{"title":"震后建筑服务停工时间分布:2016 年日本熊本地震案例研究","authors":"Tomoaki Nishino","doi":"10.1007/s44150-024-00113-3","DOIUrl":null,"url":null,"abstract":"<div><p>Seismic damage to building services systems, that is, mechanical, electrical, and plumbing systems in buildings related to energy and indoor environments, affects the functionality of buildings. Assessing post-earthquake functionality is useful for enhancing the seismic resilience of buildings via improved design. Such assessments require a model for predicting the time required to restore building services. This study analyzes the downtime data for 250 instances of damage to building services components caused by the 2016 Kumamoto earthquake in Japan, presumably obtained from buildings with minor or no structural damage. The objectives of this study are (1) to determine the empirical downtime distribution of building services components and (2) to assess the dependence of the downtime on explanatory variables. A survival analysis, which is a statistical technique for analyzing time-to-event data, reveals that (1) the median downtime of building services components was 90 days and, 7 months after the earthquake, the empirical non-restoration probability was approximately 32%, (2) the services type and the building use are explanatory variables having a statistically significant effect on the downtime of building services components, (3) the log-logistic regression model reasonably captures the trend of the restoration of building services components, (4) medical and welfare facilities and hotels restored building services components relatively quickly, and (5) the 7-month restoration probability was observed to be highest for electrical systems, followed by sanitary systems, then heating, ventilation, and air conditioning systems, and finally life safety systems. These results provide useful information to support the resilience-based seismic design of buildings.</p></div>","PeriodicalId":100117,"journal":{"name":"Architecture, Structures and Construction","volume":"4 2-4","pages":"227 - 240"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44150-024-00113-3.pdf","citationCount":"0","resultStr":"{\"title\":\"Post-earthquake building services downtime distribution: a case study of the 2016 Kumamoto, Japan, earthquake\",\"authors\":\"Tomoaki Nishino\",\"doi\":\"10.1007/s44150-024-00113-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Seismic damage to building services systems, that is, mechanical, electrical, and plumbing systems in buildings related to energy and indoor environments, affects the functionality of buildings. Assessing post-earthquake functionality is useful for enhancing the seismic resilience of buildings via improved design. Such assessments require a model for predicting the time required to restore building services. This study analyzes the downtime data for 250 instances of damage to building services components caused by the 2016 Kumamoto earthquake in Japan, presumably obtained from buildings with minor or no structural damage. The objectives of this study are (1) to determine the empirical downtime distribution of building services components and (2) to assess the dependence of the downtime on explanatory variables. A survival analysis, which is a statistical technique for analyzing time-to-event data, reveals that (1) the median downtime of building services components was 90 days and, 7 months after the earthquake, the empirical non-restoration probability was approximately 32%, (2) the services type and the building use are explanatory variables having a statistically significant effect on the downtime of building services components, (3) the log-logistic regression model reasonably captures the trend of the restoration of building services components, (4) medical and welfare facilities and hotels restored building services components relatively quickly, and (5) the 7-month restoration probability was observed to be highest for electrical systems, followed by sanitary systems, then heating, ventilation, and air conditioning systems, and finally life safety systems. These results provide useful information to support the resilience-based seismic design of buildings.</p></div>\",\"PeriodicalId\":100117,\"journal\":{\"name\":\"Architecture, Structures and Construction\",\"volume\":\"4 2-4\",\"pages\":\"227 - 240\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s44150-024-00113-3.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Architecture, Structures and Construction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s44150-024-00113-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Architecture, Structures and Construction","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s44150-024-00113-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Post-earthquake building services downtime distribution: a case study of the 2016 Kumamoto, Japan, earthquake
Seismic damage to building services systems, that is, mechanical, electrical, and plumbing systems in buildings related to energy and indoor environments, affects the functionality of buildings. Assessing post-earthquake functionality is useful for enhancing the seismic resilience of buildings via improved design. Such assessments require a model for predicting the time required to restore building services. This study analyzes the downtime data for 250 instances of damage to building services components caused by the 2016 Kumamoto earthquake in Japan, presumably obtained from buildings with minor or no structural damage. The objectives of this study are (1) to determine the empirical downtime distribution of building services components and (2) to assess the dependence of the downtime on explanatory variables. A survival analysis, which is a statistical technique for analyzing time-to-event data, reveals that (1) the median downtime of building services components was 90 days and, 7 months after the earthquake, the empirical non-restoration probability was approximately 32%, (2) the services type and the building use are explanatory variables having a statistically significant effect on the downtime of building services components, (3) the log-logistic regression model reasonably captures the trend of the restoration of building services components, (4) medical and welfare facilities and hotels restored building services components relatively quickly, and (5) the 7-month restoration probability was observed to be highest for electrical systems, followed by sanitary systems, then heating, ventilation, and air conditioning systems, and finally life safety systems. These results provide useful information to support the resilience-based seismic design of buildings.