Computers and Concrete

  • 제15권5호
  • /
  • Pages.771-794
  • /
  • 2015
  • /
  • 1598-8198(pISSN)
  • /
  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Selection of measurement sets in static structural identification of bridges using observability trees

  • Lozano-Galant, Jose Antonio (Department of Civil Engineering, University of Castilla-La Mancha) ;
  • Nogal, Maria (Department of Civil, Structural and Environmental Engineering, Trinity College) ;
  • Turmo, Jose (Department of Construction Engineering, Universitat Politecnica de Catalunya BarcelonaTECH) ;
  • Castillo, Enrique (Department of Applied Mathematics and Computational Sciences, University of Cantabria)
  • 투고 : 2014.08.27
  • 심사 : 2015.01.16
  • 발행 : 2015.05.25
⟨ 이전 논문 다음 논문 ⟩

초록

This paper proposes an innovative method for selection of measurement sets in static parameter identification of concrete or steel bridges. This method is proved as a systematic tool to address the first steps of Structural System Identification procedures by observability techniques: the selection of adequate measurement sets. The observability trees show graphically how the unknown estimates are successively calculated throughout the recursive process of the observability analysis. The observability trees can be proved as an intuitive and powerful tool for measurement selection in beam bridges that can also be applied in complex structures, such as cable-stayed bridges. Nevertheless, in these structures, the strong link among structural parameters advises to assume a set of simplifications to increase the tree intuitiveness. In addition, a set of guidelines are provided to facilitate the representation of the observability trees in this kind of structures. These guidelines are applied in bridges of growing complexity to explain how the characteristics of the geometry of the structure (e.g. deck inclination, type of pylon-deck connection, or the existence of stay cables) affect the observability trees. The importance of the observability trees is justified by a statistical analysis of measurement sets randomly selected. This study shows that, in the analyzed structure, the probability of selecting an adequate measurement set with a minimum number of measurements at random is practically negligible. Furthermore, even bigger measurement sets might not provide adequate SSI of the unknown parameters. Finally, to show the potential of the observability trees, a large-scale concrete cable-stayed bridge is also analyzed. The comparison with the number of measurements required in the literature shows again the advantages of using the proposed method.

키워드

과제정보

연구 과제 주관 기관 : Ministerio de Economia y Competitividad (Spain)

참고문헌

  1. Abdo, M.A. (2012), "Parametric study of using only static response in structural damage detection". Eng. Struct., 34, 124-131. https://doi.org/10.1016/j.engstruct.2011.09.027
  2. Aboul-Ella, F. (1990), "New iterative analysis of cable-stayed structures", Comput. Struct., 40(3), 549-554. https://doi.org/10.1016/0045-7949(91)90225-B
  3. Adeli, H. and Jiang, X. (2006), "Dynamic fuzzy wavelet neural network model for structural system identification", J. Struct. Eng., 132(1), 102-111. https://doi.org/10.1061/(ASCE)0733-9445(2006)132:1(102)
  4. Arslan, M.E. and Durmus, A. (2013), "Construction stage effect on the dynamic characteristics of RC frame using operational modal analysis", Comput. Concr., 12(1), 79-90. https://doi.org/10.12989/cac.2013.12.1.079
  5. ASCE (2011), Structural identification (st-id) of constructed facilities: approaches, methods and technologies for effective practice of st-id. Technical report, ASCE SEI Committee on Structural Identification of Constructed Systems, American Society of Civil Engineers (ASCE).
  6. Castillo, E., Lozano-Galant, J.A., Nogal, M. and Turmo, J. (2014), "New tool to help decision making in civil engineering", J. Civil Engineering and Management., DOI: 10.3846/13923730.2014.893904.
  7. Erdogan, Y.S. and Bakir, P.G. (2013), "Evaluation of the different genetic algorithm parameters and operators for the finite element model updating problem", Comput. Concr., 11(6), 541-569. https://doi.org/10.12989/cac.2013.11.6.541
  8. Joshua, L. and Varghese, K. (2013), "Selection of Accelerometer location on Brick Layers Using Decision Trees", Comp.-Aided Civ. Inf., 28(5), 372-388. https://doi.org/10.1111/mice.12002
  9. Lakshmanan, N., Raghuprasad, B.K., Muthurnani, K., Gopalakrishnan, N. and Basu, D. (2008), "Identification of reinforced concrete beam-like structures subjected to distributed damage from experimental static measurements", Comput. Concr., 5(1), 37-60. https://doi.org/10.12989/cac.2008.5.1.037
  10. Lee, J.W., Choi, K.H. and Huh, Y.C. (2010), "Damage Detection Method for Large Structures Using Static and Dynamic Strain data from Distributed Fiber Optic Sensor", J. Steel Struct., 10(1), 91-97. https://doi.org/10.1007/BF03249515
  11. Lozano-Galant, J.A., Nogal, M., Castillo, E. and Turmo, J. (2013a), "Application of observability techniques to structural system identification", Comp.-Aided Civ. Inf., 28(6), 434-450. https://doi.org/10.1111/mice.12004
  12. Lozano-Galant, J.A., Xu, D., Paya-Zaforteza, I. and Turmo, J. (2013b), "Direct simulation of the tensioning process of cable-stayed bridges", Comput. Concr., 121, 64-75.
  13. Lozano-Galant, J.A., Nogal, M., Paya-Zaforteza, I. and Turmo, J. (2014a), "Structural system identification of cable-stayed bridges with observability techniques", Struct. Infrastruct. E., 10(11), 1331-1344. https://doi.org/10.1080/15732479.2013.807292
  14. Lozano-Galant, J.A., Ruiz-Ripoll, L., Paya-Zaforteza, I. and Turmo, J. (2014b), "Modifications of the stress-state of cable-stayed bridges due to staggered erection of their superstructure", Baltic J. Road and Bridge Eng., 9(4), 241-250. https://doi.org/10.3846/bjrbe.2014.30
  15. Lozano-Galant, J.A. and Turmo, J. (2014a), "An algorithm for simulation of concrete cable-stayed bridges built on temporary supports and considering time-dependent effects", Eng. Struc., 79, 341-353. https://doi.org/10.1016/j.engstruct.2014.08.018
  16. Lozano-Galant, J.A. and Turmo, J. (2014b), "Creep and shrinkage effects in service stresses of concrete cable-stayed bridges", Comput. Concr., 13(4), 483-499. https://doi.org/10.12989/cac.2014.13.4.483
  17. Ni, Y.Q., Zhang, P., Ye, X.W., Lin, K.C. and Liao, W.Y. (2011), "Modeling of temperature distribution in a reinforced concrete supertall structure based on structural health monitoring data", Comput. Concr., 8(3), 293-309. https://doi.org/10.12989/cac.2011.8.3.293
  18. Meo, M. and Zumpano, G. (2005), "On the optimal sensor placement techniques for a bridge structure", Eng. Struct., 27(10), 1488-1497. https://doi.org/10.1016/j.engstruct.2005.03.015
  19. Podolny, W. and Scalzi, J.B. (1986), Construction and design of cable-stayed bridges. 2nd ed. New York: John Wiley & Sons.
  20. Pothisiri, T. and Hjelmstad, K.D. (2002), "Strategy for finding a near-optimal measurement set for parameter estimation from modal response", J. Sound Vib., 257(1), 89-106. https://doi.org/10.1006/jsvi.2002.5030
  21. Raich, A.M. and Liszkai, T.R. (2012), "Multi-Objective Optimization of Sensor and Excitation Layouts for Frequency Response Function-based Structural Damage Identification", Comp.-Aided Civ. Inf., 27(2), 95-117. https://doi.org/10.1111/j.1467-8667.2011.00726.x
  22. Sanayei, M., Onipede, O. and Babu, S.R. (1992), "Selection of Noisy Measurement Locations for Error Reduction in Static Parameter Identification", AIAA J., 30(9), 2299-2309. https://doi.org/10.2514/3.11218
  23. Sanayei, M. and Saletnik, J. (1996), "Parameter estimation of structures from static strain measurements. I-formulation", J. Struct. Eng. - ASCE, 122(5), 555-562. https://doi.org/10.1061/(ASCE)0733-9445(1996)122:5(555)
  24. Sanayei, M., Imbaro, G.R., McClain, J.A.S. and Brown, L.C. (1997), "Structural Model Updating Using Experimental Static Measurements". J. Struct. Eng. - ASCE, 123(6), 792-798. https://doi.org/10.1061/(ASCE)0733-9445(1997)123:6(792)
  25. S.E.T.R.A. (2001), Haubans. Recommandations de la Commission Interministerielle de la Precontrainte, Service d'Etudes Techniques des Routes et Autoroutes, France.
  26. Sumitro, S., Jarosevic, A. and Wang, M.L. (2002), "Elasto-Magnetic Sensor Utilization on Steel cable-stress measurement", Proceedings on the 1st fib Congress.
  27. Swensson, H. (2012), Cable-stayed bridges. Ernst & Sohn Gmbh and Co.
  28. Turker, T., Bayraktar, A. and Sevim, B. (2014), "Vibration based damage identification of concrete arch dams by finite element model updating", Comput. Concr., 13(2), 209-220. https://doi.org/10.12989/cac.2014.13.2.209
  29. Ubertini, F., Gentile, C. and Materzzi, A.L. (2013), "Automated modal identification in operational conditions and its application to bridges". Eng. Struct., 46, 264-278. https://doi.org/10.1016/j.engstruct.2012.07.031
  30. Zhang, J.Y. and Oshaki, M. (2011), "Force identification of prestressed pin-jointed structures", Comput. Struct., 89(23-24), 2361-2368. https://doi.org/10.1016/j.compstruc.2011.07.007

피인용 문헌

  1. Constrained observability method in static structural system identification vol.25, pp.1, 2018, https://doi.org/10.1002/stc.2040
  2. Static structural system identification for beam-like structures using compatibility conditions vol.25, pp.1, 2018, https://doi.org/10.1002/stc.2062
  3. Solving Some Special Cases of Monomial Ratio Equations Appearing Frequently in Physical and Engineering Problems vol.2016, 2016, https://doi.org/10.1155/2016/9764913
  4. Numerical damage identification of structures by observability techniques based on static loading tests vol.12, pp.9, 2016, https://doi.org/10.1080/15732479.2015.1101143
  5. Analysis of measurement and simulation errors in structural system identification by observability techniques vol.24, pp.6, 2017, https://doi.org/10.1002/stc.1923
  6. Structural system identification of thin web bridges by observability techniques considering shear deformation vol.123, 2018, https://doi.org/10.1016/j.tws.2017.11.017
  7. Damage assessment based on static and dynamic responses applied to foundation beams vol.72, pp.5, 2015, https://doi.org/10.12989/sem.2019.72.5.585
  8. Calibration of the descent local search algorithm parameters using orthogonal arrays vol.35, pp.9, 2015, https://doi.org/10.1111/mice.12545
  9. Structural Health Monitoring of 2D Plane Structures vol.11, pp.5, 2021, https://doi.org/10.3390/app11052000
  10. Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method vol.21, pp.9, 2015, https://doi.org/10.3390/s21092918
  11. Robust Static Structural System Identification Using Rotations vol.11, pp.20, 2015, https://doi.org/10.3390/app11209695