Seismic hazard causes a considerable portion of loss in many countries annually and thus is of high importance. Seismic hazard and its consequences, known as seismic risk, have been studied in the fields of geology, earthquake engineering and structural engineering in the framework of probabilistic seismic hazard analysis (PSHA). PSHA could be simply defined as the probability of occurrence of an earthquake characteristic (e.g., PGA), considering uncertainties namely magnitude, location and their resulting ground motion specified by ground motion prediction equation (GMPE). The final output of PSHA is the rate of exceeding specific intensity measure (IM), and could be expressed in terms of return period exceedance. For structural design purposes, for a given probability and structure’s design life, the seismic hazard could be stated in terms of return period TR, which is commonly applied in current design code (e.g., Eurocode 8). The abovementioned explanations of return period of exceedance are based on the Poisson relationship between time and earthquake which assumes that the probability of an earthquake occurring remains unchanged by elapsing time. In the recent decades, however, it has been claimed that earthquake occurrence could be expressed through timedependent models which means that elapsing time since the last earthquake affects its occurrence probability. This research focuses mainly on the effect of timedependent seismic hazard on structural design, by evaluating the strength required by the structure (seismic capacity) for different time intervals elapsing from the last event. “Seismic capacity” is defined as the capacity required to provide a fixed failure rate. Two different seismic scenarios (i. e., a point source and a combined source including area and line source) have been investigated and results concerning different sitetosource distance, capacity dispersion of the structure and different recurrence properties of the timedependent source have been discussed. The results obtained from the analyses highlight a significant influence of timedependent hazard properties on the structural capacity required to attain a target reliability, and give evidence to the different roles played by the parameters considered in the analysis. Moreover, in order to deeper investigate the effect of timedependent seismic hazard on structural design, the influence of soil classification, period and the GMPE implemented in the analysis have been assessed and the results discussed extensively. The analysis outcomes illustrate the remarkable impact of soil and period on structural response as well as the importance of appropriate GMPE used for the timedependent seismic hazard. Furthermore, machinelearning (ML) based models have been proposed for deriving fragility curves of buildings. Generating fragility curves is a critical key step in the PerformanceBased Earthquake Engineering (PBEE) framework which is generally timeconsuming. The accuracy of the quick accurate models proved the high reliability of MLbased techniques for obtaining fragility parameters namely dispersion and median. The developed MLbased prediction models could be used for estimating capacity (both timedependent and timeindependent cases) in further studies.
New approach for seismic hazard analysis and earthquake damage scenarios
DABIRI, HAMED
20220919
Abstract
Seismic hazard causes a considerable portion of loss in many countries annually and thus is of high importance. Seismic hazard and its consequences, known as seismic risk, have been studied in the fields of geology, earthquake engineering and structural engineering in the framework of probabilistic seismic hazard analysis (PSHA). PSHA could be simply defined as the probability of occurrence of an earthquake characteristic (e.g., PGA), considering uncertainties namely magnitude, location and their resulting ground motion specified by ground motion prediction equation (GMPE). The final output of PSHA is the rate of exceeding specific intensity measure (IM), and could be expressed in terms of return period exceedance. For structural design purposes, for a given probability and structure’s design life, the seismic hazard could be stated in terms of return period TR, which is commonly applied in current design code (e.g., Eurocode 8). The abovementioned explanations of return period of exceedance are based on the Poisson relationship between time and earthquake which assumes that the probability of an earthquake occurring remains unchanged by elapsing time. In the recent decades, however, it has been claimed that earthquake occurrence could be expressed through timedependent models which means that elapsing time since the last earthquake affects its occurrence probability. This research focuses mainly on the effect of timedependent seismic hazard on structural design, by evaluating the strength required by the structure (seismic capacity) for different time intervals elapsing from the last event. “Seismic capacity” is defined as the capacity required to provide a fixed failure rate. Two different seismic scenarios (i. e., a point source and a combined source including area and line source) have been investigated and results concerning different sitetosource distance, capacity dispersion of the structure and different recurrence properties of the timedependent source have been discussed. The results obtained from the analyses highlight a significant influence of timedependent hazard properties on the structural capacity required to attain a target reliability, and give evidence to the different roles played by the parameters considered in the analysis. Moreover, in order to deeper investigate the effect of timedependent seismic hazard on structural design, the influence of soil classification, period and the GMPE implemented in the analysis have been assessed and the results discussed extensively. The analysis outcomes illustrate the remarkable impact of soil and period on structural response as well as the importance of appropriate GMPE used for the timedependent seismic hazard. Furthermore, machinelearning (ML) based models have been proposed for deriving fragility curves of buildings. Generating fragility curves is a critical key step in the PerformanceBased Earthquake Engineering (PBEE) framework which is generally timeconsuming. The accuracy of the quick accurate models proved the high reliability of MLbased techniques for obtaining fragility parameters namely dispersion and median. The developed MLbased prediction models could be used for estimating capacity (both timedependent and timeindependent cases) in further studies.File  Dimensione  Formato  

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