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.

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.

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 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.

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。

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.

Sub-Differential Characterizations of Non-Smooth Lower Semi-Continuous Pseudo-Convex Functions on Real Banach Spaces

In this paper, we characterize lower semi-continuous pseudo-convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the pseudo-monotonicity of its Clarke-Rockafellar Sub-differential. We extend the results on the characterizations of non-smooth convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the monotonicity of its sub-differentials to the lower semi-continuous pseudo-convex functions on real Banach spaces.

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。

基于Transformer复杂运动辨识的机动星凸形扩展目标跟踪方法

针对复杂的机动扩展目标跟踪问题,利用Transformer网络设计了一种有效的星凸不规则形状机动扩展目标跟踪方法。首先,该文研究利用alpha-shape算法建立了星凸形状的变化模型,实现了静态场景下的星凸形扩展目标的形状估计。然后,通过对目标状态转移矩阵进行重新设计,结合Transformer网络对机动扩展目标运动状态转移矩阵进行实时估计,实现了对复杂机动目标运动过程的精准跟踪。进一步地,将估计得到的形状轮廓与运动状态进行融合,最终实现了对星凸形机动扩展目标的实时跟踪。最后,通过构造复杂的机动扩展目标跟踪场景,利用多重性能指标测试算法对形状和运动状态的综合估计性能,验证了算法的有效性。

脱萼剂对“浙梨6号”果实品质与着果率的影响

针对“浙梨6号”因部分萼片宿存或残存、果顶尖凸等而影响果实品相问题,选择PBO、氟硅唑、丙环唑3种脱萼剂,以清水为对照进行试验。结果表明:与对照相比,3种脱萼剂处理果实的脱萼率提高23.27~26.01百分点,果顶尖凸率降低24.55~26.44百分点,扁圆果占比、单果质量、可溶性固形物含量分别增加33.19~37.66百分点、37.9~57.1 g和0.68~0.94百分点,但果实偏斜度、全锈果率分别偏高0.54~0.74和18.36~19.23百分点,端正果率、着果率分别下降15.89~21.07和5.43~6.62百分点,差异达显著或极显著水平。上述3种脱萼剂分别选择4000、333.3、444.4 mg·L^(-1)和花序分离期进行喷施,在保证脱萼防凸效果的同时,可有效降低对着果率及果形端正度等的不利影响。

一种结构不确定分析的改进多维平行六面体模型

多维平行六面体模型是一种能够同时考虑相关变量和独立变量的非概率凸集模型,更适用于工程结构中常见的多源不确定性问题。为更加有效合理地度量结构不确定性,提出一种改进多维平行六面体模型。通过定义区间变量的相关角和边缘区间,给出模型不确定域的显式表达式,进而给出依据实验样本点构建多维平行六面体模型的方法。3个算例分析结果表明,改进多维平行六面体模型能够较好地反映区间变量之间的相关性,是一种比传统多维平行六面体模型更为紧凑合理的模型。

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。

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。

以凸面蛛网膜下腔出血为影像特征的脑淀粉样血管病临床特点分析

目的:探讨以急性凸面蛛网膜下腔出血(convexity subarachnoid hemorrhage,cSAH为影像特征的脑淀粉样血管病(cerebral amyloid angiopathy,CAA)的临床和影像学特点,及与患者脑出血再发的风险相关性。方法:回顾性分析2013年6月至2020年12月,北京安贞医院就诊的以cSAH为特征合改良Boston诊断标准的18例很可能的CAA患者,分析其流行病学资料、临床特点、头颅CT/头颅磁共振成像(magnetic resonance imaging,MRI)等信息。结果:18例患者男女比例为1:1.25,发病年龄59~91岁,平均(75±9)岁,最常见的临床症状为短暂性局灶性神经系统症状发作(transient focal neurological episodes,TFNE,12/18),头颅影像学表现为局限型(14/18)和弥漫型c SAH(4/18)。随访15个月,平均(15±5)个月,8例患者出现反复TFNE发作,4例再发c SAH,4例脑出血。结论:以cSAH为特征的CAA多见于老年人,TFNE为最常见的临床表现,头颅CT/MRI是最重要的诊断方法,应尽量避免抗栓治疗。

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。

天津滨海地热田北部深部地热资源赋存规律

【研究目的】天津地热资源丰富,目前已开发的深部地热资源大部分位于“隆中凸”构造区域,而位于“坳中凸”构造区域的地热资源勘查和研究程度基本尚属空白,揭示其深部地热赋存规律可为滨海新区及京津冀地区寻找深部地热资源及勘探与开发提供重要参考。【研究方法】本文以黄骅坳陷宁河凸起中的桥沽地区为研究区,以近期新发现的资源禀赋最好的蓟县系雾迷山组热储层为研究对象,通过分析区域地质资料、大地电磁测深(MT)、钻孔测温和物探测井等资料,系统总结了研究区地质构造、地温场和深部地热资源赋存特征。【研究结果】雾迷山组储层的热储温度高(90~120℃),出水量大于100 m^(3)/h,埋藏相对较浅(2200~2800 m)。区内地质构造条件复杂,断裂构造发育,汉沽断裂为研究区重要的导热、导水通道;地温场呈现“两高夹一低”展布特征与两处背斜构造空间位置相对应;热源以壳源热为主、幔源热次之,大气降水为主要热水来源,热传输机制以热传导型为主。【结论】综合研究区深部地热赋存规律,建立了深部地热资源概念模型,明确了“坳中凸”深部地热找矿新思路。

由Hermite-Hadamard不等式的一个推广形式所生成的不等式

考虑由一个推广的Hermite-Hadamard不等式的右边部分的连续加细所生成的两个差函数.引入参数求最值的方法,在Lipschitz条件下给出了关于这两个差函数的不等式.