Simulating high Reynolds number flow in two-dimensional lid-driven cavity by multi-relaxation-time lattice Boltzmann method

By coupling the non-equilibrium extrapolation scheme for boundary condition with the multi-relaxation-time lattice Boltzmann method, this paper finds that the stability of the multi-relaxation-time model can be improved greatly, especially on simulating high Reynolds number （Re） flow. As a discovery, the super-stability analysed by Lallemand and Luo is verified and the complex structure of the cavity flow is also exhibited in our numerical simulation when Re is high enough. To the best knowledge of the authors, the maximum of Re which has been investigated by direct numerical simulation is only around 50 000 in the literature; however, this paper can readily extend the maximum to 1000 000 with the above combination.

Event-driven timing system based on MRF cPCI hardware for HLS-II

Hefei Light Source(HLS)-II is a vacuum ultraviole(VUV) synchrotron light source. A major upgrade of the light source was finished at the end of 2014. The timing system was rebuilt using compact peripheral component interconnect(cPCI) event-driven hardware to meet synchronization requirements of the machine. In the new system, the c PCI event-driven products manufactured by the micro-research finland(MRF) Oy are employed to achieve about 100 output signals with different interfaces. Device supports and drivers developed for common Experimental Physics and Industrial Control System(EPICS) records are used to access the registers on the timing modules. Five c PCI-bus input/output controllers(IOCs) distributed in different areas of the light source host timing modules for various subsystems. The delay resolution of this system is 9.8 ns for most channels and 9 ps for the channels used for triggering the electron gun and the injection kickers. The measured rms jitter of the output signal is less than 27 ps. Using the bucket chooser, this system enables the HLS-II to fill the storage ring with any designated bunch pattern. Benefitting from this upgrade, brightness and performance of the light source are significantly improved.

数据与模型双驱动的集装箱码头集卡周转时间预测

集卡预约是缓解集装箱码头及其周边区域拥堵、实现港口内部作业机械均衡生产的有效手段。针对产业界对外集卡分时段在港周转时间预测的客观需求,提出了基于模型与数据双驱动的集卡在港周转时间预测方法,将在港周转时间预测转化为抵港车辆数量预测和港内周转时间测算两个子问题,抵港车辆数量预测部分构建了基于数据驱动的双层LSTM(长短期记忆递归神经网络)模型,港内周转时间测算部分则采用排队模型驱动方法。通过与历史实际数据集进行比较分析,实验结果表明:相较于传统单纯数据驱动或单纯模型驱动方法,所提出的数据与模型双驱动方法能够有效地预测码头集卡周转时间,且相较单纯数据驱动或单纯模型驱动的方法可降低40%以上的均方根误差(RMSE)和平均百分比误差(MAPE),更精确的集卡周转时间预测可为码头制定运营计划提供有利支持。

Stability of networked control systems with multi-step delay based on time-division algorithm

A new control mode is proposed for a networked control system whose network-induced delay is longer than a sampling period. A time-division algorithm is presented to implement the control and for the mathematical modeling of such networked control system. The infinite horizon controller is designed, which renders the networked control system mean square exponentially stable.Simulation results show the validity of the proposed theory.

Time-varying networks based on activation and deactivation mechanisms

A class of models for activity-driven networks is proposed in which nodes vary in two states： active and inactive. Only active nodes can receive links from others which represent instantaneous dynamical interactions. The evolution of the network couples the addition of new nodes and state transitions of old ones. The active group changes with activated nodes entering and deactivated ones leaving. A general differential equation framework is developed to study the degree distribution of nodes of integrated networks where four different schemes are formulated.

CADENCE系统上Timing-Driven设计流程探讨

本文首先介绍了亚微米领域集成电路中的寄生参数选取模型 ,然后给出了一种称之为时序驱动的设计流程 ,并对其中的关键步骤和工具作了简要介绍 ,着重介绍了布局布线工具SE中的时序驱动设计方法 。

Internet-based event synchronization communication driven telerobotics

Based on QoS (quality of service) parameters: time delay, jitter, bandwidth and package loss. As time delay in the Internet is variable, it is hard to compensate it by traditional methods. Event synchronization communication driven method is proposed to overcome the negative effects induced by time delay. This method is a non-time based method and it can get rid of the effects of time in the control loop of telerobotics. Stability, transparency and synchronization can be maintained in it by event-driven method. Multimodal enhanced telerobotics is put forward with its feedback including force, video, audio and temperature etc. The use of multimodal feedback improves the efficiency and safety of the whole system. Synchronization in multimodal feedback is hard to ensure and event-driven method is also good for it. Experiments on an Internet-based shaft-hole assemblage system show good results by using event synchronization communication driven method and UDP protocol.

基于数据驱动的分布式光伏发电功率预测方法研究进展

从综述的角度,以分布式光伏系统为对象,分析了功率预测技术的发展情况、存在的难点以及主要影响因素,梳理了应用数据驱动方法实现功率准确预测的技术路线。再以空间相关性、历史出力功率以及气象等影响因素为切入点,梳理了光伏系统数据驱动的功率预测研究现状,分析其相应的数据增强、时空图信息以及特征融合的手段,讨论了技术的优缺点。最后给出了功率预测数据驱动方法研究方向和发展建议。

THE EVOLUTION OF THE DENSITY OPERATORFOR DRIVEN SYSTEM

For studying the evolution of the density operator of the time-dependent dynamical system author presents here a general reformulation of subdynamics of driven system to obtain the efficient dynamical equation. The explicit formulas to calculate the creation operator and the destruction operator are given. A new intertwining relation is discussed, The method presented here can be useful to get the evolution formalism of the density operator for any system driven by an external field.

Design and implementation of high speed TDI CCD timing-driven circuits

The time delay integration charge coupled device(TDI CCD)is the key component in remote sensing systems.The paper analyzes the structure and the working principles of the device according to a customized TDI CCD chip.Employing the special clock resources and large-scale phase locked logic(PLL)in field-programmable gate arrays(FPGA),a timing-driven approach is proposed,using which all timing signals including reset gate,horizontal and vertical timing signals,are implemented in one chip.This not only reduces printed circuit board(PCB)space,but also enhances the portability of the system.By studying and calculating CCD parameters thoroughly,load capacity and power consumption,package,etc,are compared between various candidates chips,and detailed comparison results are also listed in table.Experimental results show that clock generator and driving circuit satisfy the requirements of high speed TDI CCD.

Numerical Investigation of Lid-Driven Deep Cavity with Local Grid Refinement of MRT-LBM

In the case of lid-driven deep cavity flow, the effects of different resolutions of local grid refinement have been studied in the frame of multiple relaxation times (MRT) lattice Boltzmann method (LBM). In all the cases, the aspect ratio and Reynolds number are set as 1.5 and 3.200, respectively. First, the applied method is validated by comparing it with two reported works, with which agreements are reached. Then, six separate degrees of local grid refinement at the upper left corner, i.e. purely coarse grid, including 1/64, 1/32, 1/16, 1/8, 1/4 refinements of the lattice number in the width direction have been studied in detail. The results give the following indications:① The refinement degrees lower than 1/8 produce similar results;② For single corner refinement, 1/4 refinement is adequate for clearing the noises in the singularity zone to a large extent;③ New noise around the interface between coarse and fine zones are introduced by local grid refinement. Finally, refinement of entire subzone neighboring the lid is examined to avoid introducing new noises and it has been found effective.

基于数据-模型混合驱动的电力系统机电暂态快速仿真方法

数据驱动建模方法改变了发电机传统的建模范式,导致传统的机电暂态时域仿真方法无法直接应用于新范式下的电力系统。为此,该文提出一种基于数据-模型混合驱动的机电暂态时域仿真(data and physics driven time domain simulation,DPD-TDS)算法。算法中发电机状态变量与节点注入电流通过数据驱动模型推理计算,并通过网络方程完成节点电压计算,两者交替求解完成仿真。算法提出一种混合驱动范式下的网络代数方程组预处理方法,用以改善仿真的收敛性;算法设计一种中央处理器单元-神经网络处理器单元(central processing unit-neural network processing unit,CPU-NPU)异构计算框架以加速仿真,CPU进行机理模型的微分代数方程求解;NPU作协处理器完成数据驱动模型的前向推理。最后在IEEE-39和Polish-2383系统中将部分或全部发电机替换为数据驱动模型进行验证,仿真结果表明,所提出的仿真算法收敛性好,计算速度快,结果准确。

基于Transformer的纯电动汽车充电时间预测

纯电动汽车充电时间的安排是车主日常生活中至关重要的环节,直接影响车主出行的便利度和舒适体验。然而,目前仍然面临充电桩资源不足、充电须提前规划等挑战,为解决车主因车辆电量不足而无法立即用车的问题,提出一种基于Transformer模型的充电时间预测解决方案,帮助车主更好地规划日常行程。为了更好地了解电池性能衰减程度和容量损失情况,采用容量法评估电池健康状态,并分析驾驶人的充电行为,对电池充电行为特征进行构建。使用Savitzky-Golay滤波器对表征电池衰减的特征进行平滑处理,并进行累积变换,使特征能更全面地表征电池信息;再耦合皮尔逊相关系数和LASSO(least absolute shrinkage and selection operator)回归算法二次筛选得到最优特征集。最后,利用Transformer模型的超强注意力机制,对充电时间进行预测。通过实验数据验证,此方案可以准确且快速地预测纯电动汽车的充电时间,决定系数达到0.999,运行时间为156 ms。

考虑交通信号和交通密度的城市路段个体行程时间建模

为探究城市路段中交通密度与交通信号对个体车辆行程时间的影响规律,提高城市道路行程时间的预测精度,基于车牌识别数据与信号机配时数据等多种融合数据,提出了由自由流行程时间、密度延误与随机误差项组成的行程时间关系函数,并在该函数基础上构建了考虑个体驾驶习惯的行程时间预测模型。首先,基于道路限速条件、车辆进入路段时的下游交叉口信号状态构建自由流行程时间函数;其次,提出了一种通过密度阈值判断车辆能否在当前信号周期通过下游交叉口的方法,并基于个体车辆进入路段时的路段密度计算出车辆所需等待信号周期个数及等待前方排队疏散所需时间,从而构建密度延误函数;然后,将个体实际行程时间与自由流行程时间、密度延误的差值作为随机误差项,通过高斯混合模型拟合随机误差项的概率分布;最后,选用安徽省宣城市多个路段作为案例,分析各路段行程时间函数各部分的具体表现,对该行程时间预测模型进行验证。结果表明:行程时间预测模型的MAPE,MAE,RMSE分别为6%~12%,5~15,13~35,在准确率方面优于其他算法,是一种有效的城市路段个体行程时间预测方法。

MAC技术优化日间宫腔镜手术麻醉成本的探索——基于TDABC核算模型的研究

该研究通过回顾天坛医院2021年10月-2022年9月的日间宫腔镜手术,借助估时作业成本(Timedriven Activity-based Costing,TDABC)模型计算麻醉成本,并记录围术期不良事件,评价了日间宫腔镜手术采用监测下麻醉管理(Monitored Anesthesia Care,MAC)技术消耗的麻醉成本及其安全性。717例患者完成麻醉和手术,其中466例接受了MAC麻醉,251例接受了传统的全身麻醉(General Anesthesia,GA)。MAC组平均麻醉成本为889.84元/例,明显低于GA组(1143.57元/例,P<0.0001)。MAC组围术期不良事件发生率(3.65%),与传统GA组(6.37%)相比,差异无统计学意义(P=0.0965),两组均无严重不良后果。多元回归分析显示,MAC组麻醉成本与患者年龄、手术时间和麻醉时间都有相关性(P<0.01)。MAC作为安全、有效的麻醉技术,可显著降低麻醉成本。麻醉医生可以借助TDABC模型进行成本核算,同时优化临床路径和成本控制。

珞珈三号01星在轨处理技术及验证

遥感卫星在轨处理技术是推动遥感技术实现实时智能服务的核心环节。针对星上资源受限环境引起的系列处理难题及遥感数据实时处理与信息提取需求,本文首先构建了任务驱动的卫星遥感数据在轨处理框架,以任务需求为核心并协同星地资源建立基于感兴趣区域的星上处理技术体系;然后,面向不同任务层级和应用场景,给出了以位置信息为驱动的基础在轨处理模式、以目标/场景内容和变化事件为驱动的智能处理模式;最后,论述了适配星上资源受限环境的在轨处理关键算法,基于珞珈三号01星星上处理应用程序,验证了典型算法的在轨处理效果。在任务驱动和星地协同机制下,实现了在轨高精度定位、多类型影像产品快速生成、静动态目标信息实时提取及静态和动态影像高倍率近实时压缩。在轨处理显著提高了传统地面处理的效率,能够有效支撑后续卫星遥感实时智能服务。

基于扩张状态观测器的过热汽温系统建模与参数智能辨识

可再生能源的高渗透率给电网供需匹配带来严峻挑战的同时,燃煤机组需要承担着大量的调峰调频任务,这对过热汽温系统的安全稳定运行造成了一定威胁,因此有必要建立面向热工控制的汽温数学模型。考虑到迟延型扩张状态观测器(time-delayed extended state observer,TD-ESO)的总扰动信号中含有大量模型信息,提出一种基于ESO补偿模型的参数智能优化和信息提取方法,即以总扰动中未知信息量最小为目标,采用改进沙丘猫算法对模型参数优化并提取总扰动中已知模型信息补偿至ESO的输入端。在仿真算例方面,线性和非线性系统的测试结果表明,所提辨识方法对有无输入迟延的两种系统均有良好的适用性和较高的精度;在实际应用方面,基于超超临界二次再热机组的过热汽温系统数据进行模型辨识与验证,同样表明该建模方法是合理、准确的。因此,该文所建立的模型能够为汽温系统的控制策略设计和性能优化等方面提供有价值的参考。

混合式教学在理实一体化类课程中的应用——以工业机器人现场编程为例

理实一体化类课程是高职院校最为标志性的课程,利用手段丰富的混合式教学来提升该类课程的教学效果,从而达到人才培养质量的提升。通过精品在线开放课程和学习通平台来进行线上线下混合式教学,以解决该类课程目前在教学过程中存在的一些局限,特别是如何充分利用线上的教学数据,如何分析整理数据,以数据驱动的模式来实时优化课堂的教学设计。通过教学实践总结,对教学方法的创新、教学手段的应用进行了梳理与探讨,为理实一体化类课程的教学改革提供一定的借鉴。

基于数据驱动的红外弱小机动目标检测与跟踪

针对复杂背景下红外弱小目标检测跟踪中目标特征缺失、强杂波干扰等问题,基于多帧的处理方法引入了目标运动特征来提升性能,然而针对无人机等新型强机动目标,现有的基于机理模型的多帧处理方法难以覆盖其复杂多变的运动形态,导致其检测跟踪的效果并不理想。对此,以多帧的处理方法为基础框架,提出了一种复杂背景下基于数据驱动的红外弱小机动目标检测跟踪方法:首先采用MPCM算法对弱小目标进行增强;其次将多帧的增强结果投影到二维子空间,构建基于YOLO的二维轨迹检测模型;最后将二维检测结果进行三维时空回溯,构建基于LSTM的三维轨迹检测模型。构建检测模型时,在实测图像的基础上进行了数据增广,使得训练样本尽量覆盖目标的各种运动形态;在二维子空间上,利用高性能YOLO检测网络,快速剔除大量杂波;在三维时空上,利用LSTM时序网络对少量难剔除的杂波进行精细化筛除。与多种算法的对比实验结果表明,所提方法在耗时上能满足实时性要求,同时,在多个场景下的平均跟踪精度能达到86.6%,虚警率仅有9.2%,ROC曲线下的AUC值能达到0.9820。