Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Structural identification of Humber Bridge for performance prognosis

  • Rahbari, R. (Department of Civil Engineering, University of Sheffield) ;
  • Niu, J. (School of Civil Engineering, Southeast University) ;
  • Brownjohn, J.M.W. (College of Engineering, Mathematics and Physical Science, University of Exeter) ;
  • Koo, K.Y. (College of Engineering, Mathematics and Physical Science, University of Exeter)
  • Received : 2014.11.20
  • Accepted : 2015.02.25
  • Published : 2015.03.25
⟨ Previous Next ⟩

Abstract

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

Keywords

References

  1. Abdel-Ghaffar, A.M. and Scanlan, R.H. (1985), "Ambient vibration studies of Golden Gate bridge: 1. Suspended structure, and 2. Pier tower structure", J. Eng. Mech. - ASCE, 111(4), 463-482. https://doi.org/10.1061/(ASCE)0733-9399(1985)111:4(463)
  2. Ashkenazi, V. and Roberts, G.W. (1997), "Experimental monitoring of the Humber Bridge using GPS". ICE Proceedings Civil Eng., 120, 177-182. https://doi.org/10.1680/icien.1997.29810
  3. Bathe, K.J., Wilson, E.L. and Petersen, F.E. (1974), SAPIV a structural analysis program for static and dynamic response of linear structures.
  4. Bojovi, A. Velov, N. and Toljatija, P. (2013), "Rehabilitation of the Gazelle road bridge in Belgrade", Proceedings of the 8th International Conference "Bridges in Danube Basin".
  5. Brancaleoni, F. and Diana, G. (1993), "The aerodynamic design of the Messina Straits Bridge", J. Wind Eng. Ind. Aerod., 48(2-3), 395-409. https://doi.org/10.1016/0167-6105(93)90148-H
  6. Brown, T.A. and Milne, R.D. (1985), "Strategies for the verification of a finite element model", In IMAC III (pp. 1031-1039). Orlando, Florida.
  7. Brownjohn, J.M.W., Dumanoglu, A.A., Taylor, C.A. and Severn, R.T. (1987), "Ambient vibration measurements of the Humber Suspension Bridge and comparison with calculated characteristics", Proceedings Institution of Civil Engineers Part 2, 83, 561-600. https://doi.org/10.1680/iicep.1987.335
  8. Brownjohn, J.M.W. ,Maglhaes, F., Caetano, E. and Cunha, A. (2010), "Ambient vibration re-testing and operational modal analysis of the Humber Bridge", Eng. Struct., 32(8), 2003-2018. https://doi.org/10.1016/j.engstruct.2010.02.034
  9. Brownjohn, J.M.W., Bocciolone, M., Curami, A., Falco, M. and Zasso, A. (1994), "Humber bridge full-scale measurements campaigns 1990-1991", J. Wind Eng. Ind. Aerod., 52, 185-218. https://doi.org/10.1016/0167-6105(94)90047-7
  10. Brownjohn, J.M.W., Koo, K.Y., Scullion, A. and List, D. (2015), "Operational deformations in long span bridges", J. Struct. Infrastruct. E., 11(4), 556-574 https://doi.org/10.1080/15732479.2014.951857
  11. Catbas, F.N., Correa-Kijewski, T. and Aktan, A.E. (2013), Structural Identification of Constructed Systems. Approaches, Methods and Technologies for Effective Practice of St-Id., ASCE.
  12. Cross, E.J. Koo, K.Y., Brownjohn, J.M.W. and Worden, K. (2013), "Long-term monitoring and data analysis of the Tamar Bridge", Mech. Syst. Signal Pr., 35(1-2), 16-34. https://doi.org/10.1016/j.ymssp.2012.08.026
  13. Diana, G., Cheli, F., Zasso, A., Collina, A. and Brownjohn, J.M.W. (1992), "Suspension bridge parameter identification in full-scale test", J. Wind Eng. Ind. Aerod., 41(1-3), 165-176. https://doi.org/10.1016/0167-6105(92)90404-X
  14. Dumanoglu, A.A. and Severn, R.T. (1987), "Seismic response of modern suspension bridges to asynchronous vertical ground motion", Proceedings ICE Part 2, 83, 701-730.
  15. Farrar, C.R. and Lieven, N.A.J. (2007), "Damage prognosis: the future of structural health monitoring", Philos. T. R. Soc. A., 365(1851), 623-632. https://doi.org/10.1098/rsta.2006.1927
  16. Friswell, M.I. and Mottershead, J.E. (1995), Finite element model updating in structural dynamics, Springer.
  17. Fujino, Y. and Siringoringo, D.M. (2013), "Lessons learned from structural monitoring of long-span bridges and a tall base-isolated building", Proceedings of the SHMII-6. Hong Kong.
  18. Hornby, S.R., Collins, J.H., Hill, P.G. and Cooper, J.R. (2012), "Humber bridge A-frame refurbishment / replacement", Proceedings of the 6th International Conference on Bridge Maintenance, Safety and Management (IABMAS). Stresa, Italy: Taylor & Francis Group, London.
  19. Karuna, R. (2002), Structural Modelling of Suspension Bridges with Particular Reference to the Humber Bridge, PhD Thesis, Brunel University.
  20. Koo, K.Y., de Battista, N. and Brownjohn, J.M.W. (2011), "SHM data management system using MySQL databse with MATLAB and Web interfaces", Proceedings of the SHMII-5. Cancun, Mexico,
  21. Kromanis, R. and Kripakaran, P. (2014), "Predicting thermal response of bridges using regression models derived from measurement histories", Comput. Struct., 136, 64-77. https://doi.org/10.1016/j.compstruc.2014.01.026
  22. Kumarasena, T., Scanlan, R.H. and Morris, G.R. (1989), "Deer Isle bridge: Efficacy of stiffening systems", J. Struct. Eng., 115(9), 2297-2312. https://doi.org/10.1061/(ASCE)0733-9445(1989)115:9(2297)
  23. Larsen, A., Esdahl, S., Andersen, J.E. and Vejrum, T. (2000), "Storebaelt suspension bridge - vortex shedding excitation and mitigation by guide vanes", J. Wind Eng. Ind. Aerod., 88(2-3), 283-296. https://doi.org/10.1016/S0167-6105(00)00054-4
  24. Littler, J.D. (1992), "Ambient vibration tests on long span suspension bridges", J, Wind Eng. Ind. Aerod., 41-44, 1359-1370.
  25. Littler, J.D. and Woods, A.R. (1989), Ambient vibration tests on the Humber Bridge July 1988, BRE N75/89.
  26. Nickitopoulou, A., Protopsalti, K. and Stiros, S.C. (2006), "Monitoring dynamic and quasi-static deformations of large flexible engineering structures with GPS: Accuracy, limitations and promises", Eng. Struct., 28, 1471-1482. https://doi.org/10.1016/j.engstruct.2006.02.001
  27. Stephen, G.A., Brownjohn, J.M.W. and Taylor, C.A. (1993), "Measurements of static and dynamic displacement from visual monitoring of the Humber Bridge", Eng. Struct., 15(3), 197-208. https://doi.org/10.1016/0141-0296(93)90054-8
  28. Walshe, D.E. and Cowdrey, C.F. (1972), A further investigation for the proposed Humber suspension bridge, Transport Research Laboratory.
  29. Westgate, R.J., Koo, K.Y. and Brownjohn, J.M.W. (2015), "Effect of vehicular loading on suspension bridge dynamic properties", J. Struct. Infrastruct. E., 11(2), 129-144. https://doi.org/10.1080/15732479.2013.850731
  30. Westgate, R., Koo, K.Y. and Brownjohn, J.M.W. (2014), "Effect of solar radiation on suspension bridge performance", J. Bridge Eng. - ASCE (online), 10.1061/(ASCE)BE.1943-5592.0000668.
  31. Worden, K. and Manson, G. (2007), "The application of machine learning to structural health monitoring", Philos. T. R. Soc. A., 365(1851), 515-537. https://doi.org/10.1098/rsta.2006.1938

Cited by

  1. Vision-Based Bridge Deformation Monitoring vol.3, 2017, https://doi.org/10.3389/fbuil.2017.00023
  2. Gaussian Process Time-Series Models for Structures under Operational Variability vol.3, 2017, https://doi.org/10.3389/fbuil.2017.00069
  3. Canonical correlation analysis based fault diagnosis method for structural monitoring sensor networks vol.17, pp.6, 2016, https://doi.org/10.12989/sss.2016.17.6.1031
  4. Fatigue assessment of an existing steel bridge by finite element modelling and field measurements vol.843, 2017, https://doi.org/10.1088/1742-6596/843/1/012038
  5. Long-span bridges: Enhanced data fusion of GPS displacement and deck accelerations vol.147, 2017, https://doi.org/10.1016/j.engstruct.2017.06.018
  6. Moving Load Identification with Long Gauge Fiber Optic Strain Sensing vol.16, pp.3, 2015, https://doi.org/10.7250/bjrbe.2021-16.535