Investigation of Intraclass Correlation of Seismic Capacity for RC Bridge Piers Based on Hierarchical Model
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 3
Abstract
The framework for performance-based seismic design and assessment of bridges grapples with the pressing challenge of precisely estimating the seismic capacities correlation amongst bridge piers. To address this issue, a Bayesian semiparametric hierarchical model is proposed in this study to characterize such correlation. This model was applied to a database populated with multiple-column tests conducted by distinct research cohorts. Given that each group performed tests under analogous conditions, the model could be operationalized on the database to derive intraclass correlation coefficients that reflect the statistical correlation among piers tested by individual research groups. It is postulated that these coefficients also typify the capacity correlation across multiple bridge piers within a bridge system. After a thorough examination of the data set, particularly focusing on the nature of missing values, an appropriate multiple imputation technique was selected to address the missing data, aiming to approximate the most accurate intraclass correlation. The analysis revealed that, among the various damage limit states, the correlation coefficients spanned between 0.386 and 0.883. This suggests that the seismic capacity of bridge piers is influenced not only by design parameters but also by the experimental group. Utilizing independent or fully correlated relationships between capacities, rather than true correlation coefficients, can lead to significant deviations in the fragility curve, which increase with the number of bridge piers. Such observations accentuate the necessity of integrating authentic pier capacity correlations in the bridge system fragility analysis.
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Data Availability Statement
All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors gratefully acknowledge the funding from the Natural Science Foundation of Fujian Province (Grant No. 2020J01478) and the research support from the Open Fund Project of the Sustainable and Innovative Bridge Engineering Research Center of Fujian Province University, Fuzhou University (SIBERC2022005).
References
Akaike, H. 1998. Information theory and an extension of the maximum likelihood principle. New York: Springer.
Baker, J. W. 2008. “Introducing correlation among fragility functions for multiple components.” In Proc., 14th World Conf. on Earthquake Engineering, 12–17. Beijing: Chinese Association of Earthquake Engineering, International Association for Earthquake Engineering.
Baraldi, A. N., and C. K. Enders. 2010. “An introduction to modern missing data analyses.” J. School Psychol. 48 (1): 5–37. https://doi.org/10.1016/j.jsp.2009.10.001.
Berry, M., and M. Eberhard. 2003. Performance models for flexural damage in reinforced concrete columns. Berkeley, CA: Pacific Earthquake Engineering Research Center, Univ. of California.
Berry, M., M. Parrish, and M. Eberhard. 2004. Peer structural performance database user’s manual (version 1.0). Berkeley, CA: Univ. of California, Berkeley.
Buckle, I. G., I. Friedland, J. Mander, G. Martin, R. Nutt, and M. Power. 2006. Seismic retrofitting manual for highway structures. Part 1, bridges. McLean, VA: Federal Highway Administration.
Bujang, M. A., and N. Baharum. 2017. “A simplified guide to determination of sample size requirements for estimating the value of intraclass correlation coefficient: A review.” Arch. Orofacial Sci. 12 (1): 1–11.
Burton, H. V., and G. G. Deierlein. 2018. “Integrating visual damage simulation, virtual inspection, and collapse capacity to evaluate post-earthquake structural safety of buildings.” Earthquake Eng. Struct. Dyn. 47 (2): 294–310. https://doi.org/10.1002/eqe.2951.
Chen, G., P. A. Taylor, S. P. Haller, K. Kircanski, J. Stoddard, D. S. Pine, E. Leibenluft, M. A. Brotman, and R. W. Cox. 2018. “Intraclass correlation: Improved modeling approaches and applications for neuroimaging.” Hum. Brain Mapp. 39 (3): 1187–1206. https://doi.org/10.1002/hbm.23909.
Chen, L., L. Chen, Z. Zheng, Z. Guo, and P. Gardoni. 2023. “Probabilistic seismic capacity model of pier columns: A semiparametric regression approach.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 9 (3): 04023021. https://doi.org/10.1061/AJRUA6.RUENG-1053.
Chouldechova, A., and T. Hastie. 2015. “Generalized additive model selection.” Preprint, submitted June 11, 2015. http://arxiv.org/abs/1506.03850.
Donner, A. 1986. “A review of inference procedures for the intraclass correlation coefficient in the one-way random effects model.” Int. Stat. Rev. 54 (1): 67–82.
Fisher, R. A. 1925. Statistical methods for research workers. New York: Springer.
Gokkaya, B., J. Baker, and G. Deierlein. 2017. “Estimation and impacts of model parameter correlation for seismic performance assessment of reinforced concrete structures.” Struct. Saf. 69 (Mar): 68–78. https://doi.org/10.1016/j.strusafe.2017.07.005.
Heresi, P., and E. Miranda. 2022. “Structure-to-structure damage correlation for scenario-based regional seismic risk assessment.” Struct. Saf. 95 (Dec): 102155. https://doi.org/10.1016/j.strusafe.2021.102155.
Jayaram, N., N. Shome, and M. Rahnama. 2012. “Development of earthquake vulnerability functions for tall buildings.” Earthquake Eng. Struct. Dyn. 41 (11): 1495–1514. https://doi.org/10.1002/eqe.2231.
LeBreton, J. M., and J. L. Senter. 2008. “Answers to 20 questions about interrater reliability and interrater agreement.” Organ. Res. Methods 11 (4): 815–852. https://doi.org/10.1177/1094428106296642.
Little, R. J., and D. B. Rubin. 2019. Vol. 793 of Statistical analysis with missing data. New York: Wiley.
Liu, H., and H. Motoda. 2012. Vol. 454 of Feature selection for knowledge discovery and data mining. New York: Springer.
Nielson, B. G. 2005. “Analytical fragility curves for highway bridges in moderate seismic zones.” Ph.D. thesis, School of Civil and Environmental Engineering, Georgia Institute of Technology.
Nielson, B. G., and R. DesRoches. 2007. “Analytical seismic fragility curves for typical bridges in the central and southeastern United States.” Earthquake Spectra 23 (3): 615–633. https://doi.org/10.1193/1.2756815.
Rasmussen, C. E., and C. K. I. Williams. 2005. Gaussian processes for machine learning. Cambridge, UK: MIT Press.
Rubin, D. B. 2004. Vol. 81 of Multiple imputation for nonresponse in surveys. New York: Wiley.
Schafer, J. L. 1997. Analysis of incomplete multivariate data. Boca Raton, FL: CRC Press.
Schwarz, G. 1978. “Estimating the dimension of a model.” Ann. Stat. 6 (2): 461–464. https://doi.org/10.1214/aos/1176344136.
Shieh, G. 2016. “Choosing the best index for the average score intraclass correlation coefficient.” Behav. Res. Methods 48 (Nov): 994–1003. https://doi.org/10.3758/s13428-015-0623-y.
Vamvatsikos, D. 2014. “Seismic performance uncertainty estimation via IDA with progressive accelerogram-wise Latin hypercube sampling.” J. Struct. Eng. 140 (8): A4014015. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001030.
Van Buuren, S. 2018. Flexible imputation of missing data. 2nd ed. Boca Raton, FL: CRC Press.
Van Buuren, S., and K. Groothuis-Oudshoorn. 2011. “Mice: Multivariate imputation by chained equations in R.” J. Stat. Software 45 (Dec): 1–67.
White, I. R., P. Royston, and A. M. Wood. 2011. “Multiple imputation using chained equations: Issues and guidance for practice.” Stat. Med. 30 (4): 377–399. https://doi.org/10.1002/sim.4067.
Zhang, J., and Y. Huo. 2009. “Evaluating effectiveness and optimum design of isolation devices for highway bridges using the fragility function method.” Eng. Struct. 31 (8): 1648–1660. https://doi.org/10.1016/j.engstruct.2009.02.017.
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© 2024 American Society of Civil Engineers.
History
Received: Oct 9, 2023
Accepted: Feb 28, 2024
Published online: May 24, 2024
Published in print: Sep 1, 2024
Discussion open until: Oct 24, 2024
ASCE Technical Topics:
- Bridge design
- Bridge engineering
- Bridge tests
- Bridges
- Correlation
- Design (by type)
- Earthquake engineering
- Engineering fundamentals
- Field tests
- Geotechnical engineering
- Hydraulic engineering
- Hydraulic structures
- Mathematics
- Piers
- Ports and harbors
- Seismic design
- Seismic tests
- Statistics
- Structural engineering
- Tests (by type)
- Water and water resources
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