{"title":"以伊尔库茨克为例的地震峰值烈度分布的概率分析","authors":"D. A. Karmazinov, T. Dmitrieva","doi":"10.21285/2227-2917-2022-4-570-578","DOIUrl":null,"url":null,"abstract":"This article discusses approaches to forecasting the earthquake odds of a given intensity level. This problem is relevant for the earthquake-prone zone in the south of the Irkutsk region characterised by an estimated intensity of shaking of up to 9 points, where large, populated areas having developed industrial and civil construction are located. The intensity values for Irkutsk were obtained using the analysed data on the seismic activity of the Baikal and Transbaikalia regions in 1973–2020 by the equa-tion of the macroseismic field. The algorithm for predicting large and medium-sized earthquakes in-volves mathematical statistics and probability theory. A corresponding empirical distribution was derived on the basis of a sample of the maximum intensity values for the specified period in each year. The potential applicability of common distribution functions for describing the intensity distribution of seis-mic vibrations was considered. It was established that the normal distribution function provides the most accurate description of statistical data. It was concluded that, by using this function, it is possible to determine the high-intensity vibration odds that can lead to serious destruction, as well as their most probable annual peak intensity, which may allow for measures ensuring the resistance of load-bearing structures of buildings to background seismic impacts.","PeriodicalId":119410,"journal":{"name":"«Izvestiya vuzov. Investitsiyi. Stroyitelstvo. Nedvizhimost»","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic analysis of peak intensity distribution of earthquakes on an example of Irkutsk\",\"authors\":\"D. A. Karmazinov, T. Dmitrieva\",\"doi\":\"10.21285/2227-2917-2022-4-570-578\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article discusses approaches to forecasting the earthquake odds of a given intensity level. This problem is relevant for the earthquake-prone zone in the south of the Irkutsk region characterised by an estimated intensity of shaking of up to 9 points, where large, populated areas having developed industrial and civil construction are located. The intensity values for Irkutsk were obtained using the analysed data on the seismic activity of the Baikal and Transbaikalia regions in 1973–2020 by the equa-tion of the macroseismic field. The algorithm for predicting large and medium-sized earthquakes in-volves mathematical statistics and probability theory. A corresponding empirical distribution was derived on the basis of a sample of the maximum intensity values for the specified period in each year. The potential applicability of common distribution functions for describing the intensity distribution of seis-mic vibrations was considered. It was established that the normal distribution function provides the most accurate description of statistical data. It was concluded that, by using this function, it is possible to determine the high-intensity vibration odds that can lead to serious destruction, as well as their most probable annual peak intensity, which may allow for measures ensuring the resistance of load-bearing structures of buildings to background seismic impacts.\",\"PeriodicalId\":119410,\"journal\":{\"name\":\"«Izvestiya vuzov. Investitsiyi. Stroyitelstvo. Nedvizhimost»\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"«Izvestiya vuzov. Investitsiyi. Stroyitelstvo. Nedvizhimost»\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21285/2227-2917-2022-4-570-578\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"«Izvestiya vuzov. Investitsiyi. Stroyitelstvo. Nedvizhimost»","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21285/2227-2917-2022-4-570-578","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic analysis of peak intensity distribution of earthquakes on an example of Irkutsk
This article discusses approaches to forecasting the earthquake odds of a given intensity level. This problem is relevant for the earthquake-prone zone in the south of the Irkutsk region characterised by an estimated intensity of shaking of up to 9 points, where large, populated areas having developed industrial and civil construction are located. The intensity values for Irkutsk were obtained using the analysed data on the seismic activity of the Baikal and Transbaikalia regions in 1973–2020 by the equa-tion of the macroseismic field. The algorithm for predicting large and medium-sized earthquakes in-volves mathematical statistics and probability theory. A corresponding empirical distribution was derived on the basis of a sample of the maximum intensity values for the specified period in each year. The potential applicability of common distribution functions for describing the intensity distribution of seis-mic vibrations was considered. It was established that the normal distribution function provides the most accurate description of statistical data. It was concluded that, by using this function, it is possible to determine the high-intensity vibration odds that can lead to serious destruction, as well as their most probable annual peak intensity, which may allow for measures ensuring the resistance of load-bearing structures of buildings to background seismic impacts.