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

• Autorzy: Li Si-Qi , Du Ke , Li Yi‑Ru , Han Jia-Cheng , Qin Peng-Fei , Liu Hong-Bo

Identyfikatory

DOI

10.1007/s43452-024-00874-0

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

empirical seismic vulnerability; numerical simulation analysis; reinforced concrete structure; damage modal analysis; structural failure analysis

PL

wstrząs sejsmiczny; analiza numeryczna; konstrukcja żelbetowa; analiza modalna uszkodzeń; analiza uszkodzeń konstrukcyjnych

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2024
• Tom: Vol. 24, no. 2
• Strony: art. no. e68, 2024
• Opis fizyczny: Bibliogr. 62 poz., fot., rys., tab., wykr.

Twórcy

autor

Li Si-Qi

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China
• Institute of Engineering Mechanics, China Earthquake Administration, Key Laboratory of Earthquake Disaster Mitigation, Ministry of Emergency Management, Heilongjiang University Key Laboratory of Earthquake Engineering and Engineering Vibration, Harbin Institute of Technology, Harbin, China

• https://orcid.org/0000-0002-2761-9116

autor

Du Ke

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China

autor

Li Yi‑Ru

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China

autor

Han Jia-Cheng

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China

autor

Qin Peng-Fei

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China

autor

Liu Hong-Bo

• School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin, China

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).