Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological b...Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.展开更多
The seismic design and analysis of nuclear power plant (NPP) begin with the seismic hazard assessment and design ground motion development for the site. The following steps are needed for the seismic hazard assessment...The seismic design and analysis of nuclear power plant (NPP) begin with the seismic hazard assessment and design ground motion development for the site. The following steps are needed for the seismic hazard assessment and design ground motion development:a. the development of regional seismo-tectonic model with seismic source areas within 500 km radius centered to the site;b. the development of strong motion prediction equations; c. logic three development for taking into account uncertainties and seismic hazard quantification;d. the development of uniform hazard response spectra for ground motion at the site;e. simulation of acceleration time histories compatible with uniform hazard response spectra. The following phase two in seismic design of NPP structures is the analysis of structural response for the design ground motion. This second phase of the process consists of the following steps:a. development of structural models of the plant buildings;b. development of the soil model underneath the plant buildings for soilstructure interaction response analysis;c. determination of instructure response spectra for the plant buildings for the equipment response analysis. In the third phase of the seismic design and analysis the equipment is analyzed on the basis of in-structure response spectra. For this purpose the structural models of the mechanical components and piping in the plant are set up. In large 3D-structural models used today the heaviest equipment of the primary coolant circuit is included in the structural model of the reactor building. In the fourth phase the electrical equipment and automation and control equipment are seismically qualified with the aid of the in-structure spectra developed in the phase two using large three-axial shaking tables. For this purpose the smoothed envelope spectra for calculated in-structure spectra are constructed and acceleration time is fitted to these smoothed envelope spectra.展开更多
基金The study was supported by Open Fund of State Key Laboratory of Coal Resources and Safe Mining(Grant No.SKLCRSM19ZZ02)the National Natural Science Foundation of China(No.41702173)。
文摘Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.
文摘The seismic design and analysis of nuclear power plant (NPP) begin with the seismic hazard assessment and design ground motion development for the site. The following steps are needed for the seismic hazard assessment and design ground motion development:a. the development of regional seismo-tectonic model with seismic source areas within 500 km radius centered to the site;b. the development of strong motion prediction equations; c. logic three development for taking into account uncertainties and seismic hazard quantification;d. the development of uniform hazard response spectra for ground motion at the site;e. simulation of acceleration time histories compatible with uniform hazard response spectra. The following phase two in seismic design of NPP structures is the analysis of structural response for the design ground motion. This second phase of the process consists of the following steps:a. development of structural models of the plant buildings;b. development of the soil model underneath the plant buildings for soilstructure interaction response analysis;c. determination of instructure response spectra for the plant buildings for the equipment response analysis. In the third phase of the seismic design and analysis the equipment is analyzed on the basis of in-structure response spectra. For this purpose the structural models of the mechanical components and piping in the plant are set up. In large 3D-structural models used today the heaviest equipment of the primary coolant circuit is included in the structural model of the reactor building. In the fourth phase the electrical equipment and automation and control equipment are seismically qualified with the aid of the in-structure spectra developed in the phase two using large three-axial shaking tables. For this purpose the smoothed envelope spectra for calculated in-structure spectra are constructed and acceleration time is fitted to these smoothed envelope spectra.
