A flexible multiscale algorithm based on an improved smoothed particle hydrodynamics method for complex viscoelastic flows

Viscoelastic flows play an important role in numerous engineering fields,and the multiscale algorithms for simulating viscoelastic flows have received significant attention in order to deepen our understanding of the nonlinear dynamic behaviors of viscoelastic fluids.However,traditional grid-based multiscale methods are confined to simple viscoelastic flows with short relaxation time,and there is a lack of uniform multiscale scheme available for coupling different solvers in the simulations of viscoelastic fluids.In this paper,a universal multiscale method coupling an improved smoothed particle hydrodynamics(SPH)and multiscale universal interface(MUI)library is presented for viscoelastic flows.The proposed multiscale method builds on an improved SPH method and leverages the MUI library to facilitate the exchange of information among different solvers in the overlapping domain.We test the capability and flexibility of the presented multiscale method to deal with complex viscoelastic flows by solving different multiscale problems of viscoelastic flows.In the first example,the simulation of a viscoelastic Poiseuille flow is carried out by two coupled improved SPH methods with different spatial resolutions.The effects of exchanging different physical quantities on the numerical results in both the upper and lower domains are also investigated as well as the absolute errors in the overlapping domain.In the second example,the complex Wannier flow with different Weissenberg numbers is further simulated by two improved SPH methods and coupling the improved SPH method and the dissipative particle dynamics(DPD)method.The numerical results show that the physical quantities for viscoelastic flows obtained by the presented multiscale method are in consistence with those obtained by a single solver in the overlapping domain.Moreover,transferring different physical quantities has an important effect on the numerical results.

A Control Strategy for Smoothing Active Power Fluctuation of Wind Farm with Flywheel Energy Storage System Based on Improved Wind Power Prediction Algorithm

The fluctuation of active power output of wind farm has many negative impacts on large-scale wind power integration into power grid. In this paper, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm to realize smooth control of wind power output. Based on improved wind power prediction algorithm and wind speed-power curve modeling, a new smooth control strategy with the FESS was proposed. The requirement of power system dispatch for wind power prediction and flywheel rotor speed limit were taken into consideration during the process. While smoothing the wind power fluctuation, FESS can track short-term planned output of wind farm. It was demonstrated by quantitative analysis of simulation results that the proposed control strategy can smooth the active power fluctuation of wind farm effectively and thereby improve power quality of the power grid.

Dynamic grouping control of electric vehicles based on improved k-means algorithm for wind power fluctuations suppression

To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.

Improved Model for Soil as a Two-Phase Mixture Based on Smoothed Particle Hydrodynamics (SPH)

It is desired to resolve soil contamination with reduced costs. “Insoluble treatment” is a soil improvement method for heavy metal containing soil, which uses soil mixers to mix soil and soil improvement liquid agents. To reduce the costs of this method, soil mixers have to be optimized. However, it is not achieved due to the lack of theoretical knowledge on mixing solid with liquid. Therefore, a numerical model to simulate the dynamic behavior of solid and liquid is on the development in this study using Smoothed Particle Hydrodynamics (SPH) method. To validate the numerical model, several experiments were carried out and numerically reproduced. The comparisons of the results showed that the numerical model replicated a liquid flow with an error rate of 2.1% and a seepage flow with an error rate up to 26.1%. Especially, the water distribution in the soil pores was highly improved with absolute gaps in volumetric water content up to 4.4% in the porosity range of 10% - 90%. For the water absorption into dry sand, the simulation result became more realistic by concerning soil suction.

Quality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation

The concept of optimal Delaunay triangulation (ODT) and the corresponding error-based quality metric are first introduced. Then one kind of mesh smoothing algorithm for tetrahedral mesh based on the concept of ODT is examined. With regard to its problem of possible producing illegal elements, this paper proposes a modified smoothing scheme with a constrained optimization model for tetrahedral mesh quality improvement. The constrained optimization model is converted to an unconstrained one and then solved by integrating chaos search and BFGS (Broyden-Fletcher-Goldfarb-Shanno) algorithm efficiently. Quality improvement for tetrahedral mesh is finally achieved by alternately applying the presented smoothing scheme and re-triangulation. Some testing examples are given to demonstrate the effectiveness of the proposed approach.

基于改进蚁群算法的机器人全局路径规划

针对传统蚁群算法存在初始信息素缺乏、收敛速度慢以及无法有效躲避障碍物等问题,文中提出了一种基于改进蚁群算法的全局路径规划。引入正态分布函数改进传统启发函数,提高了算法效率,缩短了算法收敛所需时间。自适应调整信息素挥发系数,限定信息素范围,避免过早收敛。对算法路径平滑处理,缩短路径长度,从而实现机器人的全局路径规划。仿真结果表明,在20×20环境下,文中算法平均迭代次数比传统蚁群算法减少了28代,收敛速度更快。平均拐点减少了33.3%,使路径更为平滑,克服了初始信息素缺乏,加快了收敛速度,减少了拐点数量,能够有效躲避环境中的障碍物,证明了该算法的可行性。

基于二次转角约束的改进RRT路径规划算法研究

针对快速随机搜索树(RRT)算法存在节点扩展冗余、生成路径不满足车辆转角条件等问题,提出一种改进的二次转角约束RRT算法。首先,在传统RRT算法基础上对采样空间进行裁剪,引入目标导向策略减少采样时间;然后采用车辆膨胀处理和直线方法检测障碍物,并引入第一次转角约束得到粗解路径;接着对粗解路径建立二次转角约束并进行优化处理,获取优化路径后拟合,并进行仿真验证。结果表明,相比于引入目标导向策略的RRT算法,所提出的算法路径最大曲率降低了34.33%,平均曲率降低47.36%,扩展节点数降低47.62%,路径距离降低7.76%,规划时间缩短14.98%。

基于活动性检测动态估计噪声的心音降噪算法

针对基于小波分解和最优改进对数幅度谱估计的心音降噪算法存在噪声残留和心音失真的问题,提出一种基于心音活动性检测(HSAD)动态估计噪声的心音降噪算法。通过设计的HSAD判断当前心音帧是否为基础心音帧(FHS),根据判断结果分别采用改进最小值控制递归平均(IMCRA)算法和递归平滑算法对噪声功率进行动态估计与更新,采用非因果先验信噪比,实现心音信号的降噪。实验结果表明,提出算法能更好在提升降噪性能的同时,降低FHS的失真。

基于RRT算法的移动机器人安全光滑路径生成

在多障碍物复杂工厂环境中,针对快速探索随机树算法(RRT)生成的路径存在冗余点、贴近障碍物且存在锯齿状转折的问题,改进得到了安全-光滑RRT(Safe-SmoothRRT)路径规划算法。首先,引入目标偏置策略;其次,该算法利用融合目标点引力思想的新节点扩展方式以及改进的近邻点度量策略以减少树的盲目扩展,提高生长的目标性;随后,引入节点安全约束,将安全节点加入树中;改进路径简化方法,剔除冗余点的同时兼顾了安全性;最后通过B样条局部平滑来改善路径的平滑性。在MATLAB仿真实验中分别与标准RRT算法、自适应目标偏向性RRT算法和改进RRT算法相比,在平均路径长度方面最大下降了7.1%,在平均有效节点数方面最大下降了64.1%,且所得路径始终与障碍物保持一定的安全距离,结果表明改进算法有效提升了路径的光滑性和安全性。

三端口柔性多状态开关多模式平滑切换控制策略

光伏整县推进和电动汽车快速发展造成配电网末端电压偏高等电能质量问题,基于区域柔性互联的柔性多状态开关(flexible multi-state switch,FMSS)技术成为解决方案之一。针对柔性多状态开关PQ模式与VF模式间切换的波动及冲击性问题,提出在状态跟随控制器之后添加惯性环节,并改进相位预同步环节,可实现FMSS并离网工作模式的平滑切换。针对FMSS直流母线控制端的馈线故障导致系统运行崩溃问题,提出一种引入权值调节的控制策略,可实现系统稳定运行情况下,有功控制和直流母线电压控制的平滑切换。在MATLAB/Simulink环境下搭建了三端口FMSS仿真模型,对提出的控制策略进行了仿真验证,仿真结果实现了任意馈线故障下三端口FMSS无缝转供电功能。最后搭建物理实验平台,进一步验证了所提平滑切换策略的有效性。

基于自学习Pauta和Smooth的地下水位异常值检测和平滑处理方法

地下水监测主要通过自动化监测设备对地下水位进行监测,从而获得随时间变化的水位曲线.目前的自动化监测设备采集的水位数据中存在很多异常值,会影响正常的决策判断.针对此问题,提出将自学习算法融入到奇异值剔除—拉依达准则中,用于异常值的检测,将其应用于地下水位数据的平滑处理中,通过对内蒙古某地采集的水位数据进行平滑处理验证,表明本文方法能够有效剔除水位数据中的异常值,而且不会影响曲线的整体趋势走向,效果良好.

基于深度强化学习的船舶路径规划方法研究

针对现有路径规划算法在面对复杂环境时需要大量先验信息,并存在计算量大、转折过多、搜索精准度差等问题,使用深度强化学习算法可以弥补上述缺陷,但是存在算法本身收敛慢等问题。针对此问题,提出使用改进人工势场法(APF)对深度强化学习算法的奖励函数进行优化处理,并通过贝塞尔曲线对路径进行平滑处理,最终输出相对平滑的船舶航行路径。在相同环境下,将改进算法模型与现有方法的路径规划效果进行比较分析,结果表明,DQN-APF算法在生成的路径长度、平滑度、规划完成时间等船舶路径综合规划参数能力上得到了提升。

MFCDD优化三次样条平滑算法在继电器数据插值中的应用

继电器参数众多,并且对各参数的测量方式和测量间隔不同,释放电压等参数相较于时间参数等实时测量参数,数据量较少,在进行相关分析时会造成结果精度较差的情况。提出一种形态波动一致性偏移距离(MFCDD)优化的平滑指标改进三次样条插值算法。引入平滑指标改进,对数据序列相关点的方差贡献率及单点平滑度进行分析,确定数据序列的平滑点及波动点;采用三次指数平滑对三次样条算法进行改进,确定改进后的插值表达式;引入形态波动一致性偏移距离对插值间隔进行确定,完成数据扩充。采用继电器吸合电压参数和释放电压参数对上述方法进行验证,结果表明上述方法对数据扩充具有较好的准确性。

基于PCISPH的流体粒子飞溅改进方法

流体飞溅是自然界中最常见的流体现象。流体模拟是计算机图形学的一个重要研究分支。流体模拟已经广泛应用于电影、游戏和其他工业数值领域。由于飞溅场景中流体的密度和压力的速率变化非常大,因此模拟对离散化解的精度要求很高。对于流体粒子飞溅模拟数值不稳定,且缺乏真实效果,针对经典的预测校正不可压缩SPH(PCISPH),该文提出了基于粒子表面流体飞溅改进的泊松压力解的方法,通过替换压力源项提高了模拟精度。实验结果表明,该方法中流体的压力分布较之经典方法更接近现实的流体粒子飞溅模拟效果,并且改进后的方法经过剧烈运动后帧率仍符合实时性仿真效果的要求,保证了良好的压力稳定性和真实感。该文通过Anaconda3集成Python3和Taichi环境实现流体仿真实验。

复杂异型建筑立面测绘轮廓提取方法设计

为解决点云数据密度异常时复杂异型建筑立面测绘轮廓提取精度变差的问题,提出基于局部点云密度的复杂异型建筑立面测绘轮廓提取方法。引入基于平面投影和双边滤波的测绘点云数据平滑方法,对测绘数据进行去噪和平滑处理,并通过点云分割方法提取目标点云区域。通过基于改进Alpha Shapes算法的立面测绘轮廓提取方法,以边界网格筛选的方式,去除目标点云区域冗余点云数据后,使用滚动圆半径自适应调节方法提取轮廓数据。试验结果表明,所提取轮廓匹配度高达95.08%,具有良好的精度和可行性。该方法可在有效平滑点云数据、分割获取目标点云区域的同时,高精度提取复杂异型建筑立面测绘轮廓。

Optimization of buckling load for laminated composite plates using adaptive Kriging-improved PSO:A novel hybrid intelligent method

An effective hybrid optimization method is proposed by integrating an adaptive Kriging(A-Kriging)into an improved partial swarm optimization algorithm(IPSO)to give a so-called A-Kriging-IPSO for maximizing the buckling load of laminated composite plates(LCPs)under uniaxial and biaxial compressions.In this method,a novel iterative adaptive Kriging model,which is structured using two training sample sets as active and adaptive points,is utilized to directly predict the buckling load of the LCPs and to improve the efficiency of the optimization process.The active points are selected from the initial data set while the adaptive points are generated using the radial random-based convex samples.The cell-based smoothed discrete shear gap method(CS-DSG3)is employed to analyze the buckling behavior of the LCPs to provide the response of adaptive and input data sets.The buckling load of the LCPs is maximized by utilizing the IPSO algorithm.To demonstrate the efficiency and accuracy of the proposed methodology,the LCPs with different layers(2,3,4,and 10 layers),boundary conditions,aspect ratios and load patterns(biaxial and uniaxial loads)are investigated.The results obtained by proposed method are in good agreement with the literature results,but with less computational burden.By applying adaptive radial Kriging model,the accurate optimal resultsebased predictions of the buckling load are obtained for the studied LCPs.

Three-dimension path planning for UAV using improved A＊ algorithm in complicated threat environment

In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.

Improving the Quality of Conforming Triangular Meshes by Topological Clean up and DSI

A new method as a post-processing step is presented to improve the shape quality of triangular meshes, which uses a topological clean up procedure and discrete smoothing interpolate (DSI) algorithm together. This method can improve the angle distribution of mesh element. while keeping the resulting meshes conform to the predefined constraints which are inputted as a PSLG.

基于改进A^(*)算法融合角度信息的船舶路径规划

为解决传统A^(*)算法在施工水域对船舶进行路径规划时搜索节点多、拐点多、节点拓展方向范围广等问题,提出一种基于改进A^(*)算法融合角度信息的路径规划方法。首先,定义加权因子,将其引入A^(*)算法的启发函数中,以此提高路径规划的效率;其次,引入角度信息,诱导搜索节点分布在起始点到目标点的连线附近;最后,添加转弯修正代价参数,并对路径进行二次优化,提高路径平滑性。实验结果表明,该方法在简单环境下的搜索时间能缩短45.8%,在复杂环境下的搜索时间能缩短63%,并且能够有效剔除冗余节点,使路径变得更加平滑。

风电波动平抑下考虑SOC均衡及收益的电池储能功率分配策略

针对电池储能(battery energy storage system,BESS)平抑风电波动过程中电池单元荷电状态(state of charge,SOC)均衡性较差且未考虑风储净收益的问题,提出了风电波动平抑下考虑SOC均衡及收益的BESS功率分配策略。首先,建立综合考虑售电收益、弃风惩罚、缺电惩罚及BESS运行成本等多个因素的风电并网指令优化模型,以并网指令波动率、电池组SOC标准差等多个因素为约束条件,提出改进算术优化算法(improved arithmetic optimization algorithm,IAOA)求解该优化模型。然后,将BESS划分为两个电池组,设计了BESS双层功率分配方法(double-layer power allocation method,DPAM),上层将BESS充放电指令分配给两个电池组,下层根据最大充放电功率原则或新型SOC均衡原则将电池组充放电指令分配给各自的电池单元。最后,通过仿真对所提策略进行了验证。仿真结果表明:IAOA加快了寻优速度,提高了寻优精度;DPAM提升了电池组内电池单元SOC的均衡速度,改善了均衡程度;提出的功率分配策略进一步降低了风电并网波动率,同时提高了风储系统净收益。