A critical state model for sands dependent on stress and density

An elastoplastic model for sands is presented in this paper, which can describe stress–strain behaviour dependent on mean effective stress level and void ratio. The main features of the proposed model are: (a) a new state parameter, which is dependent on the initial void ratio and initial mean stress, is proposed and applied to the yield function in order to predict the plastic deformation for very loose sands; and (b) another new state parameter, which is used to determine the peak strength and describe the critical state behaviour of sands during shearing, is proposed in order to predict simply negative/positive dilatancy and the hardening/softening behaviour of medium or dense sands. In addition, the proposed model can also predict the stress–strain behaviour of sands under three-dimensional stress conditions by using a transformed stress tensor instead of ordinary stress tensor. Copyright © 2004 John Wiley & Sons, Ltd.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

COORDINATING DEVELOPMENT OF AGRICULTURAL RESOURCES AND ENVIRONMENT OF THE TROPIC REGION IN YUNNAN PROVINCE

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STUDY ON BEIJING''''S EMERGING MOBILE COMMUNICATION INDUSTRIAL CLUSTER AND ITS POLICY IMPLICATIONS

1INTRODUCTIONClusters,definedasgeographicallyproximategroupsofinterconnectedcompaniesandassociatedinstitutionsinparticularfields,linkedbycommonalitiesandcomple-mentarities(PORTER,2000),havearousedanintenseinterestofurbanandregionalplanningresearchersandpolicymakersoverthepastdecades.Itiswidelyrecog-nizedthatclusterscanpromoteproductivityandinno-vation,developlocalcompetitiveadvantages.Popular-izedbyMichaelPORTERinhisbook“TheCompetitiveAdvantageofNationsin1990,theclusterisnotanewcon…     

高能偏振能量色散X射线荧光光谱仪应用现状和进展

对高能偏振能量色散X射线荧光光谱仪基本特点及其用于环境、生物、地质样品中痕量元素的分析和RoSH检测等领域的应用现状予以介绍,并对二次靶与滤光片在痕量元素分析中的应用作了探讨。     

舟山国家石油储备基地堆载预压加固效果分析

介绍了舟山国家石油储备基地试验区软基堆载预压大型现场试验结果,根据现场试验测得的数据,分析了软土地基堆载预压下沉降变化规律、分层沉降变化规律、深层土体位移变化规律、超静孔隙水压力变化规律,进一步探讨了根据应力和应变分析得到的地基固结性状,其中通过应变分析得到适用于储备基地的沉降经验系数m。结果表明,打设塑料排水板结合堆载预压处理软弱地基具有良好的效果。     

案例推理技术及其在决策科学中的应用研究

CBR技术反映了人类认知科学研究的新成果,强调了人类时过去经验和前人智慧的重现.并依靠它们指导解决实际工作中遇到的新问题.基于案例推理特别适用于领域定理难以表示成规则形式,而易表示成案例形式并且已积累了丰富案例的领域.文章探讨了决策问题与决策模式,研究了基于案例技术的科学决策过程,提出了应用案例智能技术来解决决策科学中的柔性决策难题.     

奎屯河流域南洼地地下水补给特征分析

独山子石油化工基地第二水源地(简称二水源)位于新疆奎屯河流域南洼地,认识和掌握南洼地地下水补给特征是研究和评价独山子石化基地用水保障程度的重要基础。通过南洼地地下水和主要河流的水化学、环境同位素特征分析,对南洼地地下水的补给得到如下认识:二水源西北缘和中部主要接受奎屯河、小巴音沟水的补给,其东南缘主要接受乌兰布拉克沟和乔路特沟地表水的补给;就整个二水源来讲,奎屯河与小巴音沟的补给是主要的。     

嵩县螃蟹沟隐爆角砾岩体与钼金矿化成因探讨

螃蟹沟隐爆角砾岩体是河南省嵩县西北部众多含钼、金角砾岩体之一,这些角砾岩体具有成群、成带分布的特点.螃蟹沟角砾岩体的定位与分布受北西向背形、北西向和北东向断裂构造的复合控制,由燕山期钙碱性岩体与岩脉的侵入,以及随后发生的隐蔽爆发-坍塌作用而生成了角砾岩体.其中包括了震碎角砾岩、隐爆角砾岩、侵入角砾岩及坍塌角砾岩.岩体被后期断裂构造作用所复合叠加,致使钼、金富集成矿,形成"多型一体"的钼金矿床.     

我国核燃料循环产业面临的挑战和机遇

本文设计了一个到2050年我国核电发展的参考情景,分析了国内外核燃料循环产业的各个环节的规模和状况,阐述了我国核燃料循环产业面临的挑战和机遇.