齐大山铁矿南帮含水构造带探测研究

为解决采空区突发涌水给矿山安全生产带来的安全威胁,以齐大山铁矿为研究对象,以高密度电阻率法含水构造带理论模型的正演模拟研究为基础,运用高密度电阻率法对采场南帮含水构造带的异常范围进行了圈定;运用瞬变电磁法进行了二次探测,并对高密度电阻率法所圈定的异常范围进行了验证。研究表明:含水构造带显示为低阻异常特征,在高密度电阻率法探测成果图中显示的两处低阻异常与含水构造带理论模型的正演模拟结果一致;同时,在瞬变电磁法探测成果图中显示的低阻区域均在高密度电阻率法所圈定的低阻异常范围内,二者相互验证,这两处低阻异常均为含水构造带的地球物理异常特征的显示,表明采用高密度电阻率法和瞬变电磁法组合识别技术可实现对隐伏含水构造带的先导性探测。     

Enhanced hollow fiber membrane performance via semi-dynamic layer-by-layer polyelectrolyte inner surface deposition for nanofiltration and forward osmosis applications

The layer-by-layer (LBL) polyelectrolyte deposited membranes have drawn increasing attention in various applications due to the ease of selective layer formation and their stability and versatility. In this study, the LBL deposition was performed at the inner surface of the polyethersulfone (PES) hollow fiber substrate to form composite nanofiltration (NF) membrane. The semi-dynamic deposition procedure was adopted with the aid of syringes. The newly developed inner deposited (id-LBL) membranes were then tested in NF and forward osmosis (FO) applications and the performance were compared with outer surface deposition as well as some literature data. The id-LBL membranes could not only withstand higher operating pressure but also possess superior hardness rejection especially in high concentration mixed salt solutions (more than 95% rejection to Mg²⁺ and Ca²⁺ in a 5000 ppm total dissolved salt (TDS) mixture under 4.8 bar). As for the FO process, with only two layer deposition, the id-LBL membranes also demonstrated significant performance improvement with increased water flux (up to 70 L/m² h using 0.5 M MgCl₂ as draw solution in active layer facing draw solution configuration) and reduced salt leakage (around 0.5 g/m² h using 1 M MgCl₂ draw solution in active layer facing feed water configuration). This study suggests that for hollow fiber substrate, the inner surface is more suitable for the formation of the selective layer via LBL deposition than the outer surface.     

A closed loop supply chain under retail price and product quality dependent demand

The importance of remanufacturing of used products, maintaining the same quality as new ones has been widely recognized in practice. In this paper, we address a closed loop supply chain where the manufacturer manufactures a product with a decent quality acceptable to customers, and sells it through a retailer in the market. A third party collects the used products from consumers and sends to the manufacturer. The manufacturer re-manufactures the used product and the quality of remanufactured product is the same as that of the manufactured one. For such a closed loop supply chain, we construct five different scenarios – centralized, decentralized or Nash game and three different Stackelberg games, led by the manufacturer, retailer and third party respectively. We compare the optimal results to find out the best decentralized scenario out of the four mentioned. A numerical example is taken to study the impacts of product quality on demand as well as optimal decisions and investigate sensitivity of some key model-parameters.     

航空物探遥感地质资料定密工作初探与实践

在地质调查信息化与地质资料社会化服务工作不断发展的背景下,航空物探遥感地质资料的开发利用与保密管理工作矛盾日益凸显。本文以航空物探遥感资料定密为研究重点,总结了地质、测绘地理信息、海洋等工作领域的定密工作情况,基于对航空物探遥感地质资料分类结果提取了共性资料涉密要素/事项,根据保密法规的相关规定与要求,初步建立了以比例尺/空间精度、测绘地理信息要素、航空物探遥感专业要素为主的定密判定要素集,提出了航空物探遥感地质资料的定密工作原则与参考准则,以期为航空物探遥感地质信息共享服务提供必要的工作支撑。     

Pathways to controlled 3D deformation of graphene: Manipulating the motion of topological defects

Functional properties of 2D materials like graphene can be tailored by designing their 3D structure at the Angstrom to nanometer scale. While there are routes to tailoring 3D structure at larger scales, achieving controllable sub-micron 3D deformations has remained an elusive goal since the original discovery of graphene. In this contribution, we summarize the state-of-the-art in controllable 3D structures, and present our perspective on pathways to realizing atomic-scale control. We propose an approach based on strategic application of mechanical load to precisely relocate and position topological defects that give rise to curvature and corrugation to achieve a desired 3D structure. Realizing this approach requires establishing the detailed nature of defect migration and pathways in response to applied load. From a computational perspective, the key needed advances lie in the identification of defect migration mechanisms. These needed advances define new forward and inverse problems: when a fixed stress or strain field is applied, along which pathways will defects migrate?, and vice versa. We provide a formal statement of these forward and inverse problems, and review recent methods that may enable solving them. The forward problem is addressed by determining the potential energy surface of allowable topological configurations through Monte Carlo and Gaussian process models to determine defect migration paths through dynamic programming algorithms or Monte Carlo tree search. Two inverse models are suggested, one based on genetic algorithms and another on convolutional neural networks, to predict the applied loads that induce migration and position defects to achieve desired curvature and corrugation. The realization of controllable 3D structures enables a vast design space at multiple scales to enable new functionality in flexible electronics, soft robotics, biomimetics, optics, and other application areas.     

Physics-informed deep learning for one-dimensional consolidation

Neural networks with physical governing equations as constraints have recently created a new trend in machine learning research.In this context,a review of related research is first presented and discussed.The potential offered by such physics-informed deep learning models for computations in geomechanics is demonstrated by application to one-dimensional(1D)consolidation.The governing equation for 1D problems is applied as a constraint in the deep learning model.The deep learning model relies on automatic differentiation for applying the governing equation as a constraint,based on the mathematical approximations established by the neural network.The total loss is measured as a combination of the training loss(based on analytical and model predicted solutions)and the constraint loss(a requirement to satisfy the governing equation).Two classes of problems are considered:forward and inverse problems.The forward problems demonstrate the performance of a physically constrained neural network model in predicting solutions for 1D consolidation problems.Inverse problems show prediction of the coefficient of consolidation.Terzaghi’s problem,with varying boundary conditions,is used as a numerical example and the deep learning model shows a remarkable performance in both the forward and inverse problems.While the application demonstrated here is a simple 1D consolidation problem,such a deep learning model integrated with a physical law has significant implications for use in,such as,faster realtime numerical prediction for digital twins,numerical model reproducibility and constitutive model parameter optimization.     

运输类飞机全机操纵系统功能检查试验技术研究及应用

运输类飞机驾驶舱位于机头内部,常规的试验加载设备难以固定,在全机操纵系统功能检查试验中如何准确地模拟飞行员对机械操纵装置加载成为该类试验亟待解决的问题。为了达到考核飞机结构静强度的同时实现舵面的功能检查,提出一种全新的全机静力试验舵面功能检查试验技术。通过驾驶盘双向大转角加载技术、基于响应的载荷谱自动切换技术及多向转角实时监测技术等模拟飞行员操纵过程及舵面受载情况,获得操纵力曲线及舵面响应曲线,成功解决了试验中的加载、控制及测量问题。最后以大型灭火/水上救援水陆两栖飞机操纵系统功能检查试验为研究对象,采用新方法顺利完成了试验,因此该方法满足试验要求。     

6 SPS并联机构的运动学仿真与分析

位置正解求解是6-SPS并联机构运动学计算的难点,为方便确定位置正解,在ADAMS环境中为6-SPS并联机构的动平台添加一个初始多自由度驱动,进行运动学仿真。得出仿真位置逆解,并在MATLAB环境中求得理论位置逆解,验证了仿真位置逆解的正确性。将仿真位置逆解作为输入参数驱动此并联机构,得到其位置正解,结果表明:位置正解与初始多自由度驱动的值吻合,说明所得位置正解正确。表明运用上述方法可简单方便地计算出6-SPS并联机构所需的正解,可为此类机构位置正解的求解与控制提供参考。     

爆破片疲劳实验装置的研制及其应用

爆破片作为一种保护压力容器安全的安全泄放装置,其疲劳寿命是工程中十分关注的问题。由于对爆破片疲劳特性方面的研究不多,而对在役爆破片疲劳寿命的影响因素又较多,故规定和预测爆破片寿命相当困难。搭建了一个应用范围广、压力波形可调、耐疲劳性能强的,能用于爆破片疲劳实验的实验装置,设计实验夹具,针对普通正拱型爆破片进行了疲劳实验,发现爆破片的疲劳破坏均发生在边缘位置,并与静压爆破实验的破坏位置作对比。研究了压环圆角对爆破片疲劳寿命的影响,为正拱型爆破片的设计制造提供参考。     

多用户MISO干扰信道中的安全协同波束成形

针对多用户多输入单输出(MISO, multiple-input single-output)干扰信道中保密信息泄露问题,提出了理想信道状态信息(CSI, channel state information)下的安全协同波束成形(SCB, secure coordinated beamforming)方案和非理想CSI下的顽健安全协同波束成形(RSCB, robust secure coordinated beamforming)方案。对于理想CSI情况,联合设计最优的协同波束成形向量,最大化最小安全速率。采用半定松弛(SDR, semidefinite relaxation)技术和连续的凸估计(SCA, successive convex approximation)算法得到原始非凸问题的局部最优解。进一步,将该框架扩展到信道向量和信道协方差矩阵存在确定误差的情况,提出的RSCB方案能够最大化最差情况的安全速率。仿真结果验证了所提方案的有效性和顽健性。