This paper evaluates the seismic vulnerability of different classes of typical bridges in California when subjected to seismic shaking or liquefaction-induced lateral spreading. The detailed structural configurations ...This paper evaluates the seismic vulnerability of different classes of typical bridges in California when subjected to seismic shaking or liquefaction-induced lateral spreading. The detailed structural configurations in terms of superstructure type, connection, continuity at support and foundation type, etc. render different damage resistant capability. Six classes of bridges are established based on their anticipated failure mechanisms under earthquake shaking. The numerical models that are capable of simulating the complex soil-structure interaction effects, nonlinear behavior of columns and connections are developed for each bridge class. The dynamic responses are obtained using nonlinear time history analyses for a suite of 250 earthquake motions with increasing intensity. An equivalent static analysis procedure is also implemented to evaluate the vulnerability of the bridges when subjected to liquefaction-induced lateral spreading. Fragility functions for each bridge class are derived and compared for both seismic shaking （based on nonlinear dynamic analyses） and lateral spreading （based on equivalent static analyses） for different performance states. The study finds that the fragility functions due to either ground shaking or lateral spreading show significant correlation with the structural characterizations, but differences emerge for ground shaking and lateral spreading conditions. Structural properties that will mostly affect the bridges＇ damage resistant capacity are also identified.展开更多
The seismic behavior of a large diameter extended pile shaft founded on a dense sandy site is investigated in this paper. First, a deterministic analysis is conducted including both nonlinear dynamic analysis （NDA） ...The seismic behavior of a large diameter extended pile shaft founded on a dense sandy site is investigated in this paper. First, a deterministic analysis is conducted including both nonlinear dynamic analysis （NDA） and pushover analysis to gain insights into the behavior of the pile and make sure an appropriate modeling technique is utilized. Then a probabilistic analysis is performed using the results of NDA for various demands. To this end a set of 40 pulse-like ground motions are picked and subsequently 40 nonlinear dynamic and pushover analyses are performed. The data obtained from NDA are used to generate probabilistic seismic demand model （PSDM） plots and consequently the median line and dispersion for each plot are computed. The NDA and pushover data are also plotted against each other to find out to what extent they are correlated. These operations are done for various engineering demand parameters （EDPs）. A sensitivity analysis is done to pick the most appropriate intensity measure （IM） which would cause a minimum dispersion in PSDM plots out of 7 different IMs. Peak ground acceleration （PGA） is found to be the most appropriate IM. Pushover coefficient equations as a function of PGA are proposed which can be applied to the pushover analysis data to yield a better outcome with respect to the NDA. At the end, the pacific earthquake engineering research （PEER） center methodology is utilized to generate the fragility curves using the properties obtained from PSDM plots and considering various states of damage ranging from minor to severe. The extended pile shaft shows more vulnerability with a higher probability with respect to minor damage compared to severe damage.展开更多
Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tun...Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tunnel burial depth,tunnel construction quality,and aging phenomena of the lining,on the direct seismic losses of circular tunnels in alluvial deposits when exposed to ground seismic shaking.For this purpose,a practical approach is employed to probabilistically assess the direct losses of single tunnel segment with unit length,as well as of tunnel elements representative of the Shanghai Metro Lines 1 and 10,assuming various levels of seismic intensity.The findings of this study can serve as the basis for decision-making,seismic loss,and risk management based on the principles of infrastructure resilience.展开更多
This study presents a hybrid methodology for predicting building collapses within the Intelligent Circular Resilience(ICR)framework.This uses a supervised Machine Learning(ML)approach,earthquake damage re-ports,and th...This study presents a hybrid methodology for predicting building collapses within the Intelligent Circular Resilience(ICR)framework.This uses a supervised Machine Learning(ML)approach,earthquake damage re-ports,and the Simplified Resilience Index(SRI),derived from existing earthquake damage models(EDM)-based on fragility and vulnerability functions-used in the probabilistic seismic risk assessment(PSRA).A curated building damage database comprising 89 structures(71 collapsed and 18 non-collapsed)from ten countries affected by major earthquakes(Mw 6.1-8.1,epicentral distances of 3-125 km,and PGA values ranging from 0.14 g to 0.82 g)was developed,including attributes related to exposure:occupancy,main structural material,number of stories,construction year,and hazard:magnitude,epicentral distance,intensity measures(Peak-ground acceleration,PGA,and elastic spectral acceleration).The dataset includes events such as the 2017 Puebla-Morelos earthquake(Mw 7.1,Mexico),the 1999 Kocaeli earthquake(Mw 7.6,Turkey),and the 2011 Christchurch earthquake(Mw 6.1,New Zealand),among others.Likewise,dependent attributes such as time elapsed and SRI(under 120-,180-,and 365-day recovery scenarios)were calculated using 2-EDMs.Eight Random Forest models were trained and tested for collapse and non-collapse classification using combinations of independent and dependent attributes.The results indicate that models incorporating exposure-related varia-bles-such as structural material,number of stories,construction year,and occupancy-alongside the SRI significantly improve collapse classification performance,achieving recall and F1 scores above 95%.Notably,many collapsed buildings exhibited low intensities(PGA≤0.25 g),emphasizing the influence of local site effects-particularly in Mexico City.The findings demonstrate that incorporating SRI enhances the reliability of collapse prediction and supports its use as an interpretable resilience proxy during early ICR stages.This hybrid methodology bridges empirical data,traditional PSRA models,and ML techniques,contributing to more accurate and scalable post-earthquake resilience assessments.展开更多
基金Supported by:Pacific Earthquake Engineering Research Center Lifelines Program Under Project Task No.9C
文摘This paper evaluates the seismic vulnerability of different classes of typical bridges in California when subjected to seismic shaking or liquefaction-induced lateral spreading. The detailed structural configurations in terms of superstructure type, connection, continuity at support and foundation type, etc. render different damage resistant capability. Six classes of bridges are established based on their anticipated failure mechanisms under earthquake shaking. The numerical models that are capable of simulating the complex soil-structure interaction effects, nonlinear behavior of columns and connections are developed for each bridge class. The dynamic responses are obtained using nonlinear time history analyses for a suite of 250 earthquake motions with increasing intensity. An equivalent static analysis procedure is also implemented to evaluate the vulnerability of the bridges when subjected to liquefaction-induced lateral spreading. Fragility functions for each bridge class are derived and compared for both seismic shaking （based on nonlinear dynamic analyses） and lateral spreading （based on equivalent static analyses） for different performance states. The study finds that the fragility functions due to either ground shaking or lateral spreading show significant correlation with the structural characterizations, but differences emerge for ground shaking and lateral spreading conditions. Structural properties that will mostly affect the bridges＇ damage resistant capacity are also identified.
文摘The seismic behavior of a large diameter extended pile shaft founded on a dense sandy site is investigated in this paper. First, a deterministic analysis is conducted including both nonlinear dynamic analysis （NDA） and pushover analysis to gain insights into the behavior of the pile and make sure an appropriate modeling technique is utilized. Then a probabilistic analysis is performed using the results of NDA for various demands. To this end a set of 40 pulse-like ground motions are picked and subsequently 40 nonlinear dynamic and pushover analyses are performed. The data obtained from NDA are used to generate probabilistic seismic demand model （PSDM） plots and consequently the median line and dispersion for each plot are computed. The NDA and pushover data are also plotted against each other to find out to what extent they are correlated. These operations are done for various engineering demand parameters （EDPs）. A sensitivity analysis is done to pick the most appropriate intensity measure （IM） which would cause a minimum dispersion in PSDM plots out of 7 different IMs. Peak ground acceleration （PGA） is found to be the most appropriate IM. Pushover coefficient equations as a function of PGA are proposed which can be applied to the pushover analysis data to yield a better outcome with respect to the NDA. At the end, the pacific earthquake engineering research （PEER） center methodology is utilized to generate the fragility curves using the properties obtained from PSDM plots and considering various states of damage ranging from minor to severe. The extended pile shaft shows more vulnerability with a higher probability with respect to minor damage compared to severe damage.
基金support of the National Natural Science Foundation of China(Grants No.52108381,51978517,52090082)the National Key R&D Program(Grant No.2021YFF0502200)the China Postdoctoral Science Foundation(Grants No.2022T150484,2021M702491).
文摘Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tunnel burial depth,tunnel construction quality,and aging phenomena of the lining,on the direct seismic losses of circular tunnels in alluvial deposits when exposed to ground seismic shaking.For this purpose,a practical approach is employed to probabilistically assess the direct losses of single tunnel segment with unit length,as well as of tunnel elements representative of the Shanghai Metro Lines 1 and 10,assuming various levels of seismic intensity.The findings of this study can serve as the basis for decision-making,seismic loss,and risk management based on the principles of infrastructure resilience.
基金Vicerrectoría de Inves-tigaciones of the UMNG for the financial support of the IMP-ING-3743 Project.
文摘This study presents a hybrid methodology for predicting building collapses within the Intelligent Circular Resilience(ICR)framework.This uses a supervised Machine Learning(ML)approach,earthquake damage re-ports,and the Simplified Resilience Index(SRI),derived from existing earthquake damage models(EDM)-based on fragility and vulnerability functions-used in the probabilistic seismic risk assessment(PSRA).A curated building damage database comprising 89 structures(71 collapsed and 18 non-collapsed)from ten countries affected by major earthquakes(Mw 6.1-8.1,epicentral distances of 3-125 km,and PGA values ranging from 0.14 g to 0.82 g)was developed,including attributes related to exposure:occupancy,main structural material,number of stories,construction year,and hazard:magnitude,epicentral distance,intensity measures(Peak-ground acceleration,PGA,and elastic spectral acceleration).The dataset includes events such as the 2017 Puebla-Morelos earthquake(Mw 7.1,Mexico),the 1999 Kocaeli earthquake(Mw 7.6,Turkey),and the 2011 Christchurch earthquake(Mw 6.1,New Zealand),among others.Likewise,dependent attributes such as time elapsed and SRI(under 120-,180-,and 365-day recovery scenarios)were calculated using 2-EDMs.Eight Random Forest models were trained and tested for collapse and non-collapse classification using combinations of independent and dependent attributes.The results indicate that models incorporating exposure-related varia-bles-such as structural material,number of stories,construction year,and occupancy-alongside the SRI significantly improve collapse classification performance,achieving recall and F1 scores above 95%.Notably,many collapsed buildings exhibited low intensities(PGA≤0.25 g),emphasizing the influence of local site effects-particularly in Mexico City.The findings demonstrate that incorporating SRI enhances the reliability of collapse prediction and supports its use as an interpretable resilience proxy during early ICR stages.This hybrid methodology bridges empirical data,traditional PSRA models,and ML techniques,contributing to more accurate and scalable post-earthquake resilience assessments.
