THEORETICAL RELATIONS OF BOUNDARY DISPLACEMENT DERIVATIVES AND TRACTIONS AT SINGULAR BOUNDARY POINT FOR 2D ISOTROPIC ELASTIC PROBLEMS

Although boundary displacement and traction are independent field variables in boundary conditions of an elasticity problem at a non-singular boundary point, there exist definite relations of singularity intensities between boundary displacement derivatives and tractions at a singular boundary point. The analytical forms of the relations at a singular smooth point for 2D isotropic elastic problems have been established in this work. By using the relations, positions of the singular boundary points and the corresponding singularity intensities of the unknown boundary field variables can be determined a priori. Therefore, more appropriate shape functions of the unknown boundary field variables in singular elements can be constructed. A numerical example shows that the accuracy of the BEM analysis using the developed theory is greatly increased.

3D Distinct Element Back Analysis Based on Rock Structure Modelling of SfM Point Clouds:The Case of the 2019 Pinglu Rockfall of Kaili,China

This paper introduces the use of point cloud processing for extracting 3D rock structure and the 3DEC-related reconstruction of slope failure,based on a case study of the 2019 Pinglu rockfall.The basic processing procedure involves:(1)computing the point normal for HSV-rendering of point cloud;(2)automatically clustering the discontinuity sets;(3)extracting the set-based point clouds;(4)estimating of set-based mean orientation,spacing,and persistence;(5)identifying the block-forming arrays of discontinuity sets for the assessment of stability.The effectiveness of our rock structure processing has been proved by 3D distinct element back analysis.The results show that Sf M modelling and rock structure computing provides enormous cost,time and safety incentives in standard engineering practice.

A modified method of discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces

This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.

A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models

In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.

基于无人机3D点云的高陡斜坡岩体结构特征

岩体结构控制着岩质斜坡的变形破坏模式,但传统的结构面信息调查方法存在危险性高、难度大的缺陷。为安全、高效地获取斜坡岩体结构信息,利用无人机摄影技术开展高陡岩质斜坡的测量,构建斜坡岩体的3D点云模型,识别结构面的产状、间距、迹长等岩体结构信息。对湖北秭归卡门子湾滑坡区调查验证,斜坡共发育6组优势结构面,平均间距为0.46~1.01 m,平均迹长为0.82~12.57 m;无人机3D点云获取的岩体结构信息精度满足要求,方法高效、可行;获得的岩体结构信息为斜坡岩体结构模型建立和稳定性评价等工作提供了可靠的数据基础。

基于钳位方式切换的Vienna整流器载波断续脉冲宽度调制策略

当Vienna整流器工作在直流电压不平衡条件下时,传统载波断续脉宽调制(carried-based discontinuous pulse-width modulation,CB-DPWM)会增加输入电流谐波和中点电压波动。为解决上述问题,提出一种基于钳位方式切换的CB-DPWM策略。为了减小输入电流谐波,根据变化的电压矢量对子区域和零序分量进行重新划分和计算。据此,建立统一的CB-DPWM调制波,分析可运行区域,得到直流电压不平衡度和可运行区域成反比的结论。结合中点电流分析不同钳位方式对中点电压大小的影响,并根据直流电压不平衡度的大小实时切换钳位方式,从而有效地减小中点电压波动。通过钳位区域判断和优化开关序列,减少切换钳位方式引入的开关动作,提高了Vienna整流器效率。最后,在Vienna整流器实验平台上验证所提策略的有效性。

临界点理论在分数阶微分方程边值问题中的应用

用临界点理论和变分法研究Banach空间中带Sturm-Liouville边值条件的Caputo型分数阶微分方程解的存在性.通过定义适当的分数阶导数空间,将分数阶微分方程边值问题解的存在性转化为寻找定义在某个空间上对应泛函的临界点,得到了该边值问题存在一系列无界的广义解.

兼顾共模电压抑制与中性点电压平衡的T型三电平逆变器DPWM策略

为提升T型三电平逆变器的可靠性与效率,提出1种可抑制共模电压的非连续脉宽调制RCVDPWM(reduced-common-mode-voltage pulse width modulation)策略,同时能够降低开关损耗。根据T型三电平拓扑开关序列对共模电压作用机理,总结出5种实现共模电压抑制的非连续脉宽调制DPWM(discontinuous pulse width modulation)钳位方式。分析表明,在任意调制度和相角下,至少存在1种实现共模电压抑制的钳位方式。对于部分相角区间存在的多种钳位方式,优先选取电流绝对值最大相的开关管进行钳位,以降低开关损耗。同时,所提RCVDPWM策略可保证中性点电压直流分量为0,具有中性点自平衡能力。实验结果验证了RCVDPWM策略的可行性与有效性。

基于深度学习算法和三维点云的岩体结构面智能识别

本文使用SqueezeNet网络作为基础,构建深度学习点云结构面智能识别模型,案例采用RockBench公开数据库中的数据来验证深度学习模型的识别效果。扫描岩体位于西班牙拜克斯营地地区的TP-7101公路沿线,使用Optech LLRIS 3D激光扫描仪获取点云数据。以点云XYZ坐标和法向量作为输入数据,之后挑选550个点构建训练数据集,设置模型的最优参数并以此训练深度学习模型。将训练好的深度学习模型应用到整个点云数据中,对点云数据进行结构面分组。同时,引入Ordering Points to Identify the Clustering Structure(OPTICS)和Density-Based Spatial Clustering of Applications with Noise(DBSCAN)对得到的结构面组进行划分,得到单个结构面。最后,计算出各个结构面的产状。为了验证深度学习模型的识别准确率,采用传统的BP神经网络方法进行验证,计算5组结构面的平均值产状,并与前人计算结果进行对比。经过对比,深度学习模型的计算准确率明显高于浅层BP神经网络模型,其倾向平均误差为9.6456°、倾角平均误差为7.6890°。整体来看,深度学习模型结构更加复杂、提取信息的能力更强,产状计算误差更小。

一类具有转点的右端不连续奇摄动边值问题

研究了一类具有转点的右端不连续二阶半线性奇摄动边值问题解的渐近性.首先,在间断处将原问题分为左右两个问题,通过修正左问题退化问题的正则化方程,提高了左问题渐近解的精度,并利用Nagumo定理证明了左问题光滑解的存在性.其次,证明了右问题具有空间对照结构的解,并通过在间断点的光滑缝接,得到了原问题的渐近解.最后,通过一个算例验证了结果的正确性.

Mathematica实现函数间断点的可视化

用Mathematica软件的系统函数Plot所绘制的函数图形中,在间断点处的单侧连续性没有体现出来。本研究使用Mathematica所提供的模式替换、方程求解等功能,实现了自动识别分段函数中的所有分段点,并对每个分段点计算左右极限及函数值,从而实现了分段函数图形中每一个间断点处单侧连续性的可视化。

行腹腔镜手术患者术后不同时点撤销静脉镇痛泵的效果分析

目的:评估行腹腔镜手术患者术后不同时点撤销静脉镇痛泵的效果分析。方法:选取东源县人民医院2022年5月至7月收治的60例行腹腔镜手术患者,随机分为4组,分别为未使用镇痛泵组(A组)、术后24 h停用镇痛泵组(B组)、术后48 h停用镇痛泵组(C组)和术后72 h停用镇痛泵组(D组)。比较各组患者视觉模拟评分法(VAS)评分、术后追加静脉注射镇痛药患者例数、住院时间、停止吸氧时间、肠鸣音和肛门排气恢复时间、不良反应发生情况。结果:A组VAS评分高于其他三组,C组VAS评分低于其他三组,差异具有统计学意义(P <0.05)。A组住院时间长于其他三组,C组住院时间短于其他三组,差异具有统计学意义(P <0.05)。A组术后追加静脉注射镇痛药患者占比高于其他三组,差异具有统计学意义(P <0.05),B组、C组、D组三组组间比较,差异无统计学意义(P> 0.05)。四组患者不良反应发生率比较,差异无统计学意义(P> 0.05)。结论:术后48 h撤销静脉镇痛泵对患者疼痛情况改善良好,可缩短患者住院时间,而延长镇痛泵使用时间无法带来显著的益处。

COSINE软件包中子动力学程序KIND的点堆动力学模块设计

围绕实现点堆动力学程序工程化设计的问题,简介了COSINE软件包的点堆动力学计算模块。关于点堆算法的选取,本文对比了显式方法和去刚性算法计算各种典型瞬态问题的结果。结果表明,上述两种算法能充分满足设计可靠性的要求。关于反应性模型的设计,本文简介了全面覆盖各种反应性引入形式和反馈形式的设计思想。此外,还简介了本模块内置的热工模型。本文点堆动力学模块的设计具有良好的可靠性和灵活性。

A Note on Discontinuous Functions with Continuous Second Iterate

This paper investigates four classes of functions with a single discontinuous point. We give the sufficient and necessary conditions under which the second order iterates are continuous functions. Furthermore, the sufficient conditions for the continuity of the even order iterates with finitely many discontinuous points are obtained.

COSINE软件包中子动力学程序KIND的设计与开发

中子动力学程序KIND是COSINE软件包的一部分,它基于堆芯物理分析程序CORE,用于反应堆物理设计中的瞬态计算与事故分析。KIND包含了点堆和时空动力学两种计算模式,能模拟从零维到三维的压水堆堆芯。本文简单介绍了KIND程序的基本设计思想,包括程序架构、理论模型、开发规范等。

基于无人机贴近测量的露天矿岩质边坡结构面自动识别

获取岩质边坡结构面特征是露天矿山开展边坡稳定性分析的关键工作,传统的工程调查手段容易受到边坡地形限制,存在作业风险高、效率低等问题。为高效、安全地获取露天矿岩质边坡的精确结构面特征,利用无人机倾斜测量与贴近摄影测量技术开展了露天岩质边坡测量工作,构建了边坡的精细三维点云模型。通过进行边坡点云数据滤波、特征值获取以及基于区域生长法的平面分割分析,实现了基于点云数据结构面参数的识别与提取,形成了一种基于无人机获取岩质边坡结构面的自动、高精度测量方法,并在攀枝花铁矿尖山矿区北部边坡开展了工程实例验证。研究表明:基于无人机测量获取符合工程精度要求的边坡三维点云数据,采用结构面自动识别方法可快速地从边坡点云数据中获取岩体结构面信息,为边坡稳定性分析与评价提供了基础数据。

隧道掌子面节理点云识别及微服务模块开发

快速识别岩体隧道掌子面不连续面的点云信息并解译其几何与力学参数是实现隧道远程诊断的重要基础。目前基于数码相片的三维点云识别严重依赖商业程序,本文基于计算机视觉开源框架,自主开发了隧道掌子面不连续面点云信息识别的微服务模块。该微服务模块基于Django框架封装,可灵活部署于任一具有微服务架构的隧道安全诊断平台中,根据用户在线输入的不同视角下隧道掌子面岩体相片,可自动识别三维点云并实现三维重构。该微服务模块已部署于同济大学基础设施智慧服务系统(iS3)中,点云识别结果与其他程序进行了对比,结果表明,该微服务模块能满足基本的三维重构功能要求,在点云识别速度方面具有优势,未来在计算精度方面仍存在提升空间。

A non-contact measurement method for rock mass discontinuity orientations by smartphone

Smartphones are usually packed with a large number of features.An increasing number of researchers are paying attention to the technological capabilities of smartphones,which is a new topic and research interest.This paper proposes a method using smartphones and digital photogrammetry to measure the discontinuity orientation of a rock mass.Smartphone photos satisfying a certain overlap rate provide an efficient method for generating point cloud models of rock outcrops based on image matching.Using the target and the generated point cloud model allows for determining actual geographic coordinates and the measurement of discontinuity orientations.The method proposed has been applied to two different study areas.The discontinuity orientations measured by the proposed method are compared with those measured by the manual method in two cases.The results show a good agreement,verifying the reliability and accuracy of the proposed method.The main contribution of this paper is to use knowledge of coordinate rotation to determine the actual geographic location of the model through a square target.The equipment used in this study is simple,and photogrammetric field surveys are easy to carry out.

基于指向误差与不同噪声的星地激光通信系统误码性能分析

为了研究在大气湍流、指向误差以及各种噪声的共同影响下的星地激光通信系统平均误码率性能,采用Gamma-Gamma信道模型,建立了大气湍流与指向误差的组合衰减模型,并结合各种噪声推导出关于组合衰减模型的星地激光通信系统平均误码率的闭合表达式。研究结果表明,当卫星轨道高度为400 km、天顶角为45°、波长为1550 nm以及等效波束半径和指向误差位移标准差(抖动)的归一化比值为4时,总噪声、热噪声、背景噪声对应的平均误码率分别为1.519×10^(-7)、6.907×10^(-8)、1.357×10^(-8)。

New method to identify optimal discontinuity set number of rock tunnel excavation face orientation based on Fisher mixed evaluation

Discontinuity is critical for strength,deformability,and permeability of rock mass.Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping.Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes,which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation.This paper proposes a new method of Fisher mixed evaluation(FME)to identify optimal group numbers of rock mass discontinuity orientation.In FME,orientation distribution is regarded as the superposition of Fisher mixed distributions.Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions,the probability monopoly and central location significance of independent Fisher centers.A Halley-Expectation-Maximization(EM)algorithm is derived to achieve an automatic fitting of Fisher mixed distribution.Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping.Four clustering validity indexes are used to automatically identify optimal group numbers for comparison.The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.