Design of backfilled thin-seam coal pillars using earth pressure theory     

James G. Donovan  Mario G. Karfakis 《Geotechnical and Geological Engineering》2004,22(4):627-642

In underground coal mining any increase in coal recovery rate is dependent on a decrease in pillar size. Backfilling is one way of reducing the required size of pillars and hence the volume of coal left underground. Therefore any comparisons made between a self-supported mine layout and backfill supported mine layout are based directly on pillar design. The most effective way to examine the effect of backfill on pillar support, and subsequently the rate of recovery, would be to incorporate the mechanisms of backfill support directly into the current design procedure for coal pillars. This paper presents a review of the mechanics of backfill support, a method of estimating the magnitude of that support based on earth pressure theory, and an example that incorporates backfill support into current coal pillar design.  相似文献   

复杂环境条件下深基坑综合支护措施的应用          下载免费PDF全文

李江  张明中  陈辉  贾城 《探矿工程》2004,31(8):4-7

北京某交易中心一期基坑工程属大型深基坑工程，各种地下管线和地上建(构)筑物复杂，介绍了针对其复杂环境条件的综合支护措施的设计思路与实际应用效果。  相似文献   

温州世贸中心大厦超深大直径钻孔灌注桩施工技术          下载免费PDF全文

徐辉雄  张涛  晏军  杨建林  鄢泰宁  蒋国盛 《探矿工程》2004,31(9):35-37

介绍了超深大直径钻孔灌注桩在温州世贸中心大厦桩基工程中的应用情况，对其施工中出现的主要问题进行了分析和处理，并提出了解决措施。  相似文献   

浅埋暗挖技术在南平市天台隧道工程施工中的应用          下载免费PDF全文

李耀卿 《探矿工程》2005,32(12):56-58

主要介绍了在Ⅱ、Ⅲ类围岩中施工城市浅埋隧道的施工技术，以“短开挖、快封闭、强支护、勤量测”为指导，将隧道分成上、下两个台阶进行开挖，及时进行初期支护，保证施工始终处于安全状态。  相似文献   

西藏直孔水电站大坝混凝土防渗墙超前支护成槽试验研究及施工     

马邦凯  牟兴华  蔡海燕 《探矿工程》2005,32(12):3-5

在西藏直孔水电站松散砂卵石地层混凝土防渗墙成槽施工中，结合坝基水文地质及工程地质特点，创造性地提出了超前支护成槽方案，通过三维应力模拟和渗透试验，结合现场生产试验，对原方案更进一步完善，在施工中加以应用获得了成功。  相似文献   

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach          下载免费PDF全文

Poulomi Ganguli  M. Janga Reddy 《水文研究》2014,28(19):4989-5009

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data     

Xiaoyu Sun  Xia Peng  Yiran Chen  Yu Liu 《International Journal of Digital Earth》2019,12(6):661-678

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.  相似文献   

Geospatial data mining for digital raster mapping     

Bruce K. Wylie  Neal J. Pastick  Joshua J. Picotte  Carol A. Deering 《地理信息系统科学与遥感》2019,56(3):406-429

We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.  相似文献   

基于并行计算的海洋平台谱分析疲劳筛选技术研究     

李洛东  刘成名  梁园华 《海洋工程》2018,36(5):56-64

为了得到海洋平台疲劳失效风险最大的焊接区域,提出了以有限元网格单元应力为基础的谱分析筛选方法,并开发了程序。程序采用并行计算架构,单次完成数万个单元的累积损伤度/疲劳寿命计算,并通过有限元软件以云图方式显示疲劳寿命。采用该程序计算双浮筒半潜式平台的疲劳寿命。结果表明,该型平台疲劳失效风险较高的区域为立柱与上壳体下浮体连接对角线转角区域、浮筒中纵舱壁与立柱连接区域。并行计算方法的引入,大大缩减疲劳损伤度计算的分析时间,采用22核心的CPU,时间缩短为原来的1/18.5,17小时完成全平台外壳单元谱分析计算。  相似文献   

南海北部海域油气勘探保障建设选址适宜性研究     

武二亮  陈浩东  刘裕光  安永宁 《海岸工程》2020,39(4):256-262

为分析南海北部海域油气勘探保障建设选址的适宜性,在广泛研究备选区特征资料的基础上,基于层次分析法(Analytic Hierarchy Process, AHP)原理,以自然环境因素、开发环境因素、基础设施与投资情况以及其他因素作为一级评判准则,建立了包括12项二级评判准则的递进层次结构模型,并以永兴岛、赵述岛和晋卿岛作为3个假定备选区,来验证分析评价模型的有效性和可靠性。AHP评判结果显示,3个备选区的整体优劣指数依次为0.587 1, 0.212 1, 0.200 8;AHP模型的一致性比例CR值为0.020 3。通过分析和筛选影响远海油气勘探保障建设的选址因子,构建基于AHP原理的选址评价模型,可用于分析评价南海北部岛礁油气勘探保障建设选址的适宜性。  相似文献