology can be attributed to different types of interactions between the specific crystal faces and the environment or the templates used for the growth of CaCO₃ crystals. On the other hand, isotropic amorphous calcium carbonate (ACC) has been recognized as the precursor of other crystalline calcium carbonate forms for both in vivo and in vitro systems. However, here we propose a self-confined amorphous template process leading to the anisotropic growth of single-crystalline calcite nanowires. Initiated by the assembly of precipitated nanoparticles, the calcite nanowires grew via the continuous precipitation of partly crystallized ACC nanodroplets onto their tips. Then, the crystalline domains in the tip, which were generated from the partly crystallized nanodroplets, coalesced in the interior of the nanowire to form a single-crystalline core. The ACC domains were left outside and spontaneously formed a protective shell to retard the precipitation of CaCO₃ onto the side surface of the nanowire and thus guided the highly anisotropic growth of nanowires as a template.

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A Simple Model to Describe Different Types of Exchange Bias Training Effect

The exchange bias (EB) training effect, referring to the exchange field (H _E) and/or the coercivity (H _C) decreasing with the magnetic cycle (n), is often accompanied with EB. Usually, the EB training effect has different types, showing that H _C1 (coercive field at the descending branch) and H _C2 (coercive field at the ascending branch) change with n differently. In order to understand the origin producing the training type, a phenomenological model is therefore proposed. According to this model, how H _C1 (or H _C2) changes with n is determined by the change of pinning magnetization at the descending (or ascending) branch during the training process. For verifying the validity of our model, various experimental training results with respect to different exchange-biased systems are selected for fitting and all the fitting results are nearly perfect.     

Shadow compensation and illumination normalization of face image

This study proposes a novel shadow compensation and illumination normalization method under uncontrolled light conditions. First, we decompose the face image into two images based on the Lambertian theory, which corresponds to the large- and small-scale features, respectively. Then, the threshold minimum-and-maximum filter on the small-scale features to smooth the shadow edge is applied. After that, the robust Principal Component Analysis and some normalization methods are used to remove the shadow and normalize the face image on the large-scale features. In the end, the normalized face image is obtained by combining both results from the large- and small-scale features. Our main contribution is that a more reliable shadow compensation approach is found, which can get a better normalized face image. Experiments on the Extended Yale B, CMU-PIE and FRGC 2.0 (Face Recognition Grand Challenge) face datasets show that not only the recognition performance is significantly improved, but also much better visual quality is achieved.