微温传感器系统的研制

为评价云南天文台抚仙湖太阳望远镜的圆顶视宁度,研制一种能测量常温、微温的仪器。在天文建筑物附近,安放两个微温传感器,可以测量影响天文观测的湍流强度的分布情况。介绍微温传感器的工作原理、硬件设计、软件设计以及仪器的测试。实验结果表明,该传感器具有较高的分辨率和较快的热响应时间,它将对望远镜建设物的设计具有实际意义。     

基于Web的高校学生学籍管理系统设计与实现

设计基于B/S架构的高校学生学籍管理系统,后台数据库采用开源数据库MySQL,服务器端脚本采用PHP语言编写。根据学籍管理系统的结构和功能进行数据库的设计,数据库的连接使用开源的第三方数据库框架ADODB进行数据的存取,可以批量导入和导出相关数据。实现通过网络实时管理学生的学籍工作,使学生自我管理-院系学生管理-学生处的管理三者之间建立紧密的联系。     

火焰动画快速模拟的新方法

针对火焰动画难以快速建模和绘制的问题,提出了完全利用GPU过程化生成火焰动画的高效算法。先用建模工具在预处理阶段构建一个由平面正方形组成的三维模型,在绘制阶段通过GPU编程对这些方形进行Billboard方式的变换,并用一些简单公式对他们的运动方式、大小和颜色来用过程化方式进行控制,最后通过alpha混合得到最终结果。算法完全在GPU里实现,能满足实时的绘制要求。     

长流道式直线型沉沙池结构优化与数值模拟

沉沙池是保障滴灌系统正常运行的重要设施之一,但灌溉期池内水沙“固液”耦合过程比较复杂,且难以通过单一物理模型进行结构优化。为进一步提高滴灌系统沉沙效率,设计了长流道直线型沉沙池;采用物理试验与数值模拟相结合的方式,研究有无调流板和不同调流板角度对池内水沙运动规律的影响。结果表明:Fluent软件可准确模拟池内“固液”耦合过程;后池设计的调流板起到了消能、降速和提高沉沙率的作用;相较于无调流板,有调流板时后池流速可降低70%以上,沉沙率提高12%以上;且60°倾角调流板池内流速最低,沉沙率最高,出口含沙量最低为1.12 g/L,沉沙率平均可达到71.26%。研究可为优化水工结构、提高沉沙池工作效率提供一定的技术支撑。     

The parameterized level set method for structural topology optimization with shape sensitivity constraint factor

In recent years, the parameterized level set method (PLSM) has attracted widespread attention for its good stability, high efficiency and the smooth result of topology optimization compared with the conventional level set method. In the PLSM, the radial basis functions (RBFs) are often used to perform interpolation fitting for the conventional level set equation, thereby transforming the iteratively updating partial differential equation (PDE) into ordinary differential equations (ODEs). Hence, the RBFs play a key role in improving efficiency, accuracy and stability of the numerical computation in the PLSM for structural topology optimization, which can describe the structural topology and its change in the optimization process. In particular, the compactly supported radial basis function (CS-RBF) has been widely used in the PLSM for structural topology optimization because it enjoys considerable advantages. In this work, based on the CS-RBF, we propose a PLSM for structural topology optimization by adding the shape sensitivity constraint factor to control the step length in the iterations while updating the design variables with the method of moving asymptote (MMA). With the shape sensitivity constraint factor, the updating step length is changeable and controllable in the iterative process of MMA algorithm so as to increase the optimization speed. Therefore, the efficiency and stability of structural topology optimization can be improved by this method. The feasibility and effectiveness of this method are demonstrated by several typical numerical examples involving topology optimization of single-material and multi-material structures.

     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.     

Complementary metamaterial transmission line for monoband and dual‐band bandpass filters application

A novel composite right‐/left‐handed transmission line (CRLH TL) and its equivalent circuit model are proposed based on cascaded complementary single split ring resonator (CCSSRR). It features an intrinsically balanced wider band and an additional transmission zero above the right‐handed band relative to CRLH TL using complementary single split ring resonator and complementary split ring resonators. Moreover, two single negative (SN) metamaterial (MTM) TLs constructed by using complementary electric inductive‐capacitive resonator on the conductor strip and on the ground, respectively, are researched. Both SN MTM TLs exhibit electric resonance above the fundamental magnetic resonance. For application, a monoband (MB) bandpass filter (BPF) covered WLAN band, and a dual‐band (DB) BPF covered satellite DMB band and WiMAX band are designed, fabricated, and measured. The SN MTM TLs are adopted for the sake of deep and wide out‐of‐band suppression while CRLH MTM TLs using square‐shaped and Sierpinski‐shaped CCSSRR are critical factors of the MB and DB behavior. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

A novel range-free localization based on regulated neighborhood distance for wireless ad hoc and sensor networks

Range-free localization methods are suitable for large scale wireless ad hoc and sensor networks due to their less-demanding hardware requirements. Many existing connectivity- or hop-count-based range-free localization methods suffer from the hop-distance ambiguity problem where a node has a same distance estimation to all of its one-hop neighbors. In this paper, we define a new measure, called regulated neighborhood distance (RND), to address this problem by relating the proximity of two neighbors to their neighbor partitions. Furthermore, we propose a new RND-based range-free localization method, and compare our localization algorithm with peer classical algorithms in different network scenarios, which include grid deployment, random uniform deployment, non-uniform deployment and uniform deployment with a coverage hole. Simulation results show that ours can achieve better and reliable localization accuracy in these network scenarios.     

熔体处理对一种Inconel 718C改型高温合金组织与性能的影响

在试验合金中,1600℃熔体处理对凝固后组织和性能产生显著影响。经1600℃熔体处理后,合金样品二次枝晶间距显著降低,元素偏析情况得到有效改善,凝固过程析出的TCP相数量明显减少,热处理后γ″析出相也更加细小均匀。熔体处理对合金室温和700℃拉伸强度影响不大,但却显著提高合金的拉伸塑性和700℃/620MPa持久性能。在1600℃熔体处理10min时,合金的综合力学性能最佳;延长熔体处理时间至15min时,合金力学性能呈下降趋势。