Consolidation of double‐layered ground with vertical drains

Vertical drains are usually installed in subsoil consisting of several layers. Due to the complex nature of the problem, over the past decades, the consolidation properties of multi‐layered ground with vertical drains have been analysed mainly by numerical methods. An analytical solution for consolidation of double‐layered ground with vertical drains under quasi‐equal strain condition is presented in this paper. The main steps for the computation procedure are listed. The convergence of the series solution is discussed. The comparisons between the results obtained by the present analytical method and the existing numerical solutions are described by figures. The orthogonal relation for the system of double‐layered ground with vertical drains is proven. Finally, some consolidation properties of double‐layered ground with vertical drains are analysed. Copyright © 2001 John Wiley & Sons, Ltd.     

Himalayan magmatism and porphyry copper–molybdenum mineralization in the Yulong ore belt, East Tibet

Summary ?The NW–SE-trending Yulong porphyry Cu–Mo ore belt, situated in the Sanjiang0 area of eastern Tibet, is approximately 400 km long and 35 to 70 km wide. Complex tectonic and magmatic processes during the Himalayan epoch have given rise to favorable conditions for porphyry-type Cu–Mo mineralization. Porphyry masses of the Himalayan epoch in the Yulong ore belt are distributed in groups along regional NW–SE striking tectonic lineaments. They were emplaced mainly into Triassic and Lower Permian sedimentary-volcanic rocks. K–Ar und U–Pb isotopic datings give an intrusion age range of 57–26 Ma. The porphyries are mainly of biotite monzogranitic and biotite syenogranitic compositions. Geological and geochemical data indicate that the various porphyritic intrusions in the belt had a common or similar magma source, are metaluminous to peraluminous, Nb–Y–Ba-depleted, I-type granitoids, and belong to the high-K calc-alkaline series. Within the Yulong subvolcanic belt a number of porphyry stocks bear typical porphyry type Cu–Mo alteration and mineralization. The most prominent porphyry Co–Mo deposits include Yulong, Malasongduo, Duoxiasongduo, Mangzong and Zhanaga, of which Yulong is one of the largest porphyry Cu (Mo) deposits in China with approximately 8 × 10⁶ tons of contained Cu metal. Hydrothermal alteration at Yulong developed around a biotite–monzogranitic porphyry stock that was emplaced within Upper Triassic limestone, siltstone and mudstone. The earliest alteration was due to the effects of contact metamorphism of the country rocks and alkali metasomatism (potassic alteration) within and around the porphyry body. The alteration of this stage was accompanied by a small amount of disseminated and veinlet Cu–Mo sulfide mineralization. Later alteration–mineralization zones form more or less concentric shells around the potassic zone, around which are distributed a phyllic or quartz–sericite–pyrite zone, a silicification and argillic zone, and a propylitic zone. Fluid inclusion data indicate that three types of fluids were involved in the alteration–mineralization processes: (1) early high temperature (660–420 °C) and high salinity (30–51 wt% NaCl equiv) fluids responsible for the potassic alteration and the earliest disseminated and/or veinlet Cu–Mo sulfide mineralization; (2) intermediate unmixed fluids corresponding to phyllic alteration and most Cu–Mo sulfide mineralization, with salinities of 30–50 wt% NaCl equiv and homogenization temperatures of 460–280 °C; and (3) late low to moderate temperature (300–160 °C) and low salinity (6–13 wt% NaCl equiv) fluids responsible for argillic and propylitic alteration. Hydrogen and oxygen isotopic studies show that the early hydrothermal fluids are of magmatic origin and were succeeded by increasing amounts of meteoric-derived convective waters. Sulfur isotopes also indicate a magmatic source for the sulfur in the early sulfide mineralization, with the increasing addition of sedimentary sulfur outward from the porphyry stock. Received August 29, 2001; revised version accepted May 1, 2002 Published online: November 29, 2002     

Computing the Light Periods of Blazars with the Periodogram Spectral Analysis Method

The periodogram spectral analysis method applicable to equallyspaced time series is discussed, and the method is tested first with a simulated data series. It is confirmed that this method is effective for noisy series. Then, applying this method to the analysis of the light periods of the quasars 3C 279 and 3C 345 as well as the BL Lac objects OJ 287 and ON 231, we obtain their light periods to be 7.14 yr, 10.00 yr, 11.76 yr and 6.80 yr, respectively. These results obtained by periodogram spectral analysis are consistent with those obtained by the Jurkevich method in the literature. We have analyzed the effects of different window functions, and commented on their correct selection in practical applications.     

HPABM: A Hierarchical Parallel Simulation Framework for Spatially-explicit Agent-based Models

A Hierarchical Parallel simulation framework for spatially-explicit Agent-Based Models (HPABM) is developed to enable computationally intensive agent-based models for the investigation of large-scale geospatial problems. HPABM allows for the utilization of high-performance and parallel computing resources to address computational challenges in agent-based models. Within HPABM, an agent-based model is decomposed into a set of sub-models that function as computational units for parallel computing. Each sub-model is comprised of a sub-set of agents and their spatially-explicit environments. Sub-models are aggregated into a group of super-models that represent computing tasks. HPABM based on the design of super- and sub-models leads to the loose coupling of agent-based models and underlying parallel computing architectures. The utility of HPABM in enabling the development of parallel agent-based models was examined in a case study. Results of computational experiments indicate that HPABM is scalable for developing large-scale agent-based models and, thus, demonstrates efficient support for enhancing the capability of agent-based modeling for large-scale geospatial simulation.     

Multi‐scale approach to mining significant spatial co‐location patterns

Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features, which are frequently located in close geographic proximity to each other. Existing methods for identifying spatial co‐location patterns usually require users to specify two thresholds, i.e. the prevalence threshold for measuring the prevalence of candidate co‐location patterns and distance threshold to search the spatial co‐location patterns. However, these two thresholds are difficult to determine in practice, and improper thresholds may lead to the misidentification of useful patterns and the incorrect reporting of meaningless patterns. The multi‐scale approach proposed in this study overcomes this limitation. Initially, the prevalence of candidate co‐location patterns is measured statistically by using a significance test, and a non‐parametric model is developed to construct the null distribution of features with the consideration of spatial auto‐correlation. Next, the spatial co‐location patterns are explored at multi‐scales instead of single scale (or distance threshold) discovery. The validity of the co‐location patterns is evaluated based on the concept of lifetime. Experiments on both synthetic and ecological datasets show that spatial co‐location patterns are discovered correctly and completely by using the proposed method; on the other hand, the subjectivity in discovery of spatial co‐location patterns is reduced significantly.     

Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.     

方向数据插值方法研究

方向数据是矢量数据的标量表示,通常标量数据的插值方法不适用于方向数据。本文根据方向数据的特征,把其分解成沿坐标轴的分量,通过对分量数据的插值形成表面,最后合成反算出方向数据,给出了一种对于方向数据的行之有效的插值方法;并用实验进行了验证,对其插值结果和精度进行了统计和分析,取得了较为理想的内插结果。     

一种基于人工免疫的图像分割算法

图像二维熵分割,一直因耗时长而限制了实际应用。本文借鉴生物免疫思想,提出二维熵图像分割的人工免疫算法。在克隆选择算法中引入疫苗的免疫接种,用于优化最优分割阈值对的搜索过程。在遥感高分辨率图像上的实验显示,该算法不仅能准确搜索到最优阈值对,而且计算时间只有传统算法的1.8%。该算法也验证了人工免疫思想用于图像分割的可行性和有效性。     

一定分布模式下的最优Lp估计

观测数据在一定的分布模式下,需从理论上解决究竟用多大的ｐ值进行Ｌｐ估计（最优ｐ值的确定）,本文基于渐近方差整体最小的原则,给出了最优Ｌｐ估计的定义。观测数据中含有粗差（异常值）的扰动,其误差分布可视为污染分布,作者分析了最优ｐ值的大小,结果表明,若观测数据中含有不同大小、数量的粗差,为使Ｌｐ估计差最小,则ｐ将取［１．２,１．５］中的某一定值,Ｌｐ估计结果最优,此结论对测量数据处理具有一定的参考价值