Seismic vulnerability estimation of RC structures considering empirical and numerical simulation methods

Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using various intensity measures to estimate and forecast the seismic hazard of RC structures can contribute to the development of typical structural...

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Published inArchives of Civil and Mechanical Engineering Vol. 24; no. 2; p. 68
Main Authors Li, Si-Qi, Du, Ke, Li, Yi-Ru, Han, Jia-Cheng, Qin, Peng-Fei, Liu, Hong-Bo
Format Journal Article
LanguageEnglish
Published London Springer London 05.03.2024
Springer Nature B.V
Subjects
Accuracy
Algorithms
Artificial intelligence
Civil Engineering
Computer simulation
Data points
Design optimization
Design specifications
Dynamic structural analysis
Earthquake damage
Earthquake resistance
Earthquakes
Empirical analysis
Engineering
Estimation
Finite element analysis
Finite element method
Fragility
Frame structures
Fuzzy logic
Fuzzy sets
Machine learning
Masonry
Mathematical models
Mechanical Engineering
Nonlinear dynamics
Numerical methods
Numerical models
Original Article
Performance evaluation
Regression analysis
Reinforced concrete
Reinforcing steels
Risk analysis
Risk assessment
Seismic engineering
Seismic hazard
Seismic response
Simulation
Software
Statistical analysis
Structural damage
Structural Materials
Structural models
Temperature effects
Italy
China
Numerical simulation analysis
Empirical seismic vulnerability
Structural failure analysis
Damage modal analysis
Reinforced concrete structure
Online AccessGet full text
ISSN2083-3318
1644-9665
2083-3318
DOI10.1007/s43452-024-00874-0

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Abstract Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using various intensity measures to estimate and forecast the seismic hazard of RC structures can contribute to the development of typical structural seismic resilience and vulnerability models. However, traditional empirical and analytical vulnerability studies rely more on field observation data and seismic risk algorithms and less on numerical simulation analysis for validation and optimization, resulting in limitations and fuzziness in the accuracy of the developed structural risk models. To explore the damage modes of RC frame structures under different intensities, this paper innovatively combines numerical model algorithms with empirical vulnerability methods to conduct empirical vulnerability and numerical simulation analyses on RC structures. Using probability statistics and nonlinear regression analysis methods, a prediction model for estimating the fragility of RC structures was proposed, and 858 RC structure damage samples from a typical city (Dujiangyan) during the Wenchuan earthquake in China on May 12, 2008, were used for model verification and comparative analysis. Using seismic response analysis theory, 901,530 acceleration records of the Wenchuan earthquake detected by eight actual seismic stations were selected, and nonlinear dynamic time history analysis was conducted. A four-story RC structural model was established using finite element software, and numerical simulation analysis was conducted on the model using 117,863 real earthquake acceleration data points obtained from actual monitoring stations during the Wenchuan earthquake. The acceleration time history curves and incremental dynamic analysis curves of the RC structure under different intensity measures were generated. By combining the moire algorithm and numerical simulation technology, damage stress clouds of steel bars and concrete under different intensity measures were generated, and the accuracy of the developed empirical vulnerability model was verified via numerical simulation results.
AbstractList Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using various intensity measures to estimate and forecast the seismic hazard of RC structures can contribute to the development of typical structural seismic resilience and vulnerability models. However, traditional empirical and analytical vulnerability studies rely more on field observation data and seismic risk algorithms and less on numerical simulation analysis for validation and optimization, resulting in limitations and fuzziness in the accuracy of the developed structural risk models. To explore the damage modes of RC frame structures under different intensities, this paper innovatively combines numerical model algorithms with empirical vulnerability methods to conduct empirical vulnerability and numerical simulation analyses on RC structures. Using probability statistics and nonlinear regression analysis methods, a prediction model for estimating the fragility of RC structures was proposed, and 858 RC structure damage samples from a typical city (Dujiangyan) during the Wenchuan earthquake in China on May 12, 2008, were used for model verification and comparative analysis. Using seismic response analysis theory, 901,530 acceleration records of the Wenchuan earthquake detected by eight actual seismic stations were selected, and nonlinear dynamic time history analysis was conducted. A four-story RC structural model was established using finite element software, and numerical simulation analysis was conducted on the model using 117,863 real earthquake acceleration data points obtained from actual monitoring stations during the Wenchuan earthquake. The acceleration time history curves and incremental dynamic analysis curves of the RC structure under different intensity measures were generated. By combining the moire algorithm and numerical simulation technology, damage stress clouds of steel bars and concrete under different intensity measures were generated, and the accuracy of the developed empirical vulnerability model was verified via numerical simulation results.
ArticleNumber 68
Author Qin, Peng-Fei
Du, Ke
Liu, Hong-Bo
Li, Si-Qi
Han, Jia-Cheng
Li, Yi-Ru
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  surname: Liu
  fullname: Liu, Hong-Bo
  organization: School of Civil Engineering, Heilongjiang University
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Keywords Numerical simulation analysis
Empirical seismic vulnerability
Structural failure analysis
Damage modal analysis
Reinforced concrete structure
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SSID ssj0001072165
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Snippet Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using...
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SubjectTerms Accuracy
Algorithms
Artificial intelligence
Civil Engineering
Computer simulation
Data points
Design optimization
Design specifications
Dynamic structural analysis
Earthquake damage
Earthquake resistance
Earthquakes
Empirical analysis
Engineering
Estimation
Finite element analysis
Finite element method
Fragility
Frame structures
Fuzzy logic
Fuzzy sets
Machine learning
Masonry
Mathematical models
Mechanical Engineering
Nonlinear dynamics
Numerical methods
Numerical models
Original Article
Performance evaluation
Regression analysis
Reinforced concrete
Reinforcing steels
Risk analysis
Risk assessment
Seismic engineering
Seismic hazard
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Temperature effects
Title Seismic vulnerability estimation of RC structures considering empirical and numerical simulation methods
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Volume 24
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