SANICLAY: simple anisotropic clay plasticity model

SANICLAY is a new simple anisotropic clay plasticity model that builds on a modification of an earlier model with an associated flow rule, in order to include simulations of softening response under undrained compression following K_o consolidation. Non‐associativity is introduced by adopting a yield surface different than the plastic potential surface. Besides, the isotropic hardening of the yield surface both surfaces evolve according to a combined distortional and rotational hardening rule, simulating the evolving anisotropy. Although built on the general premises of critical state soil mechanics, the model induces a critical state line in the void ratio–mean effective stress space, which is a function of anisotropy. To ease interpretation, the model formulation is presented firstly in the triaxial stress space and subsequently, its multiaxial generalization is developed systematically, in a form appropriate for implementation in numerical codes. The SANICLAY is shown to provide successful simulation of both undrained and drained rate‐independent behaviour of normally consolidated sensitive clays, and to a satisfactory degree of accuracy of overconsolidated clays. The new model requires merely three constants more than those of the modified Cam clay model, all of which are easily calibrated from well‐established laboratory tests following a meticulously presented procedure. Copyright © 2006 John Wiley & Sons, Ltd.     

一种树型网络拓扑简图的生成算法

给出一种树型网络拓扑的语义描述方法及其拓扑简图的生成算法。该方法通过建立网络联接线路标识串集和网络设备连接标识串集，来构造网络设备的拓扑描述，并计算生成网络拓扑简图。     

一种产生Fuzzy拓扑和Smooth拓扑的方法及其应用

利用邻域度给出了1种由fuzzy拓扑产生smooth拓扑的方法;利用smooth拓扑的自身结构给出了smooth拓扑产生fuzzy拓扑的方法,讨论了它们在映射间的联系并引入了强smooth拓扑并获得了一些重要结果.     

引入差比关系法分析西北太平洋TOPEX/POSEIDON卫星高度计测高数据

TOPEX/POSEIDON(T/P)卫星高度计数据信息中存在周期成分混淆问题.对其中的一类混淆引入差比关系方法对混淆的分潮进行分离.卫星轨道交叉点资料包括升轨和降轨资料,资料量比沿轨点资料多1倍,经分析发现:在已有为期6a多的观测资料时间序列中,在沿轨处混淆的分潮如K₁和SSA在交叉点处不再混淆,可以直接分离.因此首先对交叉点资料进行调和分析.然后由交叉点的分析结果得到分潮间的差比关系,处理到相近的沿轨点处,从而得到沿轨点的调和常数.用引入差比关系方法,对西北太平洋海区6a多的T/P卫星高度计资料进行了潮汐分析,并与沿岸及岛屿验潮站资料进行了比较,所得结果较满意.     

模糊化(拓扑)导算子的公理化

将模糊化(拓扑)导算子进行了公理化，并且给出了若干模糊化(拓扑)导算子的刻画；同时建立了模糊化(拓扑)导算子和模糊化(拓扑)闭包算子之间的关系。     

一类序同态的构造

作者定义了从L_1~X到L_2~Y的映射σ,证明了σ是满足σ(x_λ~0)=σ(λ)∧σ(x_(I_1)~0)的保并映射的充要条件是σ(A)=∨g(λ)∧f(Aλ),其中f为X到L_1~Y的映射,g为L_1到L_2~Y的保并映射,且有f(X)≤g(I_1);最后证明了一类序同态的分解定理,它们是前人相应结果的推广与补充。     

一种基于异步串行口的IBM-PC局部网

在综合的科学考察船上以异步通讯口实现的IBM-PC局部网具有较好的性能价格比。本文介绍了该网的联网环境、网络系统的组成及其拓扑结构、网络的服务功能以及网络软、硬件的安装和配置。     

海洋平台结构形状与拓扑优化设计

以实际环境荷载作用下的实际海洋导管架平台结构为对象，研究了海洋平台结构在风，流，海冰等多荷载模式和多荷载工况下的优化设计的理论方法和应用技术，建立了结构尺寸优化，形状优化和拓扑优化问题的统一模型。计算结果反映出形状优化比尺寸优化所得设计更优，而拓扑优化的设计效果最好。不同的荷载工况对应的最优拓扑形式不同，因此在实际设计中应考虑实际的荷载工况，选取不同的拓扑形式。     

A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.     

Using Topological Relationships to Inform a Data Integration Process

When spatial datasets are overlaid, corresponding features do not always coincide. This may be a result of the datasets having differing quality characteristics, being captured at different scales or perhaps being in different projections or datums. Data integration methods have been developed to bring such datasets into alignment. Although these methods attempt to maintain topological relationships within each dataset, spatial relationships between features in different datasets are generally not considered. The preservation of inter‐dataset topology is a research area of considerable current interest. This research addresses the preservation of topology within a data integration process. It describes the functional models established to represent a number of spatial relationships as observation equations. These are used to provide additional information concerning the relative positions of features. Since many topological relationships are best modelled as inequalities, an algorithm is developed to accommodate such relationships. The method, based on least squares with inequalities (LSI), is tested on simulated and real datasets. Results are presented to illustrate the optimal positioning solutions determined using all of the available information. In addition, updated quality parameters are provided at the level of the individual coordinate, enabling communication of local variation in the resultant quality of the integrated datasets.