Evaluating Particle Deposition in the Artificial Groundwater Recharge Process by Physical and CT Imaging Experiments

Particle clogging in the artificial groundwater recharge process is one of the main factors influencing the artificial groundwater recharge efficiency, and particle deposition is the microscopic mechanism of the occurrence and development of particle clogging. Particle deposition in porous media changes the pore structure. The computed tomography (CT) scanning technique is a nondestructive testing method and determines the spatial distribution of pores in porous media. This study combines physical and CT scanning experiments to identify the change process of the pore structure in the artificial groundwater recharge process and compares the pore changes during recharge experiments between two columns containing different media. Porous media changes are observed with the CT scanning technique. The fractal theory is applied in the analysis of CT scan images and physical experiment results. The results of this study indicate that particle deposition can be examined by using CT scan images to obtain pore-related parameters, the internal pore structure of porous media determined through CT scan images can be applied in numerical simulation, and a mathematical model for particle deposition calculation in porous media is established. Compared to the physical experiment measurements, the spatial particle deposition information acquired with the CT scanning technique exhibits a higher accuracy and contains much more relevant data. Not only does this research reveal more clearly the particle clogging mechanism which is based on particle deposition, but also characterize, simulate and predict more accurately the development tendency of particle clogging during artificial groundwater recharge.

     

基于SWMM模型模拟的海绵城市建设效果评估——以北京市房山区为例

为定量评估房山区现状海绵建设情况,支撑2020年海绵城市达标考核工作,采用资料收集结合现场调研的方式获取各类海绵建设项目信息并进行校核,借助ArcGIS软件将海绵设施数字化,并以排水分区为单元完成落图.基于暴雨径流管理模型SWMM软件构建全区数值模型,将调研的海绵设施概化到模型中开展模拟评估.结果表明:截至2020年底,房山全区有效海绵项目418个,主要分布在拱辰及西潞街道、长阳镇、良乡镇、窦店镇、阎村镇、城关街道及燕山地区.模拟结果表明城市建成区达标面积为13.73 km2,达标比例20.46％.本项目研究方法可为全市其他区的海绵现状评估提供参考.     

阎王鼻子水库生态调度方案分析研究

本文在分析阎王鼻子水库建设前后下游水文情势变化的基础上,根据河道内生态不同需求和不同计算方法,确定水库下游河道基本生态流量和目标生态流量两种需求方案。在充分考虑大凌河流域河道外需水的前提下,研究分析了阎王鼻子水库最大程度满足河道内不同生态需水要求时的调度方案,对改善水库下游河道环境具有一定的指导意义。     

Double Medical Images Zero-Watermarking Algorithm Based on the Chaotic System and Ternary Accurate Polar Complex Exponential Transform

Journal of Mathematical Imaging and Vision - Different from the traditional watermarking schemes, zero-watermarking schemes are lossless embedding methods, which are applicable to be used in...     

Study of the hinge thickness deviation for a 316L parallelogram flexure mechanism fabricated via selective laser melting

3D printing offers great potential for developing complex flexure mechanisms. Recently, thickness-correction factors (TCFs) were introduced to correct the thickness and stiffness deviations of powder-based metal 3D printed flexure hinges during design and analysis. However, the reasons for the different TCFs obtained in each study are not clear, resulting in a limited value of these TCFs for future design and fabrication. Herein, the influence of the porous layer of 3D printed flexure hinges on the hinge thickness is investigated. Samples of parallelogram flexure mechanisms (PFMs) were 3D printed using selective laser melting (SLM) and 316L stainless steel powder. A 3D manufacturing error analysis was completed for each PFM sample via 3D scanning, surface roughness measurement and morphological observation. The thickness of the porous layer of the flexure hinge was independent of the designed hinge thickness and remained close to the average powder particle diameter. The effective hinge thickness could be estimated by subtracting twice the value of the porous layer thickness from the designed value. Guidelines based on finite element analysis and stiffness experiments are proposed. The limitations of the presented method for evaluating the effective hinge thickness of flexure hinges 3D printed via SLM are also discussed.

     

航空机轮加载测控系统软件的设计与实现

鉴于航空机轮加载试验过程中,要求上位机测控软件能够即时向下位机下达控制命令并且能够实时采集下位机上传的大量现场数据,给出了一种基于DataSocket技术和OPC协议的实时网络通信方法;针对程序执行过程中常出现的响应阻塞问题,结合LabWin-dows/CVI的多线程机制论述了一种多任务并发执行的方法;经过反复测试试验,由此所构建的上位机软件响应性能良好,其网络通信传输速率快、实时性高。     

基于蓄电池三段式充电的小型风光互补控制系统的设计与仿真

基于太阳能光伏发电和风力发电的特点,给出了新颖的最大功率点跟踪控制策略;研究了蓄电池在各个充电方式下的特点,给出一种三段式充电控制策略,设计了一种新型风光互补控制系统,经matlab仿真验证,本系统可靠稳定,降低了成本,并实现了蓄电池的高效、快速、无损充电,使得充电曲线尽可能地逼近最佳充电曲线,提高了蓄电池使用效率,并利用双闭环PID控制实现了蓄电池的恒压限流充电。     

面向家庭的ZigBee医疗监护网络研究

ZigBee无线医疗监护能够让广大民众在家中享受个性化医疗卫生服务,有效地缓解医疗卫生资源紧缺等严峻的社会问题;研究通过ZigBee传感器网络在普通家庭环境下的抗干扰能力测试、最大通信距离测试、网络自恢复能力测试、耗电量测试等,阐述了Zig-Bee短距离通信技术在实际应用中的优缺点以及在医疗监护中应用的可行性,为面向家庭的的无线医疗做了理论依据,并且设计了协调器与上位机、路由节点、传感器节点的通信协议;通过各种测试,研究得出结论:ZigBee短距离通信技术在家庭环境中,能够有效地克服各种家用设备的干扰,数据传输准确率高,正常情况下,准确率达到100%,在增加路由节点的情况下,能够完全覆盖家庭环境,满足无线医疗监护的要求。     

CBR系统中一种实例相似度算法的改进

本文对CBR系统中实例相似度的算法进行了改进,在传统实例相似性算法的基础上加入实例属性缺失度因子和实例可复用性因子。因此在实例检索中考虑实例检索结果的精确度和实例的可复用度,进而使检索的精确度提高和修改难度降低,最终提高CBR系统的精确度和实用性。     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.