The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions.Moreover,not all near-fault ground motion records present...The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions.Moreover,not all near-fault ground motion records present distinct pulses in the velocity time histories.In this paper,the parameterized stochastic model of near-fault ground motion with the strongest energy and pulse occurrence probability is suggested,and the Monte Carlo simulation(MSC)and subset simulation are utilized to calculate the first excursion probability of inelastic single-degree-of-freedom(SDOF)systems subjected to these types of near-fault ground motion models,respectively.Firstly,the influences of variation of stochastic pulse model parameters on structural dynamic reliability with different fundamental periods are explored.It is demonstrated that the variation of pulse period,peak ground velocity and pulse waveform number have significant effects on structural reliability and should not be ignored in reliability analysis.Then,subset simulation is verified to be unbiased and more efficient for computing small reliable probabilities of structures compared to MCS.Finally,the reliable probabilities of the SDOF systems with different fundamental periods subjected to impulsive,non-pulse ground motions and the ground motions with pulse occurrence probability are performed,separately.It is indicated that the ground motion model with the pulse occurrence probability can give a rational estimate on structural reliability.The impulsive and ordinary ground motion models may overestimate and underestimate the reliability of structures with fundamental period much less than the mean pulse period of earthquake ground motions.展开更多
In this paper,the influence of ground motion duration on the inelastic displacement ratio,C_(1),of highly damped SDOF systems is studied.For this purpose,two sets of spectrally equivalent long and short duration groun...In this paper,the influence of ground motion duration on the inelastic displacement ratio,C_(1),of highly damped SDOF systems is studied.For this purpose,two sets of spectrally equivalent long and short duration ground motion records were used in an analysis to isolate the effects of ground motion duration on.The effect of duration was evaluated for observed values of C_(1) by considering six ductility levels,and different damping and post-yield stiffness ratios.A new predictive equation of C_(1) also was developed for long and short duration records.Results of non-linear regression analysis of the current study provide an expression with which to quantify the duration effect.Based on the average values of estimated C_(1) ratios for long duration records divided by C_(1) for a short duration set,it is concluded that the maximum difference between long and short duration records occurs when the damping ratio is 0.3 and the post-yield stiffness ratio is equal to zero.展开更多
Assessing the potential damage caused by earthquakes is crucial for a community’s emergency response.In this study,four machine learning(ML)methods—random forest,extremely randomized trees,AdaBoost(AB),and gradient ...Assessing the potential damage caused by earthquakes is crucial for a community’s emergency response.In this study,four machine learning(ML)methods—random forest,extremely randomized trees,AdaBoost(AB),and gradient boosting(GB)—were employed to develop prediction models for the damage potential of the mainshock(DIMS)and mainshock–aftershock sequences(DIMA).Building structures were modeled using eight single-degree-of-freedom(SDOF)systems with different hysteretic rules.A set of 662 recorded mainshock–aftershock(MS-AS)ground motions was selected from the PEER database.Seven intensity measures(IMs)were chosen to represent the characteristics of the mainshock and aftershock.The results revealed that the selected ML methods can well predict the structural damage potential of the SDOF systems,except for the AB method.The GB model exhibited the best performance,making it the recommended choice for predicting DIMS and DIMA among the four ML models.Additionally,the impact of input variables in the prediction was investigated using the shapley additive explanations(SHAP)method.The high-correlation variables were sensitive to the structural period(T).At T=1.0 s,the mainshock peak ground velocity(PGVM)and aftershock peak ground displacement(PGDA)significantly influenced the prediction of DIMA.When T increased to 5.0 s,the primary high-correlation factor of the mainshock IMs changed from PGVM to the mainshock peak ground displacement(PGDM);however,the highcorrelation variable of the aftershock IMs remained PGDA.The high-correlation factors for DIMS showed trends similar to those of DIMA.Finally,a table summarizing the first and second high-correlation variables for predicting DIMS and DIMA were provided,offering a valuable reference for parameter selection in seismic damage prediction for mainshock–aftershock sequences.展开更多
基金supports of the National Natural Science Foundation of China(Grant Nos.51478086 and 11672167)Shandong Province Natural Science Foundation of China(Grant No.ZR2015EL048)are much appreciated.
文摘The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions.Moreover,not all near-fault ground motion records present distinct pulses in the velocity time histories.In this paper,the parameterized stochastic model of near-fault ground motion with the strongest energy and pulse occurrence probability is suggested,and the Monte Carlo simulation(MSC)and subset simulation are utilized to calculate the first excursion probability of inelastic single-degree-of-freedom(SDOF)systems subjected to these types of near-fault ground motion models,respectively.Firstly,the influences of variation of stochastic pulse model parameters on structural dynamic reliability with different fundamental periods are explored.It is demonstrated that the variation of pulse period,peak ground velocity and pulse waveform number have significant effects on structural reliability and should not be ignored in reliability analysis.Then,subset simulation is verified to be unbiased and more efficient for computing small reliable probabilities of structures compared to MCS.Finally,the reliable probabilities of the SDOF systems with different fundamental periods subjected to impulsive,non-pulse ground motions and the ground motions with pulse occurrence probability are performed,separately.It is indicated that the ground motion model with the pulse occurrence probability can give a rational estimate on structural reliability.The impulsive and ordinary ground motion models may overestimate and underestimate the reliability of structures with fundamental period much less than the mean pulse period of earthquake ground motions.
文摘In this paper,the influence of ground motion duration on the inelastic displacement ratio,C_(1),of highly damped SDOF systems is studied.For this purpose,two sets of spectrally equivalent long and short duration ground motion records were used in an analysis to isolate the effects of ground motion duration on.The effect of duration was evaluated for observed values of C_(1) by considering six ductility levels,and different damping and post-yield stiffness ratios.A new predictive equation of C_(1) also was developed for long and short duration records.Results of non-linear regression analysis of the current study provide an expression with which to quantify the duration effect.Based on the average values of estimated C_(1) ratios for long duration records divided by C_(1) for a short duration set,it is concluded that the maximum difference between long and short duration records occurs when the damping ratio is 0.3 and the post-yield stiffness ratio is equal to zero.
基金China Postdoctoral Science Foundation under Grant No.2022M710333the Beijing Postdoctoral Research Foundation under Grant No.2023-zz-141the National Natural Science Foundation of China under Grant Nos.52278492 and 52078176。
文摘Assessing the potential damage caused by earthquakes is crucial for a community’s emergency response.In this study,four machine learning(ML)methods—random forest,extremely randomized trees,AdaBoost(AB),and gradient boosting(GB)—were employed to develop prediction models for the damage potential of the mainshock(DIMS)and mainshock–aftershock sequences(DIMA).Building structures were modeled using eight single-degree-of-freedom(SDOF)systems with different hysteretic rules.A set of 662 recorded mainshock–aftershock(MS-AS)ground motions was selected from the PEER database.Seven intensity measures(IMs)were chosen to represent the characteristics of the mainshock and aftershock.The results revealed that the selected ML methods can well predict the structural damage potential of the SDOF systems,except for the AB method.The GB model exhibited the best performance,making it the recommended choice for predicting DIMS and DIMA among the four ML models.Additionally,the impact of input variables in the prediction was investigated using the shapley additive explanations(SHAP)method.The high-correlation variables were sensitive to the structural period(T).At T=1.0 s,the mainshock peak ground velocity(PGVM)and aftershock peak ground displacement(PGDA)significantly influenced the prediction of DIMA.When T increased to 5.0 s,the primary high-correlation factor of the mainshock IMs changed from PGVM to the mainshock peak ground displacement(PGDM);however,the highcorrelation variable of the aftershock IMs remained PGDA.The high-correlation factors for DIMS showed trends similar to those of DIMA.Finally,a table summarizing the first and second high-correlation variables for predicting DIMS and DIMA were provided,offering a valuable reference for parameter selection in seismic damage prediction for mainshock–aftershock sequences.
