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

（姚建衢）（杨焕宗）ＣＯＯＲＤＩＮＡＴＩＮＧＤＥＶＥＬＯＰＭＥＮＴＯＦＡＧＲＩＣＵＬＴＵＲＡＬＲＥＳＯＵＲＣＥＳＡＮＤＥＮＶＩＲＯＮＭＥＮＴＯＦＴＨＥＴＲＯＰＩＣＲＥＧＩＯＮＩＮＹＵＮＮＡＮＰＲＯＶＩＮＣＥ￥ＹａｏＪｉａｎｑｕ（Ｉｎｓｔｉｔｕｔｅｏｆ...     

Studies on the distribution and antibacterial properties of Streptomyces in the intertidal zone of Southern Fujian

The oceans have rich resources of microbes. In recent years, searching for antibiotic of new structure and special biological activity from marine microbes has received great attention. This paper reports the results of the studies on the distribution and the antibacterial properties of Streptomyces in the intertidal zone of Southern Fujian. These studies have important significance to further investigate     

厦门筼筜港的形成与演变

本文根据实际调查的资料,概述了筼筜港区的地质地貌特征,重点论述了第四纪沉积物的成因和时代,阐述了该区的形成与演变过程,把它划分为5个发育阶段。     

I(L)值完全诱导空间

作者引入 I(L)值完全下半连续映射 ,研究其性质。利用 I(L)值完全下半连续映射定义I(L)值完全诱导空间 ,给出 I(L)值完全诱导空间的拓扑基的表达形式 ,证得两个 I(L)值完全诱导空间的映射是连续映射的充分必要条件 ,并建立了乘积空间的 I(L)值完全诱导空间与 I(L)值完全诱导空间的乘积空间的联系     

聚类分析在海洋产业分析中的应用

聚类分析是多元统计分析中的一种方法,是将数学引入分类学形成的,比以前仅凭经验及专业知识进行分类更为科学、适用.用聚类分析方法分析研究沿海地区海洋产业状况是较高层次统计知识的运用,也是对数据挖掘技术的一种探索性研究.本文仅从产值的角度考虑地区海洋经济实力的状况,是利用聚类分析方法、借助海洋经济统计数据对地区海洋经济的实证研究.     

南海西沙西南海域表层沉积物特征

西沙西南海域表层沉积物样品矿物成分，地球化学，微体古生物分析测试结果表明：沉积物可分为７种类型，沉积环境主要是陆坡，部分为深海平原，海洋生物，海洋化学以及火山物质的沉积起到了积极的作用，陆源物质的影响较小，它们主要来源于北部大陆和南部岛礁等物源区。     

葫芦岛地区道路网络的建立

本文针对城市交通道路网的特点,根据现实的交通网络,对葫芦岛地区道路网络进行建立及分析。利用ArcGIS中的Geodatabase构建路网数据库,利用节点一弧段数据结构构建空间网络拓扑关系,生成点一弧矢量数据模型表示的道路网络。并实现四种网络分析功能:最佳路径分析、空间查询、追踪分析和缓冲区分析。     

地铁隧道结构变形监测信息管理系统的开发

地铁隧道结构变形监测的特殊性、周期性和长期性,使其信息量非常庞大.信息管理是地铁隧道结构变形监测中一项重要的工作,现有的管理方式效率很低.为了高效、准确地管理监测信息,及时分析预报地铁隧道结构的稳定状况,本文结合南京地铁运营期隧道结构变形监测实例,开发了一套具有变形监测资料存储、预处理、管理分析、可视化分析、预测预报及限值预警等功能的信息管理系统,保证了准确及时快速的数据处理和信息反馈,具有良好的运用和推广前景.