Abstract

With the development of new materials and advanced structural analysis, alongside increasing aesthetic requirements, recent years have witnessed a trend toward longer, taller, and lighter footbridges. Different from vehicular bridges, footbridges carry relatively small service loads and are more susceptible to vibrations, due to their lower stiffness, damping, and modal mass. More often than not, vibration serviceability limit state governs the design of footbridges. Providing an accurate evaluation of vibration serviceability performance of existing bridges requires techniques that can include modeling and measurement uncertainties. In this paper, a population-based method called error-domain model falsification (EDMF) is used to assess the vibration serviceability for two pedestrian bridges: Fort Siloso Skywalk located in Singapore and the Dowling Hall Footbridge located at Tufts University in the United States. The unknown properties of the footbridges are identified using the ambient vibration data measured on site. This method is also compared with two other data-interpretation methodologies, that is, residual minimization and traditional Bayesian model updating. The findings show that, through explicitly accounting for measurement and modeling uncertainties, EDMF can provide more accurate identification and prediction results for vibration serviceability assessment of pedestrian bridges.

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Acknowledgments

This research was conducted at the Future Cities Laboratory at the Singapore–ETH Center (SEC). The SEC was established as a collaboration between ETH Zurich and the National Research Foundation (NRF) Singapore (FI 370074016) under the NRF's Campus for Research Excellence and Technological Enterprise (CREATE) program. The authors gratefully acknowledge the support of Prof. Babak Moaveni for generously providing the case study of Dowling Hall Footbridge, and Sentosa Development Corporation, CPG Consultants Pte. Ltd. for the case study of Fort Siloso Skywalk. The authors also thank Prof. Siu-Kui Au for his help with Bayesian operational modal analysis.

References

Araujo, I. G., E. Maldonado, and G. C. Cho. 2011. “Ambient vibration testing and updating of the finite element model of a simply supported beam bridge.” Front. Archit. Civ. Eng. China 5 (3): 344–354. https://doi.org/10.1007/s11709-011-0124-8.
Au, S. K. 2012a. “Fast Bayesian ambient modal identification in the frequency domain, Part I: Posterior most probable value.” Mech. Syst. Sig. Process. 26: 60–75. https://doi.org/10.1016/j.ymssp.2011.06.017.
Au, S. K. 2012b. “Fast Bayesian ambient modal identification in the frequency domain, Part II: Posterior uncertainty.” Mech. Syst. Sig. Process. 26: 76–90. https://doi.org/10.1016/j.ymssp.2011.06.019.
Au, S. K. 2017. Operational modal analysis: Modeling, Bayesian inference, uncertainty laws. Berlin: Springer.
Beck, J. L., and L. S. Katafygiotis. 1998. “Updating models and their uncertainties. I: Bayesian statistical framework.” J. Eng. Mech. 124 (4): 455–461. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:4(455).
Bertola, N., M. Papadopoulou, D. Vernay, and I. F. C. Smith. 2017. “Optimal multi-type sensor placement for structural identification by static-load testing.” Sensors 17 (12): 2904. https://doi.org/10.3390/s17122904.
Brownjohn, J. M. W., and A. Darby. 2018. “Human factors simulation for motion and servicebility in the built environment.” In Proc., 13th UK Conf. on Wind Engineering, 1–4. Leeds, UK: Np.
Brownjohn, J. M. W., A. De Stefano, Y.-L. Xu, H. Wenzel, and A. E. Aktan. 2011. “Vibration-based monitoring of civil infrastructure: Challenges and successes.” J. Civ. Struct. Health Monit. 1 (3–4): 79–95. https://doi.org/10.1007/s13349-011-0009-5.
Brownjohn, J. M. W., P. Moyo, P. Omenzetter, and Y. Lu. 2003. “Assessment of highway bridge upgrading by dynamic testing and finite-element model updating.” J. Bridge Eng. 8 (3): 162–172. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:3(162).
Byfield, M., and S. Paramasivam. 2012. “Murrah building collapse: Reassessment of the transfer girder.” J. Perform. Constr. Facil 26 (4): 371–376. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000227.
Cao, W.-J., C. G. Koh, and I. F. C. Smith. 2019a. “Enhancing static-load-test identification of bridges using dynamic data.” Eng. Struct. 186: 410–420. https://doi.org/10.1016/j.engstruct.2019.02.041.
Cao, W.-J., S. Zhang, N. J. Bertola, I. F. C. Smith, and C. G. Koh. 2019b. “Time series data interpretation for “wheel-flat” identification including uncertainties.” Struct. Health Monit. https://doi.org/10.1177/1475921719887117.
Catbas, F. N., and T. Kijewski-Correa. 2013. “Structural identification of constructed systems: Collective effort toward an integrated approach that reduces barriers to adoption.” J. Struct. Eng. 139 (10): 1648–1652. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000682.
CEN (European Committee for Standardization). 2005. Eurocode—Basis of structural design. Application for bridges. EN 1990:2002/A1:2005. Brussels, Belgium: CEN.
Cheung, S. H., and J. L. Beck. 2009. “Bayesian model updating using hybrid Monte Carlo simulation with application to structural dynamic models with many uncertain parameters.” J. Eng. Mech. 135 (4): 243–255. https://doi.org/10.1061/(ASCE)0733-9399(2009)135:4(243).
Cheung, S. H., and J. L. Beck. 2010. “Calculation of posterior probabilities for Bayesian model class assessment and averaging from posterior samples based on dynamic system data.” Comput.-Aided Civ. Infrastruct. Eng. 25 (5): 304–321. https://doi.org/10.1111/j.1467-8667.2009.00642.x.
Chib, S., and E. Greenberg. 1995. “Understanding the metropolis-hastings algorithm.” Am. Stat. 49 (4): 327–335.
Exler, O., and K. Schittkowski. 2007. “A trust region SQP algorithm for mixed-integer nonlinear programming.” Opt. Lett. 1 (3): 269–280. https://doi.org/10.1007/s11590-006-0026-1.
Feldmann, M., et al. 2010. Human induced vibraitons of steel structures (HiVoSS). Luxembourg: Office for Official Publications of the European Communities.
Friswell, M. I., J. E. T. Penny, and S. D. Garvey. 1998. “A combined genetic and eigensensitivity algorithm for the location of damage in structures.” Comput. Struct. 69 (5): 547–556. https://doi.org/10.1016/S0045-7949(98)00125-4.
Goller, B., J. L. Beck, and G. I. Schuëller. 2012. “Evidence-based identification of weighting factors in Bayesian model updating using modal data.” J. Eng. Mech. 138 (5): 430–440. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000351.
Goulet, J. A. 2012. Probabilistic model falsification for infrastructure diagnosis. EPFL Thesis No 5417. Lausanne, Switzerland: Swiss Federal Institute of Technology (EPFL).
Goulet, J.-A., P. Kripakaran, and I. F. C. Smith. 2010. “Multimodel structural performance monitoring.” J. Struct. Eng. 136 (10): 1309–1318. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000232.
Goulet, J.-A., C. Michel, and I. F. C. Smith. 2013. “Hybrid probabilities and error-domain structural identification using ambient vibration monitoring.” Mech. Syst. Sig. Process. 37 (1–2): 199–212. https://doi.org/10.1016/j.ymssp.2012.05.017.
Goulet, J.-A., and I. F. C. Smith. 2013. “Structural identification with systematic errors and unknown uncertainty dependencies.” Comput. Struct. 128: 251–258. https://doi.org/10.1016/j.compstruc.2013.07.009.
Goulet, J.-A., M. Texier, C. Michel, I. F. C. Smith, and L. Chouinard. 2014. “Quantifying the effects of modeling simplifications for structural identification of bridges.” J. Bridge Eng. 19 (1): 59–71. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000510.
Jaynes, E. T. 2003. Probability theory: The logic of science. Cambridge, UK: Cambridge Univ. Press.
Katafygiotis, L. S., and J. L. Beck. 1998. “Updating models and their uncertainties. II: Model identifiability.” J. Eng. Mech. 124 (4): 463–467. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:4(463).
Kim, G. H., and Y. S. Park. 2004. “An improved updating parameter selection method and finite element model update using multiobjective optimisation technique.” Mech. Syst. Sig. Process. 18 (1): 59–78. https://doi.org/10.1016/S0888-3270(03)00042-6.
Lam, H. F., J. Yang, and S. K. Au. 2015. “Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced Markov chain Monte Carlo simulation algorithm.” Eng. Struct. 102: 144–155. https://doi.org/10.1016/j.engstruct.2015.08.005.
Lee, H.-H. 2018. Finite element simulations with ANSYS workbench 19. Mission, KS: SDC Publications.
Liu, W.-S., and S. H. Cheung. 2020. “Decoupled reliability-based geotechnical design of deep excavations of soil with spatial variability.” Appl. Math. Modell. 85: 46–59. https://doi.org/10.1016/j.apm.2020.04.001.
Moaveni, B., and I. Behmanesh. 2012. “Effects of changing ambient temperature on finite element model updating of the Dowling Hall Footbridge.” Eng. Struct. 43: 58–68. https://doi.org/10.1016/j.engstruct.2012.05.009.
Moser, G., S. G. Paal, and I. F. C. Smith. 2018. “Leak detection of water supply networks using error-domain model falsification.” J. Comput. Civil Eng. 32 (2): 04017077. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000729.
Moser, P., and B. Moaveni. 2013. “Design and deployment of a continuous monitoring system for the Dowling Hall footbridge.” Exp. Tech. 37 (1): 15–26. https://doi.org/10.1111/j.1747-1567.2011.00751.x.
Mottershead, J. E., M. Link, and M. I. Friswell. 2011. “The sensitivity method in finite element model updating: A tutorial.” Mech. Syst. Sig. Process. 25 (7): 2275–2296. https://doi.org/10.1016/j.ymssp.2010.10.012.
Murray, T. M., D. E. Allen, and E. E. Ungar. 1997. Steel design guide series 11: Floor vibrations due to human activity. Chicago, IL: American Institute of Steel Construction.
Nguyen, N. T., Z. M. Sbartaï, J. F. Lataste, D. Breysse, and F. Bos. 2013. “Assessing the spatial variability of concrete structures using NDT techniques—Laboratory tests and case study.” Constr. Build. Mater. 49: 240–250. https://doi.org/10.1016/j.conbuildmat.2013.08.011.
Papadopoulou, M., B. Raphael, I. F. C. Smith, and C. Sekhar. 2016. “Optimal sensor placement for time-dependent systems: Application to wind studies around buildings.” J. Comput. Civil Eng. 30 (2): 04015024. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000497.
Pasquier, R., J.-A. Goulet, C. Acevedo, and I. F. C. Smith. 2014. “Improving fatigue evaluations of structures using in-service behavior measurement data.” J. Bridge Eng. 19 (11): 04014045. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000619.
Pasquier, R., and I. F. C. Smith. 2016. “Iterative structural identification framework for evaluation of existing structures.” Eng. Struct. 106: 179–194. https://doi.org/10.1016/j.engstruct.2015.09.039.
Pasquier, R. D., L. Angelo, J.-A. Goulet, C. Acevedo, A. Nussbaumer, and I. F. C. Smith. 2016. “Measurement, data interpretation, and uncertainty propagation for fatigue assessments of structures.” J. Bridge Eng. 21 (5): 04015087. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000861.
Rainieri, C., and G. Fabbrocino. 2014. Operational modal analysis of civil engineering structures. New York: Springer.
Ren, W. X., and X. L. Peng. 2005. “Baseline finite element modeling of a large span cable-stayed bridge through field ambient vibration tests.” Comput. Struct. 83 (8–9): 536–550. https://doi.org/10.1016/j.compstruc.2004.11.013.
Yin, T., H. F. Lam, and H. M. Chow. 2010. “A Bayesian probabilistic approach for crack characterization in plate structures.” Comput.-Aided Civ. Infrastruct. Eng. 25 (5): 375–386. https://doi.org/10.1111/j.1467-8667.2009.00647.x.
Yuen, K.-V., S. K. Au, and J. L. Beck. 2004. “Two-stage structural health monitoring approach for phase I benchmark studies.” J. Eng. Mech. 130 (1): 16–33. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(16).
Yuen, K.-V., J. L. Beck, and L. S. Katafygiotis. 2006. “Efficient model updating and health monitoring methodology using incomplete modal data without mode matching.” Struct. Control Health Monit. 13 (1): 91–107. https://doi.org/10.1002/stc.144.
Zheng, W., and Y. Yu. 2013. “Bayesian probabilistic framework for damage identification of steel truss bridges under joint uncertainties.” Adv. Civ. Eng. 2013: 1–13. https://doi.org/10.1155/2013/307171.

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Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 26Issue 3March 2021

History

Received: Dec 12, 2019
Accepted: Sep 18, 2020
Published online: Dec 17, 2020
Published in print: Mar 1, 2021
Discussion open until: May 17, 2021

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Researcher, ETH Zurich, Future Cities Laboratory, Singapore-ETH Centre, # 06-01, CREATE Tower, 1 Create Way, 138602 Singapore (corresponding author). ORCID: https://orcid.org/0000-0002-4559-9809. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, National Univ. of Singapore, 1 Engineering Drive 2, 117576 Singapore. ORCID: https://orcid.org/0000-0002-4779-2207. Email: [email protected]
I. F. C. Smith, Ph.D., F.ASCE [email protected]
Professor, Applied Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), Swiss Federal Institute of Technology (EPFL), GC G1 507, Station 18, CH-1015 Lausanne, Switzerland. Email: [email protected]

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