On developing data-driven turbulence model for DG solution of RANS

High-order Discontinuous Galerkin(DG) methods have been receiving more and more attentions in the area of Computational Fluid Dynamics(CFD) because of their high-accuracy property. However, it is still a challenge to obtain converged solution rapidly when solving the Reynolds Averaged Navier–Stokes(RANS) equations since the turbulence models significantly increase the nonlinearity of discretization system. The overall goal of this research is to develop an Artificial Neural Networks(ANNs) model with low complexity acting as an algebraic turbulence model to estimate the turbulence eddy viscosity for RANS. The ANN turbulence model is off-line trained using the training data generated by the widely used Spalart–Allmaras(SA) turbulence model before the Optimal Brain Surgeon(OBS) is employed to determine the relevancy of input features.Using the selected relevant features, a fully connected ANN model is constructed. The performance of the developed ANN model is numerically tested in the framework of DG for RANS, where the‘‘DG+ANN" method provides robust and steady convergence compared to the ‘‘DG+SA" method. The results demonstrate the promising potential to develop a general turbulence model based on artificial intelligence in the future given the training data covering a large rang of flow conditions.     

Solar neutron events as a tool to study particle acceleration at the Sun

The Sun provides unique opportunities to study particle acceleration mechanisms using data from detectors placed on the Earth’s surface and on board spacecrafts. Particles may gain high energies by several physical mechanisms. Differentiating between these possibilities is a fundamental problem of cosmic ray physics. Energetic neutrons provide us with information that keeps the signatures of the acceleration site. A summary of some representative solar neutron events observed on the Earth’s surface, including associated X and γ-ray observations from spacecrafts is presented. We discuss evidence of acceleration of particles by the Sun to energies up to several tens of GeV. In addition, a recent solar neutron event that occurred on September 7th 2005 and detected by several observatories at Earth is analyzed in detail.     

前体边条控制技术应用

采用各种不同形状和安装位置的前体边条对前体涡进行控制，研究各种前体边条对全机大迎角气动特性的影响。     

用Ce~(3+):YVO_4晶体荧光粉与蓝光LED制造自然白光LED

本文报导了通过结合自行制备的掺铈钒酸钇晶体(Ce3 :YVO4)荧光粉与InGaN／GaN蓝光发光二极管(LED)结合而得的白光发光二极管(W-LED)。在室温、正向电压3.5V、正向电流20mA时W-LED的CIE色坐标为(0．32,0．37),接近纯白色(0．33,0．33)。     

30CrMnSiA钢管外圆磁力研磨工艺的研究

采用化学粘结Ｆｅ＋ＳｉＣ磁性料对３０ＣｒＭｎＳｉＡ钢管外圆进行磁力研磨试验，研究了磨料成分、粒度以及研磨时间与研磨后表面粗糙度的关系，试验所得到的研磨表面粗糙度达到了Ｒａ０．０５μｍ。     

谈当代大学生的心理困惑

从社会问题、学习、人际交流、情感四个方面分析了目前在技大学生心理矛盾和困惑的表现及原因。     

某型航空发动机高原起动供油规律研究

以某型航空发动机作为研究平台,通过对发动机起动工作过程和起动供油调节分析,研究了地面平原起动供油和高原起动供油关系。在兼顾了空中起动的基础上,提出了在高原环境下的起动供油控制规律:调整改变自动起动器和起动放气嘴。以发动机在平原地区机场起动调整方法为基础,得到了在高原机场起动调整方法,并在高原机场试验验证中取得满意结果,解决了发动机在高原进气气压低,含氧量较少,温度较高,一系列恶劣的进气条件下起动中热悬挂、冷悬挂、起动失速等起动极限问题,可为其他型号发动机的高原起动借鉴。     

随钻测斜用微小型导航计算机系统设计与实现

为了满足随钻测斜仪器在油气井中恶劣环境下的测量要求,本文提出了一种以数字信号控制器（DSC）和FPGA组成的双CPU导航计算机方案。该系统由DSC（dsPIC30F6014A）作为核心处理器完成导航计算和滤波算法;由FPGA完成对IMU（惯性测量单元）数据的采集控制及传输等功能。DSC与FPGA之间通过串口传输,最终导航结果由DSC输出给外部控制设备。该系统很好的满足了随钻测斜仪的性能尺寸要求,试验验证结果表明倾斜角、方位角、和工具面角均达到了预期精度指标。     

北京平原地区VS30估算模型适用性研究

本文使用基于钻孔测井数据的3类模型,即常速度外推模型、速度梯度模型、双深度参数外推模型,通过对北京地区460个深度超过30m的钻孔剪切波速资料进行分析,详细探究了V_(S30)估算模型在本研究区的适用性。研究结果表明双深度参数外推模型在估算V_(S30)上准确度很高,其不需要大量的数据进行回归分析,且不具有区域独立性,可以为全球包括北京地区场地类别划分提供依据,进而在震害快速评估中用于确定场地影响,是一种值得推广的估算模型。