Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The accuracy of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create good experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data. 相似文献
Argillaceous rocks cover about one thirds of the earth's surface. The major engineering problems encountered with weak- to medium-strength argillaceous rocks could be slaking, erosion, slope stability, settlement, and reduction in strength. One of the key properties for classifying and determining the behavior of such rocks is the slake durability. The concept of slake durability index (SDI) has been the subject of numerous researches in which a number of factors affecting the numerical value of SDI were investigated. In this regard, this paper approaches the matter by evaluating the effects of overall shape and surface roughness of the testing material on the outcome of slake durability indices.
For the purpose, different types of rocks (marl, clayey limestone, tuff, sandstone, weathered granite) were broken into chunks and were intentionally shaped as angular, subangular, and rounded and tested for slake durability. Before testing the aggregate pieces of each rock type, their surface roughness was determined by using the fractal dimension. Despite the variation of final values of SDI test results (values of Id), the rounded aggregate groups plot relatively in a narrow range, but a greater scatter was obtained for the angular and subangular aggregate groups. The best results can be obtained when using the well rounded samples having the lowest fractal values. An attempt was made to analytically link the surface roughness with the Id parameter and an empirical relationship was proposed. A chart for various fractal values of surface roughness to use as a guide for slake durability tests is also proposed. The method proposed herein becomes efficient when well rounded aggregates are not available. In such condition, the approximate fractal value for the surface roughness profile of the testing aggregates could be obtained from the proposed chart and be plugged into the empirical relation to obtain the corrected Id value. The results presented herein represent the particular rock types used in this study and care should be taken when applying these methods to different type of rocks. 相似文献
A decision support system (DSS) has been developed to assist expert and non-expert users in the evaluation and selection of
eco-engineering strategies for slope protection. This DSS combines a qualitative hazard assessment of erosion and mass movements
with a detailed catalogue of eco-engineering strategies for slope protection of which the suitability is evaluated in relation
to the data entered. The slope decision support system (SDSS) is a knowledge based DSS in which knowledge is stored in frames
containing rules that can evaluate the available information for a project, stored as project specific information (PSI) in
a data file. The advantages of such a system are that it accepts incomplete information and that the qualitative nature of
the information does not instil the user with a sense of unjustified exactitude. By its multidisciplinary and progressive
nature, the DSS will be of value during the initial stages of an eco-engineering project when data collection and the potential
of different eco-engineering strategies are considered. The accent of the output of the DSS is on the application of eco-engineering
strategies for slope protection as an environmentally-friendly solution aiding sustainable development. For its acceptance
within the engineering community, the DSS needs to prove its predictive capacity. Therefore, its performance has been benchmarked
against successful and unsuccessful cases of slope stabilisation using eco-engineering. The target audience and the areas
of application of this DSS are reviewed and the strategies for further development in this area suggested. 相似文献
Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.The online version of the original article can be found at 相似文献