Effect of R, µ and T on the Fragility Curves for Two Spans Reinforced Concrete Highway Bridges

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Abstract

Fragility curves are useful tools for evaluating the probability of structural damage due to earthquakes as a function of ground motion indices. The force reduction factor (R) is one of the seismic design parameters that determine the nonlinear performance of building structures during strong earthquakes. R factor itself is mostly a function of displacement ductility (µ), natural period of a structure, and soil conditions. A statistical method (Path Analysis) is proposed for the first time to determine the effect of R, µ and T on the column fragility curve parameters of typical box girder, two spans reinforced concrete highway bridge class. An analytical approach was adopted to develop the fragility curves based on numerical simulation. The R, µ and fundamental period T have been used to characterize different bridge configurations. The total, direct, and indirect effects of the variables as having significant effect on fragility curve parameters were identified.

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  • Alwin D.F. and Hauser R.M. 1975. The decomposition of effects in path analysis. American sociological review pp. 37-47.

  • Baker J. W. and Allin Cornell C. 2005. A vector-valued ground motion intensity measure consisting of spectral acceleration and epsilon. Earthquake Engineering & Structural Dynamics 34(10) pp. 1193-1217.

  • Bentler P. M. 1990. Comparative fit indexes in structural models. Psychological bulletin 107(2) 238.

  • Berry M. Parrish M. and Eberhard M. 2004. PEER Structural Performance Database User’s Manual (Version 1.0). University of California Berkeley.

  • Browne M. W. and Cudeck R. 1993. Alternative ways of assessing model fit. Sage focus editions 154 pp. 136-136.

  • Celik OC. and Ellingwood BR. 2010. Seismic fragilities for non-ductile reinforced concrete frames–Role of aleatoric and epistemic uncertainties. Structural Safety 32 pp. 1-12

  • Choi E. DesRoches R. and Nielson B. 2004. Seismic fragility of typical bridges in moderate seismic zones. Engineering Structures 26 pp. 187-199.

  • Cornell CA. and Krawinkler H. 2000. Progress and challenges in seismic performance assessment. PEER center news 3 pp. 1-3.

  • DesRoches R. Padgett J. Ramanathan K. and Dukes J. 2012. Feasibility studies for improving Caltrans bridge fragility relationships No. CA12-1775.

  • Jeong S-H. and Elnashai AS. 2007. Probabilistic fragility analysis parameterized by fundamental response quantities. Engineering Structures 29 pp. 1238-1251.

  • Kennedy R. P. and Ravindra M. K. 1984. Seismic fragilities for nuclear power plant risk studies. Nuclear Engineering and Design 79(1) pp. 47-68.

  • Kircher C. A. Whitman R. V. and Holmes W. T. 2006. HAZUS earthquake loss estimation methods. Natural Hazards Review 7(2) pp. 45-59.

  • Land K. C. 1969. Principles of path analysis. Sociological methodology 1: 3-37.

  • Luco N. and Cornell CA. 2007. Structure-specific scalar intensity measures for near-source and ordinary earthquake ground motions. Earthquake Spectra 23 pp. 357-392.

  • Mackie K. and Stojadinovic B. 2004. Improving probabilistic seismic demand models through refined intensity measures. In: Proc. 13th World Conf. Earthquake Eng. Int. Assoc. for Earthquake Eng. Japan August 2004.

  • Mackie KR. and Stojadinovic B. 2005. Fragility basis for California highway overpass bridge seismic decision making. Pacific Earthquake Engineering Research Center College of Engineering University of California Berkeley.

  • Kadysiewski S. and Mosalam K.M. 2009. Modeling of unreinforced masonry infill walls considering in-plane and outof-plane interaction (Vol. 70). Berkeley California USA: Pacific Earthquake Engineering Research Center.

  • McKay MD. Beckman RJ. and Conover WJ. 2000. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42 pp. 55-61.

  • Megally S. Veletzos MJ. Burnell K. Restrepo JI. and Seible F. 2009. Seismic performance of precast concrete segmental bridges: Summary of experimental research on segment-to-segment joints. PCI journal 54(2).

  • Nielson B. G. 2005. Analytical fragility curves for highway bridges in moderate seismic zones. PhD Thesis. Georgia Institute of Technology

  • Padgett JE. Nielson BG. and DesRoches R. 2008. Selection of optimal intensity measures in probabilistic seismic demand models of highway bridge portfolios. Earthquake Engineering & Structural Dynamics 37 pp. 711-725.

  • Pedhazur E. J. and Pedhazur Schmelkin L. 1991. Exploratory factor analysis. Measurement design and analysis: An integrated approach pp. 590-630.

  • Priestley MN Seible F. and Calvi GM. 1996. Seismic design and retrofit of bridges. John Wiley & Sons.

  • Ramanathan K. DesRoches R. and Padgett J. 2010. Analytical fragility curves for multispan continuous steel girder bridges in moderate seismic zones. Transportation Research Record: Journal of the Transportation Research Board pp. 173-182.

  • Ramanathan K. Padgett JE. and DesRoches R. 2015. Temporal evolution of seismic fragility curves for concrete box-girder bridges in California. Engineering Structures 97 pp. 29-46.

  • Scharge L. 1981. Anchoring of bearings by friction joint sealing and bearing systems for concrete structures. In: World congress on joints and bearings (Vol. 1).

  • Shamsabadi A. Yan L. 2008. Closed-form force-displacement backbone curves for bridge abutment-backfill systems. In: Geotechnical Earthquake. Engineering and Soil Dynamics IV: pp. 1-10.

  • Shome N. 1999. Probabilistic seismic demand analysis of nonlinear structures. Stanford University.

  • Singhal A. and Kiremidjian A. S. 1996. Method for probabilistic evaluation of seismic structural damage. Journal of Structural Engineering 122(12) pp. 1459-1467.

  • Straub D. and Der Kiureghian A. 2008. Improved seismic fragility modeling from empirical data. Structural safety 30(4): pp. 320-336.

  • Wright S. 1921. Correlation and causation. Journal of agricultural research 20(7) pp. 557-585.

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