Lumped Time Distribution Function of Dynamic Equilibrium System and Its Application in Calculating Molecular Weight Distribution of Polymer

The lumped time distribution functions were proposed, which can be used for describing the dynamicsystems with two or more than two states of the end of growing polymer chain during chain addition polymerization.Numerical analysis of the lumped time distribution functions was carried out. The method for calculating molecularweight distribution of polymer in the stable free radical polymerization and more general cases was developed basedon the lumped time distribution functions.

Space-time Dynamics of Dendroctonus valens Population in China and Spatial Sampling Technique based on Its Spatial Distribution Pattern

Red turpentine beetle （RTB）, Dendroctongs valens LeConte, is a destructive forest invasive species in China, it mainly attacks Pings tabuliformis and P. bungeana. So far it has spread rapidly to the provinces of Shanxi, Hebei, Henan, Shanxi and Beijing since its first outbreak in Shanxi Province in 1998, and has caused extensive tree mortality. Space-time dynamics of D. valens population and spatial sampling technique based on its spatial distribution pattern were ana- lyzed using geostatistical methods in the pure P. tabuliforis forests and mixedwood stands which were at different damage levels. According to the spatial distribu- tion of D. valeas population, the specific spatial sampling technique was also studied, and then was compared with traditional sampling technique. The spatial sam- piing technique combined with sampling theory and the biological characteristics of D. valens population, which not only could calcnlate the error of the sampling, but also could discuss the optimal sampling number and the optimum size of plot according to different damage levels and different stand types. This helps to explain population expansion and colonization mechanism of D. valens, and to provide a good reference for adopting snitable control measures.

THEORETICAL INVESTIGATION ON STATE OF LOAD DISTRIBUTION AMONG CONTACT BEARINGS OF DOUBLE CIRCULAR ARC HELICAL GEARS

A dynamic analysis approcach to investigate the state of load distribution among contact bearings of double circular are belical gears is proposed and a computer program is developed for calculating the factor of iced distribution based on the theory of W-N gears. The changing situations of load distribution among contact bearings of the gears influenced by main issues are analyzed by a series of parametric studies.

Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays

Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

Time History Dynamic Analysis of a New Constructed Offshore Jacket Platform in Persian Gulf Due to Random Waves

API RP2AWSD is a design code in practice for design of jacket platforms in the Persian Gulf but is based on the Gulf of Mexico environmental condition. So for the sake of using this code for the Persian Gulf, it is better to perform a calibration based on this specific region. Analysis and design of jacket platforms based on API code are performed in a static manner and dynamic analysis is not recommended for such structures. Regarding the fact that the real behavior of the offshore jacket platforms is a dynamic behavior, so in this research, dynamic analysis for an offshore jacket platform in the Persian Gulf under extreme environmental condition is performed using random time domain method. Therefore, a new constructed offshore jacket platform in the Persian Gulf is selected and analyzed. Fifteen, 1-h storm, simulations for the water surface elevation is produced to capture the statistical properties of extreme sea condition. Time series of base shear and overturning moment are derived from both dynamic and static responses. By calculating the maximum dynamic amplification factor (DAF) from each simulation and fitting the collected data to Weibull distribution, the most probable maximum extreme (MPME) value for the DAF is achieved. Results show that a realistic value for DAF for this specific platform is 1.06, which is a notable value and is recommended to take into practice in design of fixed jacket platform in the Persian Gulf.

远郊大型冬季活动客流演进及路径分流研究

有效的客流组织是保证大型活动成功举办的关键,通过大型冬季活动的客流特征及意向调查,建立了观众路径选择模型和客流动态演进模型,分析了大型活动各设施节点的客流分布和客流排队时间分布动态变化规律。结果表明:增加取暖房、纪念品店、景观点等设施将提升观众在远郊大型冬季活动中的观赛体验。大型冬季活动的观众可接受的安检/检票、等公交的排队时间及步行到场馆的时间心理阈值为20 min,且观众更愿意选择步行时间短和服务设施数量多的路径;采用路径分流并提供路径实时信息,会使得分流路径上、下游节点的客流分布更为均衡平缓,有效减少客流聚集和长时间排队等待现象。

带有动态到达工件的分布式柔性作业车间调度问题研究

分布式柔性作业车间调度是生产调度的1个重要分支,工件的动态到达作为实际生产中的1种常见扰动情况,进一步增加了作业车间调度问题的复杂性和不确定性。针对带有工件动态到达的分布式柔性作业车间调度问题(DA-DFJSP),提出1种分批调度策略,将原本的动态调度问题转化成一系列连续调度区间上的静态调度问题,构建以最大完工时间为优化目标的混合整数规划模型;在此基础上,结合问题特征采用批次、工厂、工序、机器的4层染色体编码及快速贪婪搜索插入的解码方式改进遗传算法,同时引入多种交叉、变异算子来增强染色体的多样性;最后,基于FJSP标准算例构建DA-DFJSP测试算例进行仿真对比实验,验证所提策略和改进算法的求解优势。结果表明:相较于传统的重调度策略和改进前的遗传算法,采用分批调度策略和改进的遗传算法(IGA)所求调度方案具有更短的完工周期、更均匀的工厂加工负荷及更高的设备工作效率,IGA与分批调度策略之间有高度的契合性,能够有效提升生产效率。

基于RPA与滚动时间窗的零售电商订单动态调度仿真

为了提高零售电商订单的整体交付效率,提出基于RPA与滚动时间窗的零售电商订单动态调度方法。在RPA机器人技术框架的应用层逻辑端中,通过基于滚动时间窗的订单调度优先级排序方法,将订单以滚动时间窗划分的方式,分解为多个订单调度任务,并执行订单优先级排序。将排序后订单作为零售电商订单拣选与配送车辆联合动态调度方法的调度对象,构建订单交付时间最小化、全部订单均被交付的订单动态调度目标函数。由改进共同进化遗传算法,从订单拣选、配送车辆联合动态调度的角度,求解满足条件的订单拣选与配送车辆联合动态调度方案。实验验证,此方法调度下,零售电商客户订单配送交付时,交付时间均靠近客户对订单产品期望时间窗下界,无订单遗漏问题,全部订单均被高效拣选、配送。

新能源电力系统频率时空分布特性分析

随着新能源和电力电子装备在电力系统中的占比快速提升,系统的频率动态特性发生重大变化。为了研究新能源机组并网对新型电力系统频率时空分布特性的影响:首先,建立了新能源电力系统的频率动态响应解析模型,并分析了频率时空分布特性的影响因素及新能源并网对该特性的影响机理;其次,讨论了研究频率时空分布特性的必要性及描述该特性的量化指标;最后,基于仿真结果分析了不同电网形态下的频率时空分布特性,并总结了新能源机组并网对该特性的影响规律。

基于慢特征分析的分布式动态工业过程运行状态评价

现代工业过程通常具有规模大、流程长和工序多的特点,导致传统的集中式建模方法会淹没过程的局部变化信息,从而无法及时识别早期的非优运行状态.此外,闭环控制的广泛应用使得过程变量普遍存在时序相关性.针对以上问题,提出一种基于慢特征分析(Slow feature analysis, SFA)的分布式动态工业过程运行状态评价方法.首先,结合动态时间规整(Dynamic time warping, DTW)和K-medoids聚类算法对过程进行分解;然后,对每一变量子块建立相应的动态慢特征分析(Dynamic slow feature analysis, DSFA)模型;最后,利用贝叶斯推理获得全局的综合评价指标.通过在数值案例和金湿法冶金过程的仿真应用,验证了该方法的有效性.

基于EOF-DBSCAN-GRU的分布式光伏集群出力预测方法研究

提出一种基于EOF-DBSCAN划分集群的改进统计升尺度的光伏集群出力预测建模方法。针对传统统计升尺度方法子集群中光伏电站出力特性不一致问题,通过皮尔逊相关系数和经验正交函数(EOF)优化特征空间,再根据密度聚类模型(DBSCAN)对区域内光伏电站划分集群,从而增强光伏电站聚类后集群出力特性的一致性。针对待预测日权重系数时间序列动态特性的提取、预测问题,提出一种基于动态时间规整(DTW)的相似日选取算法。最后利用循环神经网络(GRU)模型进行光伏电站出力预测。实验表明该集群预测方法的平均误差百分数(MAPE)约为6.33%,均方根误差(RMSE)约为13.93 kW,均方误差(MSE)为194.25 kW,通过实际光伏电站数据证明了所提方法的准确性和有效性。

考虑波次订单动态释放的B2C电商订单合并配送决策方法

本文针对动态释放、异质性强的B2C电商波次订单的物流配送决策难题,以提高车辆满载率、降低配送成本为目标,研究考虑波次订单动态释放的B2C电商订单城区物流合并配送问题。首先,将原动态问题建模为一阶马尔可夫决策过程以表达其多阶段时序序贯决策的特点;其次,基于状态转移具有的时序特征,提出一种基于时序预测的前向动态规划方法用于寻找最优策略,将时序预测信息融入到合并配送决策的模型中,并结合定性启发式规则与定量优化模型以兼顾方法的决策效率与优化能力;最后,基于标准算例下的数值实验和某B2C电商平台的实例分析,验证了所提方法的有效性和实用性。此研究可为B2C电商订单物流配送提供决策支持,同时对于状态转移具有时序特征的马尔可夫决策问题提供了求解的新思路。

基于机器学习的雨型分类研究:以淠河流域为例

【目的】为了提升洪水预报方案的科学性和精度,开展降雨雨型分类,制定不同雨型的预报方案并实施作业预报是一条有效的技术路线。【方法】基于淠河流域2003—2021年37个雨量站逐小时降雨观测数据,利用业界公认的动态时间规划(DTW)算法进行场次降雨雨型分类并作为基准分类结果。在此基础上,分别选取决策树(DT)、长短期记忆神经网络(LSTM)、LightGBM、支持向量机(SVM)四种机器学习方法建立分类模型并检验分类效果。通过调整样本规模,分析不同样本容量对分类效果的影响。【结果】结果表明:四种分类模型中,LightGBM分类精度最高且训练速度快,LSTM和SVM分类精度良好但训练效率相对较低,DT方法分类速度较快但分类精度相对较低。随着样本规模的增大,分类结果逐步稳定,四种方法的分类效果和训练效率逐步提升。【结论】结果验证了机器学习方法在降雨序列雨型分类中具有较强的适用性,可为洪水预报方案分类构建提供技术支撑。

分布动载荷时域识别的动标定试验方法

在工程应用中,作用于工程结构上的载荷多为分布载荷,因此分布载荷识别技术一直备受关注。动标定技术通过建立载荷与响应之间的关系识别载荷,传统动标定方法根据有限元仿真获得标定矩阵,识别结果受到模型误差影响。基于Gauss-Legendre积分将无限维的动标定转换为有限维的动标定,通过傅里叶逆变换和卷积积分得到时域标定矩阵,对施加于结构上的分布载荷进行时域识别,并用仿真验证了该方法的有效性和高精度。在响应中加入噪声,考察该方法的抗噪性,并与传统仿真标定方法进行对比,并讨论了不同高斯点总数对识别精度的影响。

神东矿区构建综采工作面三维透视采场技术研究

为实现工作面回采期间矿压与生产管理、保障智慧矿山建设,需要构建三维透视采场。首先,基于实用矿山压力控制理论,建立采场空间结构力学模型,训练一套采场覆岩运动参数推导、支承压力分布规律计算、矿山压力实时监测数据分析与三维采场静态应力与动态应力模拟的算法体系。其次,通过采用二维三维一体化建模的方式构建三维透明地质模型、使用三维建模工具对液压支架等设备进行精细化建模、对采场上覆岩层的运动状态进行专业化建模,体现三维透视采场基本要素的全面性。通过采用三维曲面积分法解析综采液压支架相关数据、采用多目标多因素分级方法分析钻孔应力数据、采用时序序列数据分析其他数据三种方法进行采场实时监测数据分析。最后,以布尔台煤矿42204工作面为工程背景,构建了三维透视采场基本模型。所建立的三维模型能够根据地质信息、钻孔数据、矿压显现等实际情况反映应力场变化,实现采场空间采动应力随工作面推进的展示,为采煤工作面回采期间矿压与生产管理提供技术支撑。

基于时间序列动态匹配的含IIDGs配电网纵联保护

为提升含逆变型分布式电源IIDGs(inverter-interfaced distributed generators)接入的配电网电流差动保护抗同步误差能力,通过分析IIDGs与传统电源暂态电流波形的差异,充分考虑纵联通道同步误差的影响,提出了基于时间序列动态匹配的含IIDGs配电网纵联保护原理。通过对线路两侧电流采样值序列进行动态匹配识别故障,降低了线路两侧采样数据同步要求,引入时域波形平均欧氏距离构造保护判据提升灵敏度。仿真结果表明所提的保护判据能够可靠识别线路内部和外部故障,在现有继电保护装置采样率下性能良好。

基于DTW-两阶四分位的分布式光伏发电异常数据辨识

设备故障、天气环境等因素导致分布式光伏发电系统产生大量异常数据,对其安全稳定运行造成严重影响。为了准确识别和剔除存在的异常数据,提出一种基于动态时间弯曲(DTW)-两阶四分位的分布式光伏发电异常数据辨识方法。首先,通过对比相似辐照度下光伏功率均值实现连续型异常数据识别与剔除,采用基于同时段光伏功率均值剔除异常数据,并考虑光伏发电曲线的波动性,采用基于DTW与欧氏距离的综合曲线相似度判定方法剔除连续型异常数据,更全面地考虑了数据的波动特性,提高了连续型异常数据辨识和剔除效果;其次,提出DTW-两阶四分位异常数据辨识算法,采用一阶变化率和二阶变化率对融合后的数据进行离散型异常数据剔除,有效识别和剔除离散型异常数据;最后,根据异常数据识别和剔除结果判断是否出现故障。实验结果表明:所提算法剔除异常数据后能更好地拟合正常光伏功率数据分布情况,相较于四分位法和3-Sigma算法,所提算法剔除异常数据前后线性相关程度变化分别提高了58.15%和68.41%,辨识效果更佳。

基于动态时间规整的配电网分时段动态重构可靠性

配电网重构是指:通过改变开关状态来调整网络的拓扑结构,优化功率传输,是配电系统维持稳定的重要方法。传统的固定时间断面静态重构方法,无法适应新能源接入配电网后,快速变化的拓扑需求,配电网络节点的功率高时变性也给传统静态重构方法带来困难。为此提出了基于动态时间规整的配电网分时段动态重构方法。通过马氏距离测量电网在动态时间内,拓扑结构中节点的规整时序局部距离,划分负荷波动范围,得到电网拓扑中动态最佳分段个数与分段点。利用线性加权法把电网重构单目标转换成多目标优化,计算配电网分时段动态重构多目标优化方程。利用该方法控制开关状态,实现电网重构。实验证明:这种方法对配电网络重构后,网损值为539.2 kW,最低点电压数为0.994,重构后节点电压与实际值拟合度较好,配电网的频率偏差及谐波含量明显下降,说明所提方法的配电网重构可靠性较好。

基于周期采样的分布式动态事件触发优化算法

针对无向图下多智能体系统的优化问题,提出一种基于周期采样机制的分布式零梯度和优化算法,并设计一种新的动态事件触发策略。该策略中加入与历史时刻智能体状态相关的动态变量,有效降低了系统通信量;所提出的算法允许采样周期任意大,并考虑了通信延时的影响,利用Lyapunov稳定性理论推导出算法收敛的充分条件。数值仿真进一步验证了所提算法的有效性。

Residence time distribution and heat/mass transfer performance of a millimeter scale butterfly-shaped reactor

A millimeter scale butterfly-shaped reactor was proposed based on sizing-up strategy and fabricated via femtosecond laser engraving. An improvement of mixing performance and residence time distribution was realized by means of contraction and expansion of the reaction channel. The liquid holdup was greatly increased through connection of multiple mixing units. Structure optimization of the reactor was carried out by computational fluid dynamics simulation, from which the effect of reactor internals on mixing and the influence of parallel branching structure on heat transfer were discussed. The UV–vis absorption spectroscopy was used to determine the residence time distribution in the reactor, and characteristic parameters such as skewness and dimensionless variance were obtained. Further, a chained stagnant flow model was proposed to precisely describe the trailing phenomenon caused by fluid stagnation and laminar flow in small scale reactors, which enables a better fit for the experimental results of the asymmetric residence time distribution. In addition, the heat transfer performance of the reactor was investigated, and the overall heat transfer coefficient was 110–600 W m^(-2)K-1in the flow rate range of 10–40 m L/min.