大学英语教学中创新能力的培养

首先明确了创新的定义并在此基础上探索了大学英语教学上的弊端。其次联系“创新”这一概念,就如何在大学英语教学中培养学生的创新能力进行了阐述。最后,就应该如何在大学英语课堂上激发学生的创新能力提出了具有实际意义的建议。     

Bump进气道中鼓包诱导的激波/边界层干扰特性

为了探索Bump进气道中鼓包诱导的锥形激波和机身发展而来的湍流边界层干扰问题,分析其气动优势,首先选取了半锥和半棱锥这两种与鼓包的流场结构具有一定相似性的构型作为参照,采用数值仿真方法,分别对这三类典型的三维激波/湍流边界层干扰问题进行了流场分析。在此基础之上,设计了三个不同马赫数的鼓包,并研究了设计马赫数对鼓包流场特性的影响。结果表明:当三类构型的无黏激波强度相等时,半锥诱导产生的旋涡强度最强,鼓包次之,半棱锥最弱。尽管鼓包诱导的流场非常复杂,其干扰流场却呈现出准锥形相似的特性。虽然半锥对边界层的排移能力最强,但是综合考虑边界层排移能力及进气道出口流场畸变下,鼓包最具优势,这也是其被选为超声速进气道前缘压缩面的重要原因之一。此外,在设计状态下,适当增加设计马赫数能改善鼓包排移边界层的能力,但设计马赫数太高,边界层排移能力基本不变,反而使得进气道总压损失急剧增加。      

Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride (cBN) superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness, such as titanium alloys and superalloys. However, grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance, the chip storage capability of the working layers and the stability and controllability of the dressing process. Therefore, in this work, novel metallic cBN superabrasive wheels with aggregated cBN (AcBN) grains and open pore structures were fabricated to improve machining efficiency and surface quality. Prior to the grinding trials, the air-borne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials. Subsequently, the comparative experiments were performed and then the variations in grinding force and force ratio, grinding temperature, tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti–6Al–4V alloys. In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes, the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60# and the abrasive blasting distance and time of 60 mm and 15 s, respectively. The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN (McBN) grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains. The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.     

增强神经网络辨识模型泛化能力的研究

神经网络(Artificial Neural Network,ANN)辨识模型的泛化能力是其最主要的性能之一,增强ANN模型的泛化能力也是近年来国内外有关专家学者研究的重点问题。大量研究表明,ANN模型泛化能力的改善与很多因素相关联,其中恰当的性能指标函数设计是一个重要影响因素。文中在分析常见的基于均方误差最小原则的性能指标函数基础上,通过加入ANN辨识模型权值间的延迟信息,进而获得一种改进型性能指标函数。通过仿真,验证了所设计的改进型性能指标函数对增强ANN辨识模型的泛化能力是有效的。