Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.     

热塑性聚氨酯弹性体包覆CL-20及对NEPE推进剂性能影响

采用热塑性聚氨酯弹性体,通过水-溶液悬浮法将其包覆于六硝基六氮杂异伍兹烷(CL-20),并对包覆后的CL-20分别进行了XPS、SEM、撞击感度和表面能测试;研究了弹性体包覆CL-20对含CL-20的NEPE推进剂常温力学性能、燃烧性能的影响.研究表明,热塑性弹性体能有效包覆CL-20,在大幅度提高含CL-20的NEPE推进剂常温力学性能并改善"脱湿"的同时,改善高能低特征信号配方燃烧性能,σm最大提高了47%,εm最大提高了184%;燃速压强指数n降低了12%.     

基于工业物联网的混流车间机器人自适应调度

随着工业物联网技术与人工智能技术深度融合,物料机器人已广泛应用于物联网车间中.针对车间存在实时动态变化和状况不确定等诸多复杂因素,本文提出以组分层建树和以实时状态为根节点的SP–MCTS(Single-player monte-carlo tree search algorithm)搜索方法实现车间自适应调度决策.该方...     

基于粒子云方法研究地磁场对运动电子束的时空分布影响

空间电荷效应是空间带电粒子分布直接产生的相关效应,对于理解空间辐射环境有着重要意义。为研究地球磁场对空间电荷效应的影响,文章通过数值求解Poisson方程和相对论粒子运动方程,建立粒子云（particle-in-cell, PIC）自洽模型,并构建地球偶极子磁场模型作为内磁层背景磁场（空间分布L值为3～7）。在模型基础上,给出内磁层典型电子束结构（能量0.1～100 keV）的两种初始分布（Uniform和Gaussian分布）,模拟电子束在地磁场影响下的动力学过程。结果表明：电子束结构受地磁场影响出现纵向的整体偏转,并由于自场效应产生了纵向的拉伸和横向的发散;电子束整体的偏转角主要受地磁场强弱以及电子束运动与磁场夹角影响,而拉伸和发散效应则主要受电子束能量等参数所影响。     

ZnO纳米棒阵列/QCM超疏水空间污染气敏传感器性能研究

空间环境污染监测中,石英晶体微天平（QCM）传感器可通过增加比表面积增强对有机污染分子的吸附能力,通过表面超疏水化减小水分子的影响,从而提高传感器的探测精度。文章采用水热法在QCM表面制备 ZnO纳米棒阵列膜,并对其形貌和物化性能进行实验测试。研究结果表明：ZnO纳米棒的顶端呈六边形,属于六方纤锌矿结构;ZnO纳米棒沿(002)晶面择优生长,具有较低的表面自由能;纳米棒之间存在空隙,表面接触角可达150°,表现出超疏水性能;ZnO纳米棒阵列增加了有机分子的吸附位点,使石英晶振吸附有机分子的能力更强;同时,ZnO纳米棒阵列具有一定的光催化性能,140 min内光催化降解罗丹明B的效率约为35.5%。以上研究工作可为空间环境有机分子污染监测提供技术参考。     

基于干扰距离控制的直升机桨-涡干扰噪声降噪方法

提出了一种适用于直升机旋翼桨-涡干扰距离计算的方法.针对桨-涡干扰距离计算中必需的旋翼桨盘入流及桨盘倾角,又分别建立了旋翼耦合N-S(Navier-Stokes)/自由尾迹模型和桨盘配平模型进行求解,其特点是兼顾计算精度和计算效率;并从悬停、前飞两方面验证了方法的有效性.应用所建立的桨-涡干扰距离计算方法,着重分析了直...     

A novel architecture of electro-hydrostatic actuator with digital distribution

To address the flow imbalance rapidly of the asymmetric Electro-Hydrostatic Actuator (EHA), this paper presents a novel architecture of asymmetric EHA with the Digital Distribution (EHA-DD). It also improves the flow nonlinearity and control accuracy of the pump, especially in the low-speed condition. The digital distribution with two High-Speed on–off Valves (HSVs) not only balances flow instead of the check valves, but also replaces the pump at the low-speed to control output flow by adjusting the PWM signal. The pump and HSVs are the crucial components to control flow output. Firstly, the flow calculation models of the pump and the duty ratio inversed model of the HSV are obtained through experimental tests and the identification method. To get the control input signal for the required flow, the pump speed and PWM duty ratio for the HSVs are inversed to compensate for flow output. Further, a multimode digital flow distribution control method based on pump speed, mainly including the pump-controlled mode for large flow demand and valve-controlled mode for little flow demand, is proposed to control the accurate flow output actively. The step extension experiments based on the flow calculation models are conducted on the EHA-DD prototype under elastic, opposite varying load. The results demonstrate that the EHA-DD realizes little position error by accurate flow control, and it is also beneficial to improve the service life of the pump.     

Coronal mass ejection detection using wavelets,curvelets and ridgelets: Applications for space weather monitoring

Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic field that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph images, wavelet and multiscale image processing techniques are well suited to enhancing the visibility of CMEs and suppressing noise. However, wavelets are better suited to identifying point-like features, such as noise or background stars, than to enhancing the visibility of the curved form of a typical CME front. Higher order multiscale techniques, such as ridgelets and curvelets, were therefore explored to characterise the morphology (width, curvature) and kinematics (position, velocity, acceleration) of CMEs. Curvelets in particular were found to be well suited to characterising CME properties in a self-consistent manner. Curvelets are thus likely to be of benefit to autonomous monitoring of CME properties for space weather applications.     

Contamination of short GRBs by giant magnetar flares: Significance of downward revision in distance to SGR 1806–20

We highlight how the downward revision in the distance to the star cluster associated with SGR 1806–20 by Bibby et al. (2008) reconciles the apparent low contamination of BATSE short GRBs by intense flares from extragalactic magnetars without recourse to modifying the frequency of one such flare per 30 years per Milky Way galaxy. We also discuss the variety in progenitor initial masses of magnetars based upon cluster ages, ranging from ∼50 M_⊙ for SGR 1806–20 and AXP CXOU J164710.2–455216 in Westerlund 1 to ∼17 M_⊙ for SGR 1900+14 according to Davies et al. (2009) and presumably also 1E 1841–045 if it originated from one of the massive RSG clusters #2 or #3.