三维石墨烯-碳纳米管/水泥净浆的压敏性能

为了探索三维石墨烯-碳纳米管(G-CNTs)/水泥净浆的压敏性能,采用四电极法研究了荷载作用下GCNTs/水泥净浆的电阻率变化,并分析不同G-CNTs掺量、加载幅度、加载速度以及恒定荷载对电阻率变化的影响。研究表明:随着G-CNTs掺量的增加,电阻率呈先减小后稳定的变化趋势,在G-CNTs掺量由0.2wt%增加至1.6wt%时,电阻率下降51.8%;电阻率与温度呈负相关;G-CNTs掺量高于0.8wt%时可以显著提高水泥净浆的压敏性能,且电阻率变化率与应力应变有明显的对应关系,1.2wt%G-CNTs掺量下试件的应力灵敏系数和应变灵敏系数分别为2.3%/MPa和291;G-CNTs/水泥净浆电阻率变化率幅值随着加载幅度增大而相应增加,其电阻率变化率曲线在不同加载速度以及恒定荷载作用下均与应力-应变曲线一一对应,具有良好的压敏特性。     

A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

A large-scale dynamically weighted directed network (DWDN) involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications, like in a terminal interaction pattern analysis system (TIPAS). It can be represented by a high-dimensional and incomplete (HDI) tensor whose entries are mostly unknown. Yet such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN. A latent factorization-of-tensors (LFT) model proves to be highly efficient in extracting such knowledge from an HDI tensor, which is commonly achieved via a stochastic gradient descent (SGD) solver. However, an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale DWDNs. To address this issue, this work proposes a proportional-integral-derivative (PID)-incorporated LFT model. It constructs an adjusted instance error based on the PID control principle, and then substitutes it into an SGD solver to improve the convergence rate. Empirical studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models, the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.      

数控多轴正逆向制造实训基地建设探索

本文阐述了多轴正逆向制造发展趋势,基地建设的必要性,以五轴加工中心、五轴仿真模拟面板、三维扫描仪、3D打印机等为主的加工、逆向、快速成形先进前沿设备,形成多元化的先进制造实习链,满足、丰富实训内容,提升学生社会就业竞争力。     

基于改进EEMD与混沌振子的配电网故障选线

提出改进的集合经验模态分解(MEEMD)和混沌振子相结合的电网故障微弱信号检测方法。首先,建立神经网络预测模型,通过神经网络对配网各线路零序电流进行短时预测,滤除故障信号中的背景信号;其次,为了检测配网发生单相接地故障后微弱的5次谐波信号,提出结合多尺度排列熵和完备集合经验模态分解(CEEMD)改进的改进的集合经验模态分解算法;处理已经滤除背景信号的故障信号,提取其第一固有模态函数作为混沌振子的输入。混沌振子对和内驱动力信号同频的外策动力信号有较高的敏感性,通过混沌振子输出的相图完成电网故障选线。     

Explicit bounds for separation between Oseledets subspaces

We consider a two-sided sequence of bounded operators in a Banach space which are not necessarily injective and satisfy two properties (SVG) and (FI). The singular value gap (SVG) property says that two successive singular values of the cocycle at some index d admit a uniform exponential gap; the fast invertibility (FI) property says that the cocycle is uniformly invertible on the fastest d-dimensional direction. We prove the existence of a uniform equivariant splitting of the Banach space into a fast space of dimension d and a slow space of codimension d. We compute an explicit constant lower bound on the angle between these two spaces using solely the constants defining the properties (SVG) and (FI). We extend the results obtained by Bochi and Gourmelon in the finite-dimensional case for bijective operators and the results obtained by Blumenthal and Morris in the infinite dimensional case for injective norm-continuous cocycles, in the direction that the operators are not required to be globally injective, that no dynamical system is involved and no compactness of the underlying system or smoothness of the cocycle is required. Moreover we give quantitative estimates of the angle between the fast and slow spaces that are new even in the case of finite-dimensional bijective operators in Hilbert spaces.     

水润滑螺旋阶梯腔艉轴承接触特性分析及结构优化

基于有限元法,考虑艉轴承材料的非线性力学特性以及各结构参数间的交互作用,对该轴承进行接触分析。采用正交试验法分析腔长、腔数、螺旋角、深浅腔比例等主要影响因素对接触应力及变形量的影响规律,采用控制变量法分析螺旋腔腔角、进/出水孔直径、螺旋腔腔深等次要因素对接触应力及变形量的影响规律,分别得到各参数的优化值。同时利用多目标优化方法,对艉轴承的沟槽直径和内衬外径进行优化,以满足低应力及轻量化的设计要求。优化后艉轴承质量降低了29%,接触应力降低了12%,在达到轻量化的目的同时,显著提高了其力学性能。     

基于历史数据聚类的火电机组工况划分

针对调峰背景下火电机组非稳态工况增多,以及常见运行工况偏离设计工况等问题,提出了基于历史运行数据聚类的工况划分模型。首先,考虑到运行数据中非稳态工况与稳态工况并存的情况,以功率作为特征变量,提出基于功率差值期望区间估计的稳态判别算法,筛选出历史数据中的非稳态工况;其次,由于稳态工况下外部边界条件变量的分布差异性,提出改进的多步K-均值聚类算法进行稳态工况的划分,并利用silhouette评价准则确定每步条件下的最佳聚类数;最后,采用某实际发电用重型燃气轮机的历史运行数据进行模型验证。通过与传统K-均值聚类算法比较,所提出的模型能够有效解决工况分类数目较少以及样本分布不均的问题。