P‐wave transmission across fractures with nonlinear deformational behaviour

Stress wave attenuation across fractured rock masses is a great concern of underground structure safety. When the wave amplitude is large, fractures experience nonlinear deformation during the wave propagation. This paper presents a study on normal transmission of P‐wave across parallel fractures with nonlinear deformational behaviour (static Barton–Bandis model). The results show that the magnitude of transmission coefficient is a function of incident wave amplitude, nondimensional fracture spacing and number of fractures. Two important indices of nondimensional fracture spacing are identified, and they divide the area of nondimensional fracture spacing into three parts (individual fracture area, transition area and small spacing area). In the different areas, the magnitude of transmission coefficient has different trends with nondimensional fracture spacing and number of fractures. In addition, the study reveals that under some circumstances, the magnitude of transmission coefficient increases with increasing number of fractures, and is larger than 1. Copyright © 2006 John Wiley & Sons, Ltd.     

Seasonal variations in prey selection by estuarine black-headed gulls (Larus ridibundus)

The number of black-headed gulls (Larus ridibundus) in the Clyde Estuary is large. In summer the average density has reached 1350 gulls km^?2 and in winter 180 gulls km^?2. This paper compares prey selection and feeding efficiency in gulls during summer and winter on tidal flats, and considers how seasonal differences may be adaptations to cope with seasonal changes in prey availability.Gross and net rates of energy intake were highest in summer because gulls captured more of the polychaete N. diversicolor than the amphipod C. volutator. In winter, gulls selected for C. volutator and therefore an energetically less profitable diet. Throughout the year gulls selected more C. volutator relative to N. diversicolor than expected on energetic grounds and so apparently did not maximize potential net rate of energy intake.Gulls used three techniques to capture prey and made most intensive use of the ‘crouch’ technique. Crouching gulls attained a much higher net rate of energy intake than ‘upright’ or ‘paddling’ gulls.A log-linear model showed that (a) season, water depth and gull density determined feeding technique and (b) feeding technique and season independently determined foraging success and prey selection. Thus gull density and water depth acted on prey selection through imposed variations in feeding technique.Reasons for gulls selecting energetically unprofitable C. volutator and for the use of several distinct feeding techniques are discussed.     

Generalized strain probing of constitutive models

Advanced material constitutive models are used to describe complex soil behaviour. These models are often used in the solution of boundary value problems under general loading conditions. Users and developers of constitutive models need to methodically investigate the represented soil response under a wide range of loading conditions. This paper presents a systematic procedure for probing constitutive models. A general incremental strain probe, 6D hyperspherical strain probe (HSP), is introduced to examine rate‐independent model response under all possible strain loading conditions. Two special cases of HSP, the true triaxial strain probe (TTSP) and the plane‐strain strain probe (PSSP), are used to generate 3‐D objects that represent model stress response to probing. The TTSP, PSSP and general HSP procedures are demonstrated using elasto‐plastic models. The objects resulting from the probing procedure readily highlight important model characteristics including anisotropy, yielding, hardening, softening and failure. The PSSP procedure is applied to a Neural Network (NN) based constitutive model. It shows that this probing is especially useful in understanding NN constitutive models, which do not contain explicit functions for yield surface, hardening, or anisotropy. Copyright © 2004 John Wiley & Sons, Ltd.     

A micromechanical finite element model for linear and damage‐coupled viscoelastic behaviour of asphalt mixture

This study presents a finite element (FE) micromechanical modelling approach for the simulation of linear and damage‐coupled viscoelastic behaviour of asphalt mixture. Asphalt mixture is a composite material of graded aggregates bound with mastic (asphalt and fine aggregates). The microstructural model of asphalt mixture incorporates an equivalent lattice network structure whereby intergranular load transfer is simulated through an effective asphalt mastic zone. The finite element model integrates the ABAQUS user material subroutine with continuum elements for the effective asphalt mastic and rigid body elements for each aggregate. A unified approach is proposed using Schapery non‐linear viscoelastic model for the rate‐independent and rate‐dependent damage behaviour. A finite element incremental algorithm with a recursive relationship for three‐dimensional (3D) linear and damage‐coupled viscoelastic behaviour is developed. This algorithm is used in a 3D user‐defined material model for the asphalt mastic to predict global linear and damage‐coupled viscoelastic behaviour of asphalt mixture. For linear viscoelastic study, the creep stiffnesses of mastic and asphalt mixture at different temperatures are measured in laboratory. A regression‐fitting method is employed to calibrate generalized Maxwell models with Prony series and generate master stiffness curves for mastic and asphalt mixture. A computational model is developed with image analysis of sectioned surface of a test specimen. The viscoelastic prediction of mixture creep stiffness with the calibrated mastic material parameters is compared with mixture master stiffness curve over a reduced time period. In regard to damage‐coupled viscoelastic behaviour, cyclic loading responses of linear and rate‐independent damage‐coupled viscoelastic materials are compared. Effects of particular microstructure parameters on the rate‐independent damage‐coupled viscoelastic behaviour are also investigated with finite element simulations of asphalt numerical samples. Further study describes loading rate effects on the asphalt viscoelastic properties and rate‐dependent damage behaviour. Copyright © 2006 John Wiley & Sons, Ltd.     

Effect of non-linear soil deformation on the interaction among energy piles

This study investigates the effect of non-linear soil deformation on the displacement interaction among energy piles. The work is based on interaction factor analyses of full-scale pile group tests, whose results are compared with experimental evidence. The results presented highlight the tendency of interaction factor analyses that ignore non-linear soil deformation to overestimate the interaction and the displacement of energy pile groups. This outcome, in accordance with previous studies for conventional pile groups subjected to mechanical loads, may be considered in the analysis and design of energy pile groups subjected to thermal (and mechanical) loads through the interaction factor method.     

面向电网巡检的多旋翼无人机航测系统关键技术研究及应用

针对无人机电力巡检所面临的定位精度低、近距离巡检操控难度大、自动化程度低、人为操控事故风险高等问题,本文提出了利用多旋翼无人机RTK差分定位技术、复杂塔型飞行规则机器学习算法等无人机航测系统技术,研发面向电网巡检的无人机智能操作系统及控制终端,提升电网线路日常管理和应急指挥的规范性、便利性和经济性,为电网管理部门提供一种低成本、易操作、高效率、机动灵活的新型巡检模式。     

混合核特征加权SVM遥感湿地空间分类

针对湿地空间信息的复杂性和SVM的分类性能,设计一种基于混合核函数的特征加权SVM分类模型,综合利用多种特征信息,避免被弱相关特征所支配,从而提供更佳的映射性能和泛化能力。实验结果表明,该分类模型兼具良好的外推和内推能力,能够有效地融合不同信息源特征,得到更完整和准确的分类结果,在总体精度、Kappa系数等多项指标上都表现出更高的水平。     

人工心肺机流量计的研制

本文介绍了如何应用单片微型计算机和光电传感器组成人工心肺机(或称体外循环机)流量计。该仪器对人工心肺机的泵的各种转速能够准确地采集,对不同的患者能够精确地计算出所需血液流量,从而定量地控制输送给病人的血液流量,以保证心脏手术顺利进行,改变了临床手术时手工计算的落后情况。流量计是一台新型的智能化仪表。     

盾构机轴线方位角解算原理研究

以德国VMT公司的TMB制导系统SLS-T为例,主要解析了盾构机轴线方位角测量原理,并完整地推导了盾构机姿态参数公式。由于国外导向系统的核心原理不公开,因此本文的研究成果,为隧道施工工程技术人员深入理解激光导向系统原理以及开发国产的自动导向系统提供了理论基础。     

基于机器学习的稀疏样本下的土壤有机质估算方法

采用GRNN（Generalized Regression Neural Network）和RF（Random Forest）2种机器学习方法构建土壤有机质预测模型,以提高稀疏样本情况下的土壤有机质估算精度。依据北京市大兴区农用地2007年的土壤有机质采样数据,按MMSD准则（Minimization of the Mean of the Shortest Distances）抽稀为8种不同采样密度的样本（分别为2703、1352、676、339、169、85、43、22个样本）,分别采用GRNN、RF和Ordinary kriging对各采样密度下的未知采样点进行预测,采用交叉检验的方式验证各采样密度下未知样点的预测精度。随着采样点密度的下降,样点间的空间自相关性逐渐减弱,半变异函数的拟和精度变差,预测点结果误差增大,预测的置信度降低。当抽稀到43个和22个采样点时,样点间的空间自相关性接近歼灭,半变异函数的决定系数较低且残差较大。普通克里格受到采样点数量和采样密度、样点的空间结构的影响比较明显,其预测精度随采样点数量的下降而下降。在85个采样点及以下时,其预测值与观测值之间没有显著的相关性。GRNN和RF的预测精度受采样密度的影响不大,其预测精度在一个较小的范围内波动,其预测值围绕观测值在一定阈值空间内震荡波动,具有较好的相关性,在85个及以下的采样密度时,预测精度相对普通克里格有较大的提升。普通克里格法不适合在稀疏样本条件下空间插值计算,尤其是在空间自相关性比较弱的情况下。机器学习模型能充分学习土壤间环境信息、样点空间邻近效应信息,兼顾属性相似性和空间自相关,具有更好的稳定性和适应性,不容易受到采样点数量、构型和采样密度等因素的影响,即使在采样点空间自相关性很弱的情况下也能做出稳定预测精度。