Based on the analysis of several objective functions,a new method was proposed.Firstly,the feature of the inclination curve was analyzed.On this basis,the soil could be divided into several blocks with different displ...Based on the analysis of several objective functions,a new method was proposed.Firstly,the feature of the inclination curve was analyzed.On this basis,the soil could be divided into several blocks with different displacements and deformations.Then,the method of the soil division was presented,and the characteristic of single soil block was studied.The displacement of the block had two components:sliding and deformation.Moreover,a new objective function was constructed according to the deformation of the soil block.Finally,the sensitivities of the objective functions by traditional method and the new method were calculated,respectively.The result shows that the new objective function is more sensitive to mechanical parameters and the inversion result is close to that obtained by the large direct shear apparatus.So,this method can be used in slope back analysis and its effectiveness is proved.展开更多
Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies ...Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies into their component patterns were described. A set of stream sediment geochemical data was obtained for 1 880 km 2 of the Pangxidong area, which is in the southern part of the recently recognized Qinzhou-Hangzhou joint tectonic belt. This belt crosses southern China and tends to the northwest (NE) direction. The total number of collected samples was 7 236, and the concentrations of Ag, Au, Cu, As, Pb and Zn were measured for each sample. The spatial combination distribution law of geochemical elements and principal component analysis (PCA) were used to construct combination models for the identification of combinations of geochemical anomalies. Spectrum-area (S-A) fractal modeling was used to strengthen weak anomalies and separate them from the background. Composite anomaly modeling was combined with fractal filtering techniques to process and analyze the geochemical data. The raster maps of Au, Ag, Cu, As, Pb and Zn were obtained by the multifractal inverse distance weighted (MIDW) method. PCA was used to combine the Au, Ag, Cu, As, Pb, and Zn concentration values. The S-A fractal method was used to decompose the first component pattern achieved by the PCA. The results show that combination anomalies from a combination of variables coincide with the known mineralization of the study area. Although the combination anomalies cannot reflect local anomalies closely enough, high-anomaly areas indicate good sites for further exploration for unknown deposits. On this basis, anomaly and background separation from combination anomalies using fractal filtering techniques can provide guidance for later work.展开更多
基金Projects(2013CB036004,2011CB710601)supported by the National Basic Research Program of ChinaProject(51178468)supported by the National Natural Science Foundation of ChinaProject(CX2011B096)supported by Hunan Provincial Postgraduate Innovation Program,China
文摘Based on the analysis of several objective functions,a new method was proposed.Firstly,the feature of the inclination curve was analyzed.On this basis,the soil could be divided into several blocks with different displacements and deformations.Then,the method of the soil division was presented,and the characteristic of single soil block was studied.The displacement of the block had two components:sliding and deformation.Moreover,a new objective function was constructed according to the deformation of the soil block.Finally,the sensitivities of the objective functions by traditional method and the new method were calculated,respectively.The result shows that the new objective function is more sensitive to mechanical parameters and the inversion result is close to that obtained by the large direct shear apparatus.So,this method can be used in slope back analysis and its effectiveness is proved.
基金Project(1212010071012) supported by Guangdong Pangxidong Mineral Prospect Investigation, ChinaProject(41004051) supported by the National Natural Science Foundation of ChinaProject ([2007]038-01-18) supported by Nationwide Mineral Resource Potential Evaluation Projects of Ministry of Land and Resources, China
文摘Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies into their component patterns were described. A set of stream sediment geochemical data was obtained for 1 880 km 2 of the Pangxidong area, which is in the southern part of the recently recognized Qinzhou-Hangzhou joint tectonic belt. This belt crosses southern China and tends to the northwest (NE) direction. The total number of collected samples was 7 236, and the concentrations of Ag, Au, Cu, As, Pb and Zn were measured for each sample. The spatial combination distribution law of geochemical elements and principal component analysis (PCA) were used to construct combination models for the identification of combinations of geochemical anomalies. Spectrum-area (S-A) fractal modeling was used to strengthen weak anomalies and separate them from the background. Composite anomaly modeling was combined with fractal filtering techniques to process and analyze the geochemical data. The raster maps of Au, Ag, Cu, As, Pb and Zn were obtained by the multifractal inverse distance weighted (MIDW) method. PCA was used to combine the Au, Ag, Cu, As, Pb, and Zn concentration values. The S-A fractal method was used to decompose the first component pattern achieved by the PCA. The results show that combination anomalies from a combination of variables coincide with the known mineralization of the study area. Although the combination anomalies cannot reflect local anomalies closely enough, high-anomaly areas indicate good sites for further exploration for unknown deposits. On this basis, anomaly and background separation from combination anomalies using fractal filtering techniques can provide guidance for later work.
