我国云母分选技术现状及其在砂石行业中的应用前景

砂石原料中常含有云母,砂石骨料对云母的含量有严格规定。介绍了我国云母分选技术现状和研究进展,并结合其各项技术特点,初步分析了云母分选在砂石行业中的应用前景。分析结果表明,破碎筛分分选、摇床重选、磁选和风选等物理分选方法有较好的应用前景。     

泥沙起动条件分析及推移质输沙率公式

基于床面均匀泥沙颗粒相对位置关系,确定了瞬时作用流速及有效作用高度,建立了平坡泥沙起动条件与床面泥沙暴露度的关系。从理论上分析得到,泥沙跃移起动要求水流条件最高,滚动起动及滑动起动取决于泥沙颗粒的暴露角,且暴露角θ不随拖曳力系数C_D和上举力系数C_L的变化而变化。当暴露角θ小于42.8°时,泥沙更易于滚动起动;当暴露角θ大于42.8°时,泥沙更易于滑动起动。在此基础上,推导出了考虑两种起动模式的起动全概率公式,建立了床面推移质单宽输沙率公式。通过经典的推移质输沙率实测资料验证及误差计算表明,公式结构合理,计算精度较高,对于高、中、低输沙率都具有较好的适用性。     

砾石土料全级配击实仪研制及应用

砾石土料最大粒径为100 mm全级配击实仪的成功研制与应用,提高了全级配击实试验的科学性,保证了试验结果准确可靠。特别在类似的工程中全级配击实仪首次采用锤击点角度为53.5°,实现了锤击点之间无击实盲区,在国内已建类似工程中未见相关文献资料。本文依托双江口水电站工程,研制全级配土料超大型击实仪(土料最大粒径为100 mm),真实反映了土料全级配击实试验结果,为砾石土心墙料采用全料压实度控制碾压质量提供可靠的基础数据,具有较高的推广价值。     

金沙江中游梯级水电站联合优化调度实践

分析了金沙江中游区域梯级水电站联合调度的特殊性及复杂性,从电调的角度介绍了金中集控中心自成立以来对受控梯级水电站联合调度的具体实施,总结了梯级水电站联合优化调度的措施,并分析了梯级水电站联合优化调度的综合效益,发现优化调度成效明显。     

一种固结桩式薄板丁坝及其桩体的抗倾覆能力

介绍一种新型且经济的、带固结桩的预制插板丁坝,其固结桩是该丁坝的主要抗倾覆构件。通过室内试验和三维扫描技术,在细砂基床上开展了固结桩的抗倾覆性能研究。结果表明:固化剂与土体反应后在桩周形成"脚靴"状固结体,显著提高了桩的抗倾覆力;固结桩的倾覆过程分为微偏阶段、倾斜阶段、倾覆阶段和拔移阶段;固结桩抗倾覆力主要受桩体几何形状、埋深、土体性质、固化剂注浆剂量和注入流量等因素的影响。通过量纲分析和试验数据拟合,提出了固结桩临界水平抗倾覆力及临界倾斜角的计算公式。     

基于层合板理论的多层加筋碎石垫层承载特性分析

为研究多层加筋垫层自身极限承载特性,考虑多层土工格栅的加筋作用,假设加筋垫层为层合板,并根据静力平衡条件和应变连续条件,分析得出加筋垫层的极限承载能力计算方法,通过室内试验对理论推导公式进行结果验证。研究结果表明:理论计算与试验结果吻合较好;随着格栅层数、垫层厚度、碎石抗剪强度的增加,多层加筋垫层自身极限承载能力增强;随着桩间距和底层格栅距桩帽距离的增大,多层加筋垫层自身极限承载能力降低。     

Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning

Process monitoring in additive manufacturing may allow components to be certified cheaply and rapidly and opens the possibility of healing defects, if detected. Here, neural networks (NNs) and convolutional neural networks (CNNs) are trained to detect flaws in layerwise images of a build, using labeled XCT data as a ground truth. Multiple images were recorded after each layer before and after recoating with various lighting conditions. Classifying networks were given a single image or multiple images of various lighting conditions for training and testing. CNNs demonstrated significantly better performance than NNs across all tasks. Furthermore, CNNs demonstrated improved generalizability, i.e., the ability to generalize to more diverse data than either the training or validation data sets. Specifically, CNNs trained on high-resolution layerwise images from one build showed minimal loss in performance when applied to data from an independent build, whereas the performance of the NNs degraded significantly. CNN accuracy was also demonstrated to be a function of flaw size, suggesting that smaller flaws may be produced by mechanisms that do not alter the surface morphology of the build plate. CNNs demonstrated accuracies of 93.5 % on large (>200 μm) flaws when testing and training on components from the same build and accuracies of 87.3 % when testing on a previously unseen build. Finally, evidence linking the formation of large lack-of-fusion defects to the presence of process ejecta is presented.     

基于CAN总线的嵌入式智能防褥疮气垫床的设计

针对家庭护理问题,设计并实现了基于CAN总线的嵌入式智能防褥疮气垫床.阐述了该智能气垫床的硬件系统设计,软件系统设计及实现方法.气垫床控制模块由AT90CAN128单片机、气垫床、压力传感器、气泵和电磁阀门等构成.采用S3C2440作为主控制模块,以WindowsCE操作系统为核心开发的人机交互界面(HMI)通过CAN总线实时传递各个功能模块命令,能够实现气垫床的预定功能,给出了实验实测数据,并且能够实现即插即用的模块化设计.     

Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model

In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used to model local scouring depth and pattern scouring around concave and convex arch shaped circular bed sills. The experimental part of this research study includes seven sets of laboratory test cases which were performed in an experimental flume under different flow conditions. A data set consists of 2754 data points of scouring depth were collected to use in the ANFIS model. The ratio of arch diameter, D, to flume width, W, is used as a non dimensional variables in all test cases. The results from ANFIS model were compared with the results of ANN model obtained by Homayoon et al. [24] and previously presented models. The results indicated that for D/W equal to 1 and 1.2, the ANFIS models produced a good performance for convex and concave bed sills. As a result, the ANFIS models can be used as an alternative to ANN for estimation of scour depth and scour pattern around a concave bed sill installed with a bridge pier.     

Continuous size fractionation of magnetic nanoparticles by using simulated moving bed chromatography

The size fractionation of magnetic nanoparticles is a technical problem, which until today can only be solved with great effort. Nevertheless, there is an important demand for nanoparticles with sharp size distributions, for example for medical technology or sensor technology. Using magnetic chromatography, we show a promising method for fractionation of magnetic nanoparticles with respect to their size and/or magnetic properties. This was achieved by passing magnetic nanoparticles through a packed bed of fine steel spheres with which they interact magnetically because single domain ferro-/ferrimagnetic nanoparticles show a spontaneous magnetization. Since the strength of this interaction is related to particle size, the principle is suitable for size fractionation. This concept was transferred into a continuous process in this work using a so-called simulated moving bed chromatography. Applying a suspension of magnetic nanoparticles within a size range from 20 to 120 nm, the process showed a separation sharpness of up to 0.52 with recovery rates of 100%. The continuous feed stream of magnetic nanoparticles could be fractionated with a space-time-yield of up to 5 mg/(L∙min). Due to the easy scalability of continuous chromatography, the process is a promising approach for the efficient fractionation of industrially relevant amounts of magnetic nanoparticles.