Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis me...Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis method of metallogenic information,was proposed.In addition,a case study by using the method of the extraction of metallogenic information from the west Guangxi and southeast Yunnan district as an example was performed.The representation method for the field models of metallogenic information,including the metallogenic influence field model and the metallogenic distance field model,was discussed by introducing the concept of the field theory,based on the characteristic analysis of the distance gradualness and the influence superposition of metallogenic information.According to the field theory superposition principle and the spatial distance analysis method,the mathematical models for the metallogenic influence field and the metallogenic distance field of point,line and area geological bodies were derived out by using parameter equation and calculus.Based on the metallogenic background analysis,the metallogenic information field models of synsedimentary faults and manganese sedimentary basins were built.The relationship between the metallogenic information fields and the manganese mineralization distribution was also investigated by using the method of metallogenic information field analysis.The instance study indicates that the proposed method of metallogenic information field analysis is valid and useful for extracting the ore-controlling information of synsedimentary faults and manganese sedimentary basins in the study area,with which the extraction results are significant both statistically and geologically.展开更多
For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marg...For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marginal probability density function(PDF) of the epistemic variable and the conditional PDF of the aleatory one at the fixed epistemic variable,the epistemic and aleatory uncertainties are propagated to the response of the structure firstly in the presented method.And the computational model for calculating the importance measures of the epistemic variables is established.For solving the computational model,the high efficient SDP method is applied to estimating the first order high dimensional model representation(HDMR) to obtain the importance measures.Compared with the direct Monte Carlo method,the presented method can considerably improve computational efficiency with acceptable precision.The presented method has wider applicability compared with the existing approximation method,because it is suitable not only for the linear response functions,but also for nonlinear response functions.Several examples are used to demonstrate the advantages of the presented method.展开更多
基金Project(2006BAB01B07) supported by the National Science and Technology Pillar Program during the 11th Five-Year Plan Period of China
文摘Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis method of metallogenic information,was proposed.In addition,a case study by using the method of the extraction of metallogenic information from the west Guangxi and southeast Yunnan district as an example was performed.The representation method for the field models of metallogenic information,including the metallogenic influence field model and the metallogenic distance field model,was discussed by introducing the concept of the field theory,based on the characteristic analysis of the distance gradualness and the influence superposition of metallogenic information.According to the field theory superposition principle and the spatial distance analysis method,the mathematical models for the metallogenic influence field and the metallogenic distance field of point,line and area geological bodies were derived out by using parameter equation and calculus.Based on the metallogenic background analysis,the metallogenic information field models of synsedimentary faults and manganese sedimentary basins were built.The relationship between the metallogenic information fields and the manganese mineralization distribution was also investigated by using the method of metallogenic information field analysis.The instance study indicates that the proposed method of metallogenic information field analysis is valid and useful for extracting the ore-controlling information of synsedimentary faults and manganese sedimentary basins in the study area,with which the extraction results are significant both statistically and geologically.
基金supported by the National Natural Science Foundation of China (Grant No. 51175425)the Aviation Science Foundation (Grant No.2011ZA53015)the Doctorate Foundation of Northwestern Polytechnical University (Grant No. CX201205)
文摘For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marginal probability density function(PDF) of the epistemic variable and the conditional PDF of the aleatory one at the fixed epistemic variable,the epistemic and aleatory uncertainties are propagated to the response of the structure firstly in the presented method.And the computational model for calculating the importance measures of the epistemic variables is established.For solving the computational model,the high efficient SDP method is applied to estimating the first order high dimensional model representation(HDMR) to obtain the importance measures.Compared with the direct Monte Carlo method,the presented method can considerably improve computational efficiency with acceptable precision.The presented method has wider applicability compared with the existing approximation method,because it is suitable not only for the linear response functions,but also for nonlinear response functions.Several examples are used to demonstrate the advantages of the presented method.
