CONVEXITY OF THE FREE BOUNDARY FOR AN AXISYMMETRIC INCOMPRESSIBLE IMPINGING JET

This paper is devoted to the study of the shape of the free boundary for a threedimensional axisymmetric incompressible impinging jet.To be more precise,we will show that the free boundary is convex to the fluid,provided that the uneven ground is concave to the fluid.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions.Since nodes exchange optimization parameters through the wireless network,large-scale training models can create communication bottlenecks,resulting in slower training times.To address this issue,CHOCO-SGD was proposed,which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions.Nevertheless,most convex functions are not strongly convex(such as logistic regression or Lasso),which raises the question of whether this algorithm can be applied to non-strongly convex functions.In this paper,we provide the first theoretical analysis of the convergence rate of CHOCO-SGD on non-strongly convex objectives.We derive a sufficient condition,which limits the fidelity of compression,to guarantee convergence.Moreover,our analysis demonstrates that within the fidelity threshold,this algorithm can significantly reduce transmission burden while maintaining the same convergence rate order as its no-compression equivalent.Numerical experiments further validate the theoretical findings by demonstrating that CHOCO-SGD improves communication efficiency and keeps the same convergence rate order simultaneously.And experiments also show that the algorithm fails to converge with low compression fidelity and in time-varying topologies.Overall,our study offers valuable insights into the potential applicability of CHOCO-SGD for non-strongly convex objectives.Additionally,we provide practical guidelines for researchers seeking to utilize this algorithm in real-world scenarios.

Relaxed Stability Criteria for Time-Delay Systems:A Novel Quadratic Function Convex Approximation Approach

This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying delays.By introducing two adjustable parameters and two free variables,a novel convex function greater than or equal to the quadratic function is constructed,regardless of the sign of the coefficient in the quadratic term.The developed lemma can also be degenerated into the existing quadratic function negative-determination(QFND)lemma and relaxed QFND lemma respectively,by setting two adjustable parameters and two free variables as some particular values.Moreover,for a linear system with time-varying delays,a relaxed stability criterion is established via our developed lemma,together with the quivalent reciprocal combination technique and the Bessel-Legendre inequality.As a result,the conservatism can be reduced via the proposed approach in the context of constructing Lyapunov-Krasovskii functionals for the stability analysis of linear time-varying delay systems.Finally,the superiority of our results is illustrated through three numerical examples.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

Relaxed Stability Criteria for Delayed Generalized Neural Networks via a Novel Reciprocally Convex Combination

Dear Editor,This letter examines the stability issue of generalized neural networks(GNNs) with time-varying delay based on a novel reciprocally convex combination(RCC). By considering a new matrix polynomial, the proposed novel reciprocally convex method leads to a tight bound for integral inequality combination and encompasses several existing approaches as special cases.

DOUBLE INERTIAL PROXIMAL GRADIENT ALGORITHMS FOR CONVEX OPTIMIZATION PROBLEMS AND APPLICATIONS

In this paper, we propose double inertial forward-backward algorithms for solving unconstrained minimization problems and projected double inertial forward-backward algorithms for solving constrained minimization problems. We then prove convergence theorems under mild conditions. Finally, we provide numerical experiments on image restoration problem and image inpainting problem. The numerical results show that the proposed algorithms have more efficient than known algorithms introduced in the literature.

基于改进凸内逼近法的主动配电网有功-无功协调优化

以风电、光伏为代表的分布式电源接入配电网后容易导致系统电压波动变大以及局部电压越限。以二阶锥优化为代表的松弛技术在优化时为了保证松弛后解的精确,约束条件极为严苛并且在功率的极端注入下容易导致对偶间隙增大。针对上述问题,该文提出基于改进凸内逼近法的主动配电网有功-无功优化方法。首先,基于支路潮流方程定义与支路电流、节点电压和视在功率流相关的非线性项的凸包,并与剩余线性元素结合形成凸内部近似,建立完善的数学模型;进一步提出网络容许性判据以及引入KKT条件收缩最优解的对偶间隙。最后,基于IEEE 33系统及PG&E69节点系统,利用Yalmip等平台求得电网中各有功、无功决策变量的出力区间,验证所提方法的稳定、精确与高效性。

基于凸型线圈双向电磁力加载的管件电磁翻边成形

传统线圈电磁力单一导致管件翻边角度不佳。本文提出采用凸型线圈管件翻边的方法,通过设计新型线圈,同时为管件翻边提供双向电磁力。建立了两组模型,分别采用传统线圈和凸型线圈驱动管件发生电磁翻边成形,探讨分析了两组管件模型翻边成形过程中的电磁力矢量以及变形速率的变化。结果表明,凸型线圈加载管件翻边时提供的双向电磁力极大地提高了管件变形的流动性,从而提高了翻边角度。此外,相同放电参数下基于凸型线圈的管件翻边角度较传统线圈提高了1.25倍。显然,新型线圈能够在一定程度上改善管件电磁翻边的质量问题,为电磁翻边成形的工业化应用提供更多可能。

计及UPFC最优配置的电力系统鲁棒调度协同优化策略

统一潮流控制器(UPFC)应用于潮流调控时,计及UPFC调控参数的交流潮流计算是非凸、非线性问题,且多台装置间的非线性交叉耦合特性也会直接影响优化配置方案。为此,基于UPFC的潮流调控特性,构建了计及UPFC的松弛型交流潮流二阶锥规划模型;计及风电的不确定性,协同考虑UPFC的规划和电力系统的调度问题,建立了计及UPFC最优配置的电力系统鲁棒协同优化模型,并采用列和约束生成算法进行求解。以IEEE RTS-24节点系统为算例进行仿真分析,结果表明所提协同优化策略有效提升了UPFC配置方案的适应性,提高了系统运行经济性和风电消纳能力,增强了系统运行调控的灵活性。

交错凸齿式宽苗带小麦精量排种器设计与试验

针对外槽轮式小麦宽苗带排种器排量不稳定和苗带内种子分布均匀性较差的问题,该研究设计了一种交错凸齿式宽苗带小麦精量排种器。通过连续充种分析和排量计算,确定凸齿高度和凸齿角度是影响排量一致性和排种均匀性的关键参数。应用离散元法对上述关键参数进行中心旋转组合仿真试验,结果表明,对排量一致性、排种均匀性影响显著性程度由大到小的因素分别依次为凸齿角、凸齿高、作业速度,且均具有交互影响。借助响应面分析,得出凸齿高5 mm、凸齿角75°时的排量一致性和排种均匀性较优,平均变异系数分别为2.27%和7.61%。对该参数组合排种器进行样机试制,并进行台架试验,台架试验结果表明,排种一致性和均匀性变异系数与仿真值误差均低于5%,说明仿真优化结果可靠、准确。田间对比试验结果表明,播量120、150和180 kg/hm~2时,交错凸齿式宽苗带小麦精量排种器的播量一致性、纵向播种均匀性和横向播种均匀性变异系数分别较外槽轮式排种器降低0.99、3.01和9.38个百分点,满足小麦宽苗带播种农艺要求。研究结果可为提高排种均匀性的小麦排种装置设计提供参考。

基于非凸与不可分离正则化算法的电容层析成像图像重建

搅拌器内两相混合是化工生产中常见的现象,电容层析成像(ECT)技术主要对两相分布进行可视化重构,以达到监测的目的。受稀疏贝叶斯学习的启发,提出了一种非凸与不可分离正则化(NNR)算法重建ECT图像。在稀疏先验的基础上引入矩阵低秩特性,采用最大后验估计在潜在空间中提出一个新的优化问题,利用对偶变量将潜在空间的目标函数映射到原始空间进行迭代求解,用来恢复同时稀疏与低秩的矩阵。与凸近似L1范数相比,NNR算法可获得更准确的重建图像,同时比非凸可分离方法更容易收敛到全局最优解。为验证NNR算法的重建效果,通过数值仿真与静态实验的方法分别与其他5种算法进行重建对比。结果表明:NNR算法可以有效减少重建伪影,提升中心物体的重建质量,为搅拌器内两相分布提供了高质量的重建算法。

Drag Coefficient of a Non-Convex Polygonal Plate during Free Fall

Waterside creatures or aquatic organisms use a fin or web to generate a thrust force. These fins or webs have a non-convex section, referred to as a non-convex shape. We investigate the drag force acting on a non-convex plate during unsteady motion. We perform the experiment in a water tank during free fall. We fabricate the non-convex plate by cutting isosceles triangles from the side of a convex hexagonal plate. The base angle of the triangle is between 0° to 45°. The base angle is 0 indicates the convex hexagonal thin plate. We estimate the drag coefficient with the force balance acting on the model based on the image analysis technique. The results indicate that increasing the base angle by more than 30° increased the drag coefficient. The drag coefficient during unsteady motion changed with the growth of the vortex behind the model. The vortex has small vortices in the shear layer, which is related to the Kelvin-Helmholtz instabilities.

基于空间稀疏先验的冲击载荷识别频域非凸稀疏正则化方法

复合材料因其强度高、刚度高、密度小等优点而广泛应用于航空、航天等领域。但由于其抗冲击性差,监测作用于复合材料结构上的冲击载荷对于结构快速检测损伤十分重要。经典的Tikhonov正则化方法在欠定情况下求解载荷识别问题时容易在载荷非加载区识别出虚假力;近年来兴起的L1范数稀疏正则化方法在识别冲击载荷时常低估载荷的幅值。为了突破这些方法的局限以实现更高精度的冲击载荷识别,该研究基于冲击载荷的空间稀疏先验,提出一种新的冲击载荷识别频域非凸稀疏正则化方法。所提出的方法结合了广义极小极大凹惩罚项的非凸优势以及非凸保凸的特性,利用向前向后分裂算法进行凸优化求解,既避免了非凸优化容易收敛到局部最优解的问题,又促进了解的稀疏。分别在复合材料梁和复合材料层合板上开展了冲击载荷试验验证,试验结果表明,无论在正定还是欠定的情况下,所提出方法能在精准定位冲击位置的同时重构冲击载荷的时间历程,且该方法在促进解稀疏和识别载荷幅值方面的表现都优于L1正则化方法,其中幅值识别精度能比L1正则化提升50%以上。

硬件损伤条件下无人机辅助的NOMA-IRS网络资源分配算法

探讨了在硬件损伤条件下,如何通过搭载在无人机上的智能反射面(IRS)有效支持基于非正交多址接入(NOMA)技术的网络,以加快多用户数据的传输速率。提出了一种全面优化策略实现整个通信系统的最大传输速率,包括联合调整串行干扰消除的解码策略、IRS的反射配置、无人机的空间位置以及基站的发射功率。由于该问题是一个非凸问题,提出使用块坐标下降方法来实现优化的一种迭代算法,将原始的非凸问题细分为3个子问题,并通过结合惩罚函数法、半正定松弛技术和连续凸近似法来解决这些子问题。仿真结果表明:提出的算法在系统总速率方面相比随机部署无人机、未使用IRS辅助的NOMA策略,系统速率有显著提升。

硫酸盐对混凝土侵蚀过程的细观数值分析

硫酸盐侵蚀作为混凝土耐久性损伤的一个重要方面,日益受到人们的普遍关注。根据Fick第二定律和化学反应动力方程,建立了细观层面硫酸盐对混凝土侵蚀过程的数值分析方法。以混凝土随机凸多边形骨料模型为基础,利用Matlab程序对有限元软件进行二次开发,建立了基于扩散-化学反应的硫酸盐对混凝土侵蚀过程的细观数值分析方法,并与试验结果进行了对比。结果表明:硫酸盐侵蚀过程细观数值方法得到的模拟结果与试验结果吻合较好,可以有效模拟硫酸盐对混凝土的侵蚀过程;距混凝土表面一定深度范围内,SO_(4)^(2-)浓度随表面SO_(4)^(2-)浓度的提高而增加;砂浆中SO_(4)^(2-)扩散系数是影响混凝土内SO_(4)^(2-)最大侵蚀深度的主要因素;界面过渡区厚度对硫酸盐环境中混凝土损伤的影响较小。

非完美信道状态信息下分布式智能反射面辅助安全通信研究

针对非完美信道状态信息(CSI)下分布式智能反射面(RIS)安全通信问题,该文构建基于基站波束成形、人工噪声(AN)和RISs相移的联合优化问题,并提出相对应优化方法和1维线性搜索的有效算法来求解所构建的非凸优化方程。仿真结果表明:相对于随机相位、无AN辅助的安全传输策略,所提方法在非完美CSI场景可取得更高的安全传输速率;在总反射单元数目固定情况下,分布单元数目越多,所提算法优越性越明显;进一步,所提算法具有更强的鲁棒性,即本策略能更好地适应信道不确定性。

多电压等级配电系统智能软开关协同配置

配电网逐步发展成为光伏、电动汽车等新型源荷的主要承载平台,面临的电压越限和线路过载等问题逐步加剧。柔性配电装置具有良好的调控能力,成为提高配电网运行灵活性的有效手段。已有的柔性化升级主要面向中压或低压配电网,多电压等级配电网柔性互联的潜力被忽视。因此,该文开展多电压等级配电系统智能软开关协同配置方法研究。首先,提出多电压等级配电系统智能软开关协同配置策略;其次,在计及源荷不确定性影响下,考虑源荷典型场景的概率化波动,建立多电压等级配电系统智能软开关协同配置模型。最后,为实现大规模优化配置模型的可靠收敛,采用凸差规划算法进行求解。选取实际配电网算例对优化配置模型和求解算法进行验证,结果表明,所提方法可以有效解决多电压等级配电系统智能软开关协同配置问题,支撑配电网承载高比例新型源荷,在提高系统运行安全性的同时具有更好的经济效益。

直角凸壁面附近非对称位置的空泡动力学行为实验研究

空化破坏现象在核电厂中广泛存在。为了更深入地揭示空化破坏的机理,本文借助高速摄影实验系统,研究了直角凸壁面附近非对称位置空泡的动力学行为。具体分析了空泡的轮廓变形,形心的移动距离和方向,以及空泡射流的方向随着空泡与壁面相对位置d、h的变化规律。本文主要结论如下:(1)空泡的变形与空泡和固体壁面的相对位置d、h有关。随着空泡与右壁面的距离d的增大,空泡的非对称性越来越弱。随着空泡与上壁面的距离h的增大,在整个空泡的动力学过程中空泡的非球形特征逐渐减弱。(2)在空泡的溃灭和再生长过程中,空泡形心会持续地向左下方移动,且形心向左移动的距离随着d和h的增大而明显减小。(3)当空泡与上壁面的距离h适当时,会产生明显的斜向左下方的射流现象,且射流方向角θ随着d的增大而增大。

一种基于流形的机械臂动作构型知识压缩表达方法

针对在机械臂分拣任务中,存在物体形状各异、大小不一、训练神经网络成本过高的问题,提出一种基于流形空间的机械臂快速分拣方法。通过自主设计的一款简易实验装置模拟代替机械臂进行实验。对高维数据进行压缩,结合三维快速凸包求解算法,对体积大小不同的同类物体的流形空间进行分割,以凸包形式将稳定性较高的点集包裹起来。实验结果表明,体积大小不同的同类物体的高稳定流形子空间是一致的。该方法可以通过对一种物体的流形子结构进行尺度放缩,得到不同大小的同类物体的高稳定分拣区域,用于生成高效、可靠的机械臂分拣任务中的6D位姿构型,以提高分拣作业的工作效率。