Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribut...Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.展开更多
Behavior choice, coal mine monitoring, and control intensity are combined in a general mathematical model established from the perspective of a behavioral game. A case study is provided with effective conditions of mo...Behavior choice, coal mine monitoring, and control intensity are combined in a general mathematical model established from the perspective of a behavioral game. A case study is provided with effective conditions of monitoring provided. This paper defines the expected value difference of control return and behavior cost difference and discusses the measurement and optimization of variable indexes, including the monitoring intensity and costs of control. The results imply that the control of unsafe behavior can be more effective when monitoring and control of coal mines are both improved. Monitoring will be useful when the rewards for displaying safe behavior, and the monitoring of unsafe behavior, are improved to a high level.展开更多
Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can repre...Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices（SPI（Standardized Precipitation Index）, PNI（Percent of Normal Index）, DI（Deciles index）, EDI（Effective drought index）, CZI（China-Z index）, MCZI（Modified CZI）, RAI（Rainfall Anomaly Index）, and ZSI（Z-score Index）） calculated from the station-observed precipitation data and the Ag MERRA gridded precipitation data to assess historical drought events during the period 1987–2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index（DDI） for comparing the intensities of different drought categories in each year of the study period（1987–2010）. In general, the correlations among drought indices calculated from the Ag MERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated（R^2=0.99）. Furthermore, the higher correlations（R^2=0.99） were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the Ag MERRA precipitation data and from the station-observed precipitation data, we suggest that the Ag MERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the Ag MERRA precipitation data may be used for the data-lacking areas.展开更多
基金funded by the Research and Development Fund Project of China Academy of Railway Science Group Co.,Ltd.,(No:2023YJ259)the Science and Technology Research and Development Program Project of China State Railway Group Co.,Ltd.(No:J2024G008).
文摘Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.
基金Project supports from The Humanistic and Social Scientific Research Planning Program in Ministry of Education of China (No.12YJA630063)The Social Science Foundation of Jiangsu Province of China (No. 10GLB001)the Ph.D. Programs Foundation of Ministry of Education of China (No. 20100095120014) are acknowledged
文摘Behavior choice, coal mine monitoring, and control intensity are combined in a general mathematical model established from the perspective of a behavioral game. A case study is provided with effective conditions of monitoring provided. This paper defines the expected value difference of control return and behavior cost difference and discusses the measurement and optimization of variable indexes, including the monitoring intensity and costs of control. The results imply that the control of unsafe behavior can be more effective when monitoring and control of coal mines are both improved. Monitoring will be useful when the rewards for displaying safe behavior, and the monitoring of unsafe behavior, are improved to a high level.
文摘Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices（SPI（Standardized Precipitation Index）, PNI（Percent of Normal Index）, DI（Deciles index）, EDI（Effective drought index）, CZI（China-Z index）, MCZI（Modified CZI）, RAI（Rainfall Anomaly Index）, and ZSI（Z-score Index）） calculated from the station-observed precipitation data and the Ag MERRA gridded precipitation data to assess historical drought events during the period 1987–2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index（DDI） for comparing the intensities of different drought categories in each year of the study period（1987–2010）. In general, the correlations among drought indices calculated from the Ag MERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated（R^2=0.99）. Furthermore, the higher correlations（R^2=0.99） were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the Ag MERRA precipitation data and from the station-observed precipitation data, we suggest that the Ag MERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the Ag MERRA precipitation data may be used for the data-lacking areas.
