A multi‐level parallelized substructuring‐frontal solution for coupled thermo/hydro/mechanical problems in unsaturated soil

This paper proposes a multi‐level parallelized substructuring–frontal combined algorithm for the analysis of the problem of thermo/hydraulic/mechanical behaviour of unsaturated soil. Temperature, displacement, pore water pressure and pore air pressure are treated as the primary variables in a non‐linear analysis. Details are given firstly of the substructuring–frontal combined approach. The incorporation of the algorithm in a multi‐level parallel strategy is then discussed. The parallel processing can thus be carried out at different substructural levels. The method thus developed impacts, in a positive way, on both computer storage requirement and execution time. Copyright © 2003 John Wiley & Sons, Ltd.     

基于神经网络的平底结构砰击压力预报

对利用神经网络预报平底结构入水砰击压力的方法进行了探讨。首先利用仿真软件计算各种情况下平底结构入水所产生的砰击压力，以此形成训练神经网络的数据集。其次利用数据集对三层反馈式网络进行了训练，讨论了不同隐含层节点数对该非线性系统的拟合能力，并且对梯度下降法、动量修正法和基于优化的LM算法的有效性和精度进行了比较，最后得出了适合平底结构入水砰击系统的网络结构。     

Influence of large-diameter pipe pile driving on surrounding marine soils and adjacent submarine pipelines

Abstract

With the large-scale development and utilization of ocean resources and space, it is inevitable to encounter existing submarine facilities in pile driving areas, which necessitates a safety assessment. In this article, by referring to a wharf renovation project as a reference, the surrounding soil response and buried pipe deformation during pile driving in a near-shore submarine environment are investigated by three-dimensional (3D) numerical models that consider the pore water effect. Numerical studies are carried out in two different series: one is a case of a single pile focusing on the effect of the minimum plane distance of the pile–pipe, and the other is a case of double piles focusing on the effect of the pile spacing.     

渤海、黄海强温跃层数值预报模式

文中对前人关于水温垂直结构计算、模拟和预报研究成果进行了评价，并在此基础上建立了考虑海面吸收辐射和透射辐射、地形、风、海流、界面摩擦及其引起的混合作用的强温跃层三维数值预报模式。该模式运行的驱动量仅为风和气温场资料，因而具有较好的实用性；此外，从试报的结果看，效果是令人满意的。     

能量分析在台风短期预报业务中的应用

本文以９４１４、９４１５号两个连续北上台风为例，证明能量场的分布与台风移向有着明显的对应关系。     

GIS在处置地下管线突发事件中的应用研究——以苏州市地下综合管网应急处置系统为例

随着经济社会的不断发展,城市建设步伐不断加快。近几年,各类地下管线突发事件频发。通过"苏州市地下综合管网应急处置系统"项目的开发和实践,本文试图从总体上论述地下综合管网突发事件的处置过程、应用原理及相关的技术实现,重点阐述了基于"12345"便民服务中心工作平台,在充分利用GIS的网络分析技术的基础上,实现城市地下管网突发事件应急处置的自动化和信息化。     

地震综合效应场函数及其在地震预报中的应用──（一）地震综合效应场函数及其计算方法

在系统地分析了目前各种测震学地震预报方法科学思路的基础上,认为测震学地震预报方法基本上可以分为两大类。一类是以已经发生的一些地震作为未来可能发生的地震的“因”,即由于已经发生的地震对区域应力场的影响,导致未来发生较强地震。这一类包括的预报方法较多,如空区、条带、ｂ值、地震迁移、相关地震等等及其由此衍生出来的各种方法。另一类是把已经发生的一些地震作为区域应力场增强的“果”,即已经发生的地震是区域应力场增强过程中的一种反映,而未来地震不一定是已经发生的地震所导致的结果。这一类包括“地震窗口”、小震群活动等方法。针对第一类方法,各种预报方法都是力图从地震三要素中提取未来地震的信息,而具体作法又都是利用地震三要素这个多维空间的某个剖面。为了从地震活动诸要素的多维空间提取综合信息,我们对每个地震加入了破裂面方位,构成了地震第四要素,并依据地震４要素建立了地震综合效应场函数。地震综合效应场函数概括了多种测震学地震预报方法的科学思路和预报经验,从而可以形成测震学的综合预报方法。     

Prediction of the occurrence of Related Strong Earthquakes in Italy

In the seismic flow it is often observed that a Strong Earthquake (SE), is followed by Related Strong Earthquakes (RSEs), which occur near the epicenter of the SE with origin time rather close to the origin time of the SE. The algorithm for the prediction of the occurrence of a RSE has been developed and applied for the first time to the seismicity data of the California-Nevada region and has been successfully tested in several regions of the world, the statistical significance of the result being 97%. To date it has been possible to make five successful forward predictions, with no false alarms or failures to predict.The algorithm is applied here to the Italian territory, where the occurrence of RSEs is a particularly rare phenomenon. Our results show that the standard algorithm is successfully directly applicable without adjustment of the parameters. Eleven SEs are considered. Of them, three are followed by a RSE, as predicted by the algorithm, eight SEs are not followed by a RSE, and the algorithm predicts this behaviour for seven of them, giving rise to only one false alarm. Since, in Italy, often the series of strong earthquakes is relatively short, the algorithm has been extended to handle such a situation. The result of this experiment indicates that it is possible to attempt to test a SE, for the occurrence of a RSE, soon after the occurrence of the SE itself, performing timely preliminary recognition on reduced data sets. This fact, the high confidence level of the retrospective analysis, and the first successful forward predictions, made in different parts of the World, indicates that, even if additional tests are desirable, the algorithm can already be considered for routine application to Civil Defence.     

“煤特征指数”与矿井瓦斯危险类型的关系

矿井瓦斯危险程度与煤层中瓦斯赋存状况及其泄出方式有关,并取决于多种地质条件和采掘工艺。其中,煤特征条件特别重要。本文分析了湖南省的5种矿井瓦斯危险类型以及相应的煤特征条件,提出了“煤特征指数(I_c)”这一概念。I_c是一项评价矿井瓦斯危险程度的综合指标。研究表明,矿井瓦斯危险愈严重,则其I_c值愈高。应用该项成果预测了16对矿井的瓦斯危险类型,取得了满意的效果。     

Comparison of structural and least-squares lines for estimating geologic relations

Two different goals in fitting straight lines to data are to estimate a true linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating true straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal—predicting the dependent variable—OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples.