岩土面上抗剪强度与破坏面位置

通过理论推导出在平面应变条件下岩土任意面上的抗剪强度通式和破坏时中主应力与大小主应力的关系,给出了破坏面位置与强度准则的一般关系。为岩土滑移面的确定提供了理论依据,对研究岩土强度准则具有指导意义。     

多组分等温吸附测试中的体积校正方法探讨

借助于单组分等温吸附特性测试中体积校正的原理和方法,提出多组分等温吸附测试的体积校正公式,同时对多组分吸附相的密度进行讨论并提出计算方法。通过例子表明,多组分吸附实验体积校正前后的相对误差小于纯甲烷。      

华南弧形海岸岸线形态与地貌发育模式

Coastline configuration indexes of 34 typical arc-shaped coasts in South China are investigated by the method of principal component analysis, and meanwhile deposition and geomorphologic features of arc-shaped coast are also analyzed. The results show: (1) The configuration of arc-shaped coast in South China is of the characteristic of variability and complexity. (2) The wave power and the openings of the bay are the decisive factors to result in the changes of the configuration of the arc-shaped coast in South China, however, incidence direction of the wave has no effect on configuration development of the coast. (3) Commonly, geomorphologic modes of the arc-shaped coast system in South China consist of barriers, lagoons and tidal-inlets, and can be divided into four types:the openings of the bay leaning to the east, the openings of the bay leaning to the south, the openings of the bay leaning to the west and the openings of the bay leaning to the north.     

贵州森林的空间格局及组成结构

利用ArcGIS,对贵州省2000年所作的森林资源连续清查遥感判读样点数据进行处理和分析,提取了森林资源分布图、林龄结构分布图、郁闭度分布图等系列森林景观图;分析结果表明：(1) 贵州森林植被类型多样,但覆盖率相对较低,全省森林覆盖率为25.27 % (不含疏林、灌木林、未成林造林地面积);(2) 森林地理分布不均匀,主要分布在黔东南及北部的遵义地区;(3) 地带性植被常绿阔叶林破坏严重,森林具有明显的次生性,表现为针叶林和灌木林所占比重大;(4) 林种结构的特点是用材林占比重大,防护林、经济林所占比重小;(5) 林龄结构的特点是幼中龄林为主,近成过熟林面积、蓄积比重都相对较小;(6) 贵州森林不能充分发挥森林植被对喀斯特山区生态环境的保护功能。     

基于统一强度理论的地基极限承载力公式

现有的地基临塑荷载及极限承载力公式均以Mohr-Coulomb强度理论为基础建立的,没有考虑中间主应力的效应,其计算结果一般偏小,没有充分发挥土体强度潜能。基于统一强度理论考虑中间主应力的影响,以Terzaghi公式的假设与原理为基础,导出地基极限承载力公式的一般形式,太沙基地基极限承载力公式是其特例。由于考虑中间主应力的影响,计算的地基承载力比太沙基地基极限承载力要大,可发挥土体的强度潜能,得到一系列的解答。     

Estimating anisotropic aquifer parameters by artificial neural networks

In recent years, many approaches have been developed using the artificial neural networks (ANN) model incorporated with the Theis analytical solution to estimate the effective hydrological parameters for homogeneous and isotropic porous media, such as the Lin and Chen approach (ANN approach) and the principal component analysis (PCA)‐ANN approach. The above methods assume a full superimposition of the type curve and the observed drawdown and try to use the first time‐drawdown data as a match point to make a fine approximation of the effective parameters. However, using first time‐drawdown data or early time‐drawdown data does not always allow for an accurate estimation of the hydrological parameters, especially for heterogeneous and anisotropic aquifers. Therefore, this article corrects the concept of the superimposed plot by modifying the ANN approach and the PCA‐ANN approach, as well as incorporating the Papadopoulos analytical solution, to estimate the transmissivities and storage coefficient for anisotropic, homogeneous aquifers. The ANN model is trained with 4000 training sets of the well function, and tested with 1000 sets and 300 sets of synthetic time‐drawdown generated from the homogeneous and heterogeneous parameters, respectively. In situ observation data from the time‐drawdown at station Shi‐Chou on the Choushui River alluvial fan, Taiwan, is further adopted to test the applicability and reliability of the proposed methods, as well as provide a basis for comparison with the Straight‐line method and the Type‐curve method. Results suggest that both of the modified methods perform better than the original ones, and using late time‐drawdown to optimize the effective parameters is shown to be better than using early time‐drawdown. Additionally, results indicate that the modified ANN approach is better than the modified PCA‐ANN approach in terms of precision, while the efficiency of the modified PCA‐ANN approach is approximately three times better than that of the modified ANN approach. Copyright © 2010 John Wiley & Sons, Ltd.     

The impact of spatial scale: exploring urban butterfly abundance and richness patterns using multi-criteria decision analysis and principal component analysis

ABSTRACT

Modelling changes in biodiversity have become a necessary component of smart urban planning practices. However, concepts such as biodiversity are often evaluated using area-based composite indices, the results of which are heavily reliant on specific parameters chosen. This paper explores the design and implementation of a butterfly biodiversity index by comparing two widely accepted modelling techniques: principal component analysis and spatial multi-criteria decision analysis (MCDA). A high degree of scale dependency has been demonstrated in previous studies exploring the use of area-based composite measures. To evaluate the impact of scale, each model was assessed at two different spatial resolutions. The outcomes were analyzed, mapped and compared using ordinary least squares, geographically weighted regression and global Moran’s I to evaluate relative biodiversity patterns across the City of Toronto, Canada. Findings indicate that the impact of spatial scale was significant, whereby the coarser resolution models were found to be more highly correlated with biodiversity, compared to the finer resolution models. The results of this study contribute to a growing body of literature that explores key conceptual questions regarding the robustness of GIS-based MCDA, the impact of scale in urban ecology studies, and the use of composite indices to manage spatial ecological data.     

Predicting the initiation of static liquefaction of cross‐anisotropic sands under multiaxial stress conditions

Experimental evidence has shown that the liquefaction instability of sands can be affected by its material density, stress state, and inherent anisotropy. In order to predict the initiation of the static liquefaction of inherent cross‐anisotropic sands under multidimensional stress conditions, a rational constitutive model is needed. An elastoplasticity model able to capture the influences of intermediate principal stress ratio (b  = (σ ₂ ? σ ₃)/(σ ₁ ? σ ₃)) and loading direction on stress–strain relationships and volumetric properties was proposed. The yield function was formulated to be controlled by Lode angle, loading direction, and material state; the stress–dilatancy was a material state‐dependent function. After using the existing drained hollow cylinder tests to validate the proposed model, this model was used to simulate the existing undrained hollow cylinder tests. During this simulation, the second‐order work criterion was used to determine the initiation of static liquefaction. The results showed that an increase in both the intermediate principal stress ratio and the loading angle induces a decrease in the second‐order work. Static liquefaction is initiated more easily at a stress state with a large intermediate principal stress ratio and a large loading angle, and the mobilized friction angle at the instability points decreases with the intermediate principal stress ratio and the loading angle. Copyright © 2017 John Wiley & Sons, Ltd.     

中钢澳大利亚 Carpentaria 锰矿矿权区 ASTEＲ数据蚀变信息提取研究

应用 ASTEＲ 多光谱卫星遥感数据,根据与锰矿相关的蚀变矿物光谱特征,采用主成份分析算法,提取了中钢集团所属的澳大利亚 Carpentaria 锰矿矿权区铁染、羟基、碳酸盐化、锰和硅化的蚀变信息。ASTEＲ 数据在锰矿化蚀变信息提取中能更好的识别不同类型含羟基蚀变矿物,能更好的提取含三价 Fe 离子的蚀变信息及锰矿物蚀变信息。对这些蚀变信息进行深入分析将有助于矿权区锰矿地质研究和勘查目标的确定。     

Improving the performance of precipitation outputs from Global Climate Models to predict monthly and seasonal rainfall over the Indian subcontinent

Skilful prediction of the monthly and seasonal summer monsoon rainfall over India at a smaller spatial scale is a major challenge for the scientific community. The present study is aimed at achieving this objective by hybridising two mathematical techniques, namely synthetic superensemble (SSE) and supervised principal component regression (SPCR) on six state-of-the art Global Climate Models (GCMs). The performance of the mathematical model is evaluated using correlation analysis, the root mean square error, and the Nash–Sutcliffe efficiency index. Results feature reasonable improvement over central India, which is a zone of maximum rainfall activity in the summer monsoon season. The study also highlights improvement in the monthly prediction of rainfall over raw GCMs (15–20% improvement) with exceptional improvement in July. The developed model is also examined for anomalous years of monsoon and it is found that the model is able to capture the signs of anomalies over different gridpoints of the Indian domain.