Numerical simulation modeling is a hotspot in the geological engineering computing field.Taking a fast Langrangian analysis of continua in 3 dimensions(FLAC) numerical modeling on computing the geo-deformation informa...Numerical simulation modeling is a hotspot in the geological engineering computing field.Taking a fast Langrangian analysis of continua in 3 dimensions(FLAC) numerical modeling on computing the geo-deformation information caused by the mining subsidence in a coalmine for example,a new GIS-Excel modeling method is proposed to build geologic strata within the simulation range combined with the coal-seam dip angle of the underground mining working-planes.First of all,the coal-seam model of the numerical computing is built by using the geographic information system(GIS) according to the stripe-through principle and the calculating formula on the size of the model blocks in the paper defined,then the FLAC^(3D) numerical computing model of all geologic strata within the simulation range is also built based on the calculating formula of thickness of each stratum and the Excel fast computing advantages.The GIS-Excel method is good at the higher modeling accuracy,seldom making mistakes and consuming less time.The reliability and validity of the method is verified well by its practical applications in the coalmine area.展开更多
Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when ...Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.展开更多
基金Supported by the National Natural Science Foundation of China(No.41271436)
文摘Numerical simulation modeling is a hotspot in the geological engineering computing field.Taking a fast Langrangian analysis of continua in 3 dimensions(FLAC) numerical modeling on computing the geo-deformation information caused by the mining subsidence in a coalmine for example,a new GIS-Excel modeling method is proposed to build geologic strata within the simulation range combined with the coal-seam dip angle of the underground mining working-planes.First of all,the coal-seam model of the numerical computing is built by using the geographic information system(GIS) according to the stripe-through principle and the calculating formula on the size of the model blocks in the paper defined,then the FLAC^(3D) numerical computing model of all geologic strata within the simulation range is also built based on the calculating formula of thickness of each stratum and the Excel fast computing advantages.The GIS-Excel method is good at the higher modeling accuracy,seldom making mistakes and consuming less time.The reliability and validity of the method is verified well by its practical applications in the coalmine area.
基金supported by the National Nature Science Foundation of China(Grant No.71401052)the National Social Science Foundation of China(Grant No.17BGL156)the Key Project of the National Social Science Foundation of China(Grant No.14AZD024)
文摘Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.
