油田高含水期基于微观渗流机理的宏观岩心水驱油数值模拟研究

建立地层孔隙网络模型描述微观孔喉特征,利用逾渗方法计算基于微观渗流机理的相对渗透率曲线,并将之应用到数值模拟计算中,给出考虑微观渗流特征的方程,并进行数值求解,得到地层中流体分布特征。实例分析表明该方法可以得到基于微观特征的剩余油分布数量和形式,为调剖堵水、化学驱提供技术参数,实现微观渗流机理与宏观计算的结合。     

A Study on the Spectral Form of Nearshore Water Waves

- The spectral form of wind waves is investigated based on the ocean wave data observed at three nearshore stations of Taiwan. In this study, the generalized forms of Pierson-Moskowitz spectrum and JONSWAP spectrum are used to describe the local wave spectrum by selecting suitable spectral form parameters. It is shown that, at a specific site, the similarity of wave spectral form exists. Thus it is possible to use a representative spectral form for a given nearshore region to describe the wave spectrum at this nearshore. On the other hand, the effects of relative water depth on spectral form are examined. The feasibility of two spectral models in finite water depth is evaluated by using the same field wave data.     

高校GIS专业课程设置的探索

通过对高校地理信息系统(简称GIS)专业基础理论、基本方法、应用技术、与学科最新发展前沿的深入分析,结合GIS专业学生的知识结构体系,提出了一种新的GIS专业基础课和专业课的设置,在对GIS人才的特点和能力培养途径提出了自己建议的同时,对课程内容及教学形式等相关问题进行了相应地探讨。     

湿法冶锰废渣中锰的形态分析与应用

将湿法冶锰废渣经过烘干、研细等预处理,按其所使用的原材料进行形态研究,通过筛选和实验,确定了废渣中的锰可用形态分析方法。在弄清废渣中锰的各种形态及含量的基础上,将其成果进行转化,用于指导工业生产、环境评价和废渣处理,具有很好的经济效益和社会效益。     

Open source, spatial analysis, and activity-travel behaviour research: capabilities of the aspace package

This paper reports on recent experience with the development of aspace, an Open Source (OS) library for the geographic visualization and analysis of activity-travel behaviour. The paper begins with an overview of recent progress with respect to the convergence of Open Source technology, spatial analysis, and travel behaviour research. The remainder of the paper focuses on aspace; a collection of functions that, when combined with data describing the geographical location of daily activities, can be used to visualize and describe spatial properties of individual and household activity spaces. These properties include: size, orientation, shape, and the geographical dispersion of activity locations contained within the activity space. Several planar geometries are used to transform measurable spatial properties into intuitive objects for visualizing spatial patterns of activity participation. Experiments are conducted, using data from the first wave of the 2003 Toronto Travel Activity Panel Survey, to demonstrate the potential application of aspace for basic and applied policy-based research into activity-travel behaviour. The toolkit is distributed as a downloadable ‘package’ from the Open Source R Project for Statistical Computing.      

基于LongruanGIS的电子地质报告系统的设计与实现

基于LongruanGIS3．0开发的电子地质报告系统包括数据库管理系统、图形处理系统和文字表格处理系统三部分。在介绍该系统的总体设计、功能实现和系统特点的基础上,总结了该软件的几方面优势：具有数据共享、数据集成、自动成图、功能开放的技术优势;具有开放的数据交换格式以及将CAD与GIS软件结合起来的强大图形编辑、查询、空间分析功能。     

梁子湖水体P的季节变化与沉积物P释放初步研究

采用分级测定的方法对梁子湖沉积物中无机磷酸盐进行了分析,测定了梁子湖水体P的季节变化,并以室内模拟的方法研究梁子湖沉积物在pH值和温度控制下P的释放特征。研究表明,梁子湖水体P的含量呈明显的季节变化,冬季高,夏季低。沉积物无机磷(P i)中以钙磷(Ca—P)为主(55%~61%),铁磷(Fe—P)次之(28%~33%),铝磷(A l—P)最少(3%~5%)。在梁子湖的入水口和出水口,由于沉积环境影响到P的形态,P的释放明显较湖心高。在试验初期,由于扰动的影响,使得P的释放在第1天比第2天和第3天高,其后P的释放量则迅速增加。温度对P释放影响明显,其具体表现为,30℃时P释放达到峰值的时间比4℃时提前4 d,而且前者峰值比后者高出9倍。pH值对沉积物P释放同样有明显的影响,与正常状态下的湖水条件(pH值为8.5)相比,偏酸(pH值为5.5)和偏碱(pH值为11.5)条件下,P的释放量增加。     

青海热水柴达尔井田构造组合型式

柴达尔井田构造可分为压缩机制的推覆构造与伸展机制的断块体两类。南北F0为逆冲型的控制性边界断裂，井田内部一系列小型弧形构造为逆掩型浅层断裂；F1、F2、F17，是拉伸作用下的同沉积正断层，切断煤系基底T3地层。其动力机制为印度板块向北推移、西伯利亚板块向南运移发生对挤，脆一韧性剪切变形导致了井用现有的构造组合形式。     

地震快报系统

本文简述了开发地震快报系统的主要技术。     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.