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Statistical model analysis of typical bridges considering the actual seismic damage observation database

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
To study the seismic vulnerabilities and performances of typical bridges, data from a field investigation of 2134 bridges on 22 highway sections hit by the Wenchuan earthquake that occurred in China on May 12, 2008, were collected and processed. From the sample data of the empirical seismic-damage observations, 1409 simply supported girder bridges, 107 continuous girder bridges, and 612 arch bridges were selected. The latest version of the Chinese seismic intensity standard was utilized to evaluate the fragility of bridge samples in different macroseismic intensity zones, and the empirical vulnerability matrix and multidimensional regression comparison model of typical bridge clusters were developed. Taking the bridge length, the coordinate azimuth of the bridge location, the number of spans, the geometric form of the pier columns, and the type of bearings and foundations as the single factors influencing vulnerability and assuming (i) the line type and bridge length, (ii) the types of pier column and foundation, and (iii) the number of spans, the type of bearings, foundations, and linearity as the coupled factors influencing vulnerability, the aforementioned typical bridges were subjected to comparative vulnerability analysis. Innovative fragility regression and probability comparison models of typical bridges were developed considering the influence of multiple factor coupling. A novel vulnerability evaluation model was proposed based on the characteristic parameters and damage grade of bridge clusters in the umbrella earthquake area, and the model was optimized and verified by using the typical bridge database of the Wenchuan earthquake.
Rocznik
Strony
art. no. e178, 2023
Opis fizyczny
Bibliogr. 40 poz., rys., wykr.
Twórcy
autor
  • School of Civil Engineering, Heilongjiang University, No. 74, Xuefu Road, Harbin City, China
  • Longjian Road and Bridge Co., Ltd, No. 109, Songshan Road, Harbin City, China
  • School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin City, China
  • Department of Structures for Engineering and Architecture, School of Polytechnic and Basic Sciences, University of Naples “Federico II”, Naples, Italy
Bibliografia
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  • 4. Li SS, Wei B, Tan H, Li CB, Zhao XM. Equivalence of friction and viscous damping in a spring-friction system with concave friction distribution. J Test Eval. 2021;49(1):372–95. https://doi. org/10.1520/JTE20190885.
  • 5. Perdomo C, Monteiro R, Sucuoğlu H. Development of fragility curves for single-column RC Italian bridges using nonlinear static analysis. J Earthquake Eng. 2020;26(5):2328–52. https://doi.org/ 10.1080/13632469.2020.1760153.
  • 6. Cademartori M, Sullivan TJ, Osmani S. Displacement- based assessment of typical Italian RC bridges. Bull Earthq Eng. 2020;18(9):4299–329. https:// doi. org/ 10. 1007/ s10518-020-00861-9.
  • 7. Padgett JE, DesRoches R. Methodology for the development of analytical fragility curves for retrofitted bridges. Earthquake Eng Struct Dyn. 2008;37:1157–74. https://doi.org/10.1002/eqe.801.
  • 8. Li SQ, Liu HB. Vulnerability prediction model of typical struc- tures considering empirical seismic damage observation data. Bull Earthq Eng. 2022;20:5161–203. https:// doi. org/ 10. 1007/ s10518-022-01395-y.
  • 9. Soleimani F. Propagation and quantification of uncertainty in the vulnerability estimation of tall concrete bridges. Eng Struct. 2020;202:109812. https:// doi. org/ 10. 1016/j. engst ruct. 2019. 109812.
  • 10. Bhuiyan MAR, Alam MS. Seismic vulnerability assessment of a multi-span continuous highway bridge fitted with shape memory alloy bars and laminated rubber bearings. Earthq Spectra. 2012;28(4):1379–404. https://doi.org/10.1193/1.4000089.
  • 11. Kappos AJ, Manolis GD, Moschonas IF. Seismic assessment and design of R/C bridges with irregular congiguration, including SSI effects. Eng Struct. 2002;24(10):1337–48. https://doi. org/10.1016/S0141-0296(02)00068-8.
  • 12. Agalianos A, Sieber M, Anastasopoulos I. Cost-effective analy- sis technique for the design of bridges against strike-slip faulting. Earthquake Eng Struct Dyn. 2020;49(11):1137–57. https:// doi.org/10.1002/eqe.3282.
  • 13. Tong T, Lei H, Yuan S, Liu Z. Experimental investigation and seismic vulnerability assessment of low flexural strength rectangular bridge piers retrofitted with ultrahigh-performanceconcrete jackets. Eng Struct. 2020;206:110132. https://doi.org/ 10.1016/j.engstruct.2019.110132.
  • 14. Attary N, Symans M, Nagarajaiah S, Reinhorn AM, Constantinou MC, Sarlis AA, Pasala DTR, Taylor DP. Experimental shake table testing of an adaptive passive negative stiffness device within a highway bridge model. Earthq Spectra. 2015;31(4):2163–94. https://doi.org/10.1193/101913EQS273M.
  • 15. Li SQ, Liu HB. Comparison of vulnerabilities in typical bridges using macroseismic intensity scales. Case Stud Constr Mater. 2022;16:e01094. https://doi.org/10.1016/j.cscm.2022.e01094.
  • 16. Lew SW, Wotherspoon L, Hogan L, Ai-Ani M, Chigullapally P, Sadashiva V. Assessment of the historic seismic performance of the New Zealand highway bridge stock. Struct Infrastruct Eng. 2020;17(5):689–701. https://doi.org/10.1080/15732479.2020. 1762675.
  • 17. Li SQ, Chen YS, Liu HB, Du K. Empirical seismic fragility rapid prediction probability model of regional group reinforced concrete girder bridges. Earthquakes Struct. 2022;22(6):609– 23. https://doi.org/10.12989/eas.2022.22.6.609.
  • 18. Padgett JE, DesRoches R, Nilsson E. Regional seismic risk assessment of bridge network in Charleston, South Carolina. J Earthquake Eng. 2010;14:918–33. https:// doi. org/ 10. 1080/ 13632460903447766.
  • 19. Li SQ, Liu HB, Farsangi EN, Du K. Seismic fragility estima- tion considering field inspection of reinforced concrete girder bridges. Struct Infrastruct Eng. 2023. https://doi.org/10.1080/ 15732479.2023.2208565.
  • 20. Li SQ. Empirical resilience and vulnerability model of regional group structure considering optimized macroseismic intensity measure. Soil Dyn Earthquake Eng. 2023;164:107630. https:// doi.org/10.1016/j.soildyn.2022.107630.
  • 21. Li SQ, Chen YS, Yu TL. Comparison of macroseismic intensity scales by considering empirical observations of structural seismic damage. Earthq Spectra. 2021;37(1):449–85. https:// doi.org/10.1177/8755293020944174.
  • 22. Li SQ, Liu HB. Analysis of probability matrix model for seismic damage vulnerability of highway bridges. Geomat Nat Haz Risk. 2022;13(1):1395–421. https://doi.org/10.1080/19475705. 2022.2077146.
  • 23. Li SQ, Chen YS. Vulnerability and economic loss evaluation model of a typical group structure considering empirical field inspection data. Int J Disaster Risk Reduct. 2023;88:103617. https://doi.org/10.1016/j.ijdrr.2023.103617.
  • 24. GB/T 17742. (2020) The Chinese seismic intensity scale. (In Chinese).
  • 25. Li SQ, Chen YS, Liu HB, Del Gaudio C. Empirical seismic vulnerability assessment model of typical urban buildings. Bull Earthq Eng. 2023. https://doi.org/10.1007/s10518-022-01585-8.
  • 26. GB/T 24336 (2009) Classification of earthquake damage to life- line engineering. (In Chinese).
  • 27. Li SQ, Chen YS. Analysis of the probability matrix model for the seismic damage vulnerability of empirical structures. Nat Hazards. 2020;104(1):705–30. https:// doi. org/ 10. 1007/ s11069-020-04187-2.
  • 28. JTG/TB02-01 (2008) Guidelines for seismic design of highway bridges. (In Chinese).
  • 29. JTG/T 2231-01. (2020) Specifications for seismic design of high- way bridges. (In Chinese).
  • 30. GB/T 17742 (2008) The Chinese seismic intensity scale. (In Chinese).
  • 31. Li SQ. Comparison of RC girder bridge and building vulnerability considering empirical seismic damage. Ain Shams Eng J. 2023. https://doi.org/10.1016/j.asej.2023.102287.
  • 32. Li SQ. Empirical vulnerability estimation models considering updating the structural earthquake damage database. Soil Dyn Earthquake Eng. 2023. https://doi.org/10.1016/j.soildyn.2023. 107864.
  • 33. Formisano A, Chieffo N. Seismic damage scenarios induced by site effects on masonry clustered buildings: a case study in south Italy. Int J Architect Herit. 2022. https://doi.org/10.1080/15583 058.2022.2104143.
  • 34. Chieffo N, Clementi F, Formisano A, Lenci S. Comparative fragil- ity methods for seismic assessment of masonry buildings located in Muccia (Italy). J Build Eng. 2019;25:100813. https://doi.org/ 10.1016/j.jobe.2019.100813.
  • 35. Li SQ, Gardoni P. Empirical seismic vulnerability models for building clusters considering hybrid intensity measures. J Build Eng. 2023;68:106130. https:// doi. org/ 10. 1016/j. jobe. 2023. 106130.
  • 36. Chen LS, Zhuang WL, Zhao QH. Report on highways damage in the Wenchuan earthquake. Beijing: China Communications Press; 2012.
  • 37. Li SQ, Chen YS, Liu HB, Du K, Chi B. Assessment of seismic damage inspection and empirical vulnerability probability matri- ces for masonry structure. Earthquakes Struct. 2022;22(4):387– 99. https://doi.org/10.12989/eas.2022.22.4.387.
  • 38. Li SQ, Liu HB, Du K, Han JC, Li YR, Yin LH. Empirical seis- mic vulnerability probability prediction model of RC struc- tures considering historical field observation. Struct Eng Mech. 2023;86(4):547–71. https://doi.org/10.12989/sem.2023.86.4.547.
  • 39. Del Gaudio C, Martino GD, Ludovico MD, Manfredi G, Prota A, Ricci P, Verderame GM. Empirical fragility curves from damage data on RC buildings after the 2009 L’Aquila earthquake. Bull Earthq Eng. 2017;15:1425–50. https:// doi. org/ 10. 1007/ s10518-016-0026-1.
  • 40. Li SQ. Comparison of empirical structural vulnerability rapid prediction models considering typical earthquakes. Structures. 2023;49:377–401. https://doi.org/10.1016/j.istruc.2023.01.130.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-651a71e5-ecaf-48b1-bc74-07f37116d298
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