DOI QR코드

DOI QR Code

Influence line- model correction approach for the assessment of engineering structures using novel monitoring techniques

  • Strauss, Alfred (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences) ;
  • Wendner, Roman (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences) ;
  • Frangopol, Dan M. (Department of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh Univ.) ;
  • Bergmeister, Konrad (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences)
  • Received : 2011.07.01
  • Accepted : 2011.09.11
  • Published : 2012.01.25

Abstract

In bridge engineering, maintenance strategies and thus budgetary demands are highly influenced by construction type and quality of design. Nowadays bridge owners and planners tend to include life-cycle cost analyses in their decision processes regarding the overall design trying to optimize structural reliability and durability within financial constraints. Smart permanent and short term monitoring can reduce the associated risk of new design concepts by observing the performance of structural components during prescribed time periods. The objectives of this paper are the discussion and analysis of influence line or influence field approaches in terms of (a) an efficient incorporation of monitoring information in the structural performance assessment, (b) an efficient characterization of performance indicators for the assessment of structures, (c) the ability of optimizing the positions of sensors of a monitoring system, and (d) the ability of checking the robustness of the monitoring systems applied to a structure. The proposed influence line- model correction approach has been applied to an integrative monitoring system that has been installed for the performance assessment of an existing three-span jointless bridge.

Keywords

References

  1. Bathe, K.J. (1995), Finite-Element-Method, Springer.
  2. Bergmeister, K. and Wendner, R., Wörner, J.D. and Fingerloos, F. (2010), "Monitoring und Strukturidentifikation von Betonbrucken", Betonkalender, 1, 245-290.
  3. Cervenka, V., Jendele, L. and Cervenka, J. (2007), ATENA Program Documentation, Part I, Theorie. Prague, Czech Republic.
  4. Doebling, S.W., Farrar, C.R., Prime, M.B. and Shevitz, D.W. (1996), Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review, Los Alamos National Laboratory.
  5. Dorvash, S., Yao, R., Pakzad, S. and Okaly, K. (2010), "Static and dynamic model validation and damage detection using wireless sensor networks", Proceedings of the 5th international conference on bridge maintenance, safety and management IABMAS2010, D.M. Frangopol, R. Sause and C.S. Kusko. Philadelphia, Pennsylvania, USA, Taylor & Francis Group, London, 1282-1286 (on CD-ROM).
  6. Eurocode - Basis of structural design (2002), EN 1990. Brüssel, Belgium, European Committee for Standarization.
  7. Frangopol, D.M. (2011), "Life-cycle performance, management, and optimization of structural systems under uncertainty: accomplishments and challenges", Struct. Infrastruct. E., 7(6), 389-413. https://doi.org/10.1080/15732471003594427
  8. Frangopol, D.M. and Okasha, N.M. (2008), "Life-cycle performance and redundancy of structures", Proceedings of the 6th Int. Probabilistic Workshop, C.A. Graubner, H. Schmidt and D. Proske. Technische Universität, Darmstadt, Germany, 1-14.
  9. Frangopol, D.M., Strauss, A. and Kim, S. (2008a), "Use of monitoring extreme data for the performance prediction of structures: General approach", Eng. Struct. 30(12), 3644-3653. https://doi.org/10.1016/j.engstruct.2008.06.010
  10. Frangopol, D.M., Strauss, A. and Kim, S. (2008b), "Bridge reliability assessment based on monitoring", J. Bridge Eng., 13(3), 258-270. https://doi.org/10.1061/(ASCE)1084-0702(2008)13:3(258)
  11. Geier, R. (2010), "The benefit of monitoring for bridge maintenance", Proceedings of the 5th international conference on bridge maintenance, safety and management IABMAS2010, D.M. Frangopol, R. Sause and C. S. Kusko. Philadelphia, Pennsylvania, USA, Taylor & Francis Group, London: 415-422(on CD-ROM).
  12. Hirschfeld, K. (2008), Baustatik Theorie und Beispiele, Berlin Heidelberg New York, Springer.
  13. Hoffmann, S. (2008), System identification by directly measured influence lines - A user orientated approach for global damage identification at reinforced concrete bridges. Wien, Universitat fur Bodenkultur. Dissertation: 149.
  14. Hoffmann, S., Wendner, R., Strauss, A., Ralbovsky, M. and Bergmeister, K. (2007), "AIFIT-anwenderorientierte identifikation für Ingenieurtragwerke, versuchsgestützte steifigkeitsanalysen", Betonund Stahlbetonbau, 102(10), 699-706. https://doi.org/10.1002/best.200700575
  15. Inaudi, D. (2010), "Optimal design of bridge SHM systems based on risk and opportunity analysis", Proceedings of the 5th international conference on bridge maintenance, safety and management IABMAS2010, D.M. Frangopol, R. Sause and C.S. Kusko. Philadelphia, Pennsylvania, USA, Taylor & Francis Group, London: 2119-2126 (on CD-ROM).
  16. Kim, S. and Frangopol, D.M. (2010), "Optimal planning of structural performance monitoring based on reliability assessment", Probab. Eng. Mech., 25(1), 86-98. https://doi.org/10.1016/j.probengmech.2009.08.002
  17. Kim, S. and Frangopol, D.M. (2011a), "Cost-effective lifetime structural health monitoring based on availability", J. Struct. Eng., 137(1), 22-33 https://doi.org/10.1061/(ASCE)ST.1943-541X.0000280
  18. Kim, S. and Frangopol, D.M. (2011b), "Cost-based optimum scheduling of inspection and monitoring for fatiguesensitive structures under uncertainty", J. Struct. Eng-ASCE, 137(11).
  19. Kwon, K. and Frangopol, D.M. (2010), "Bridge fatigue reliability assessment using probability density functions based on field monitoring data", Int. J. Fatigue, 32(8), 1221-1232. https://doi.org/10.1016/j.ijfatigue.2010.01.002
  20. Liu, M., Frangopol, D.M. and Kim, S. (2009a), "Bridge system performance assessment from structural health monitoring: a case study", J. Struct. Eng-ASCE, 135(6), 733-742. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000014
  21. Liu, M., Frangopol, D.M. and Kim, S. (2009b), "Bridge safety evaluation based on monitored live load effects", J. Bridge Eng., 14(4), 257-269. https://doi.org/10.1061/(ASCE)1084-0702(2009)14:4(257)
  22. Liu, M., Frangopol, D.M. and Kwon, K. (2010a), "Fatigue reliability assessment of retrofitted steel bridges integrating monitoring data", Struct. Saf., 32(1), 77-89. https://doi.org/10.1016/j.strusafe.2009.08.003
  23. Liu, M., Frangopol, D.M. and Kwon, K. (2010b), "Optimization of retrofitting distortion-induced fatigue cracking of steel bridges using monitored data under uncertainty", Eng. Struct., 32(11), 3467-3477. https://doi.org/10.1016/j.engstruct.2010.07.016
  24. Mayr, M. and Thalhofer, U. (1993), Numerische Losungsverfahren in der Praxis: FEM-BEM-FDM, Hanser.
  25. Messervey, T.B. and Frangopol, D.M. (2009), "Life-cycle cost and performance prediction: role of structural health monitoring", Frontier Technologies for Infrastructures Engineering. S.S. Chen and A.H.S. Ang. Leiden, The Netherlands, CRC Press-Balkema-Taylor & Francis Group: 361-381.
  26. Messervey, T.B., Frangopol, D.M. and Casciati, S. (2010), "Application of statistics of extremes to the reliability assessment of monitored highway bridges", Struct. Infrastruct. E., 7(1-2), 87-99.
  27. Novak, D. and Lehký, D. (2006), "ANN inverse analysis based on stochastic small-sample training set simulation", Eng. Apl. Artif. Intel., 19(7), 731-740. https://doi.org/10.1016/j.engappai.2006.05.003
  28. Orcesi, A.D. and Frangopol, D.M. (2010a), "Inclusion of crawl tests and long-term health monitoring in bridge serviceability analysis", J. Bridge Eng., 15(3), 312-326. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000060
  29. Orcesi, A.D. and Frangopol, D.M. (2010b), "Optimization of bridge management under budget constraints: Role of structural health monitoring", Transportation Research Record: Journal of the Transportation Research Board (Bridge Engineering 2010: Volumes 1-3), 3(2202), 148-158.
  30. Orcesi, A.D. and Frangopol, D.M. (2011), "Optimization of bridge maintenance strategies based on structural health monitoring information", Struct. Saf., 33(1), 26-41. https://doi.org/10.1016/j.strusafe.2010.05.002
  31. Orcesi, A.D., Frangopol, D.M. and Kim, S. (2010), "Optimization of bridge maintenance strategies based on multiple limit states and monitoring", Eng. Struct., 32(3), 627-640. https://doi.org/10.1016/j.engstruct.2009.11.009
  32. RVS 13.03.11, "Monitoring von Brucken und anderen Ingenieurbauwerken", Uberwachung, Kontrolle und Prufung von Kunstbauten - Strassenbrucken.
  33. Strauss, A., Bergmeister, K., Novak, D. and Lehky, D. (2004), "Stochastische parameteridentifikation bei konstruktionsbeton fur die betonerhaltung", Beton- und Stahlbetonbau, 99(12), 967-975. https://doi.org/10.1002/best.200490282
  34. Strauss, A., Bergmeister, K., Wendner, R. and Hoffmann, S. (2009a), "System- und Schadensidentifikation von Betonstrukturen", Betonkalender, 2, 55-125.
  35. Strauss, A., Frangopol, D.M. and Kim, S. (2008c), "Use of monitoring extreme data for the performance prediction of structures: Bayesian updating", Eng. Struct., 30(12), 3654-3666. https://doi.org/10.1016/j.engstruct.2008.06.009
  36. Strauss, A., Frangopol, D.M. and Kim, S. (2008d), "Statistical, probabilistic and decision analysis aspects related to the efficient use of structural monitoring systems", Beton- und Stahlbetonbau,103(S1), 23-28. https://doi.org/10.1002/best.200810119
  37. Strauss, A., Hoffmann, S., Wendner, R. and Bergmeister, K. (2009b), "Structural assessment and reliability analysis for existing engineering structures, applications for real structures", Struct. Infrastruct. E., 5(4), 277-286. https://doi.org/10.1080/15732470601185638
  38. Strauss, A., Wendner, R., Bergmeister, K. and Frangopol, D.M. (2010a), "Monitoring based analysis of an concrete frame bridge Marktwasser bridge", Proceedings of the 3rd International fib Congress, Washington, DC, USA.
  39. Strauss, A., Wendner, R., Bergmeister, K. and Frangopol, D.M. (2011), "Monitoring and influence lines based performance indicators", ICASP 11 Applications of Statistics and Probability in Civil Engineering, M. Faber, J. Köhler and K. Nishijma. Zurich, Switzerland: 1059-1068.
  40. Strauss, A., Wendner, R., Bergmeister, K. and Horvatits, J. (2011), "Modellkorrekturfaktoren als "Performance Indikatoren", fur die Langzeitbewertung der integralen Marktwasserbrücke S33.24", Beton- und Stahlbetonbau, 106(4), 231-240. https://doi.org/10.1002/best.201100003
  41. Strauss, A., Wendner, R., Bergmeister, K. and Reiterer, M. (2010), "Monitoringbasierte analyse von integralen brucken am beispiel der marktwasserbrücke", Schriftenreihe des Departments, K. Bergmeister. Vienna, Department für Bautechnik und Naturgefahren, Universitat fur Bodenkultur. 20.
  42. Vrouwenvelder, T. (1997), "The JCSS probabilistic model code", Struct. Saf., 19(3), 245-251. https://doi.org/10.1016/S0167-4730(97)00008-8
  43. Wendner, R., Strauss, A., Bergmeister, K. and Frangopol, D.M. (2010b), "Monitoring based evaluation of design criteria for concrete frame bridges", IABSE Symposium 2010, Venice, Italy.
  44. Wendner, R., Strauss, A., Guggenberger, T., Bergmeister, K. and Teplý, B. (2010), "Ansatz zur beurteilung von chloridbelasteten stahlbetonbauwerken mit bewertung der restlebensdauer", Beton- und Stahlbetonbau, 105(12), 778-786. https://doi.org/10.1002/best.201000049
  45. Wenzel, H. and Egerer, V. (2010), Determination of a performance baseline for lifecycle consideration of bridges, Proceedings of the 5th international conference on bridge maintenance, safety and management IABMAS2010, D.M. Frangopol, R. Sause and C.S. Kusko. Philadelphia, Pennsylvania, USA, Taylor & Francis Group, London: 1282-1286 (on CD-ROM).
  46. Zilch, K., Weiher, H., Glaser, C., Bergmeister, K., Fingerloos, F. and J.D. Wörner. (2009), "Monitoring im betonbau", Betonkalender, 2.
  47. JCSS Probabilistic Model Code Part 1: Basis of Design (2001).

Cited by

  1. Optimization method, choice of form and uncertainty quantification of Model B4 using laboratory and multi-decade bridge databases vol.48, pp.4, 2015, https://doi.org/10.1617/s11527-014-0515-0
  2. Localized reliability analysis on a large-span rigid frame bridge based on monitored strains from the long-term SHM system vol.14, pp.2, 2014, https://doi.org/10.12989/sss.2014.14.2.209
  3. Extraction of influence line through a fitting method from bridge dynamic response induced by a passing vehicle vol.151, 2017, https://doi.org/10.1016/j.engstruct.2017.06.067
  4. Reliability-based approach to the robustness of corroded reinforced concrete structures vol.18, pp.2, 2017, https://doi.org/10.1002/suco.201600084
  5. Application of influence lines for the ultimate capacity of beams under moving loads vol.103, 2015, https://doi.org/10.1016/j.engstruct.2015.09.003
  6. Baseline-free real-time assessment of structural changes vol.11, pp.2, 2015, https://doi.org/10.1080/15732479.2013.858169
  7. Direct kinematic method for exactly constructing influence lines of forces of statically indeterminate structures vol.54, pp.4, 2015, https://doi.org/10.12989/sem.2015.54.4.793
  8. Influence line extraction by deconvolution in the frequency domain vol.189, 2017, https://doi.org/10.1016/j.compstruc.2017.04.014
  9. Tragkapazität schlanker Druckglieder vol.110, pp.12, 2015, https://doi.org/10.1002/best.201500040
  10. 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
  11. Inclined Approach Slab Solution for Jointless Bridges: Performance Assessment of the Soil–Structure Interaction vol.29, pp.2, 2015, https://doi.org/10.1061/(ASCE)CF.1943-5509.0000522
  12. Prediction of the remaining service life of existing concrete bridges in infrastructural networks based on carbonation and chloride ingress vol.21, pp.3, 2012, https://doi.org/10.12989/sss.2018.21.3.305
  13. Aging concrete structures: a review of mechanics and concepts vol.69, pp.3, 2018, https://doi.org/10.2478/boku-2018-0015
  14. Bridge influence line identification based on adaptive B‐spline basis dictionary and sparse regularization vol.26, pp.6, 2012, https://doi.org/10.1002/stc.2355
  15. Bridge Influence Line Identification Based on Regularized Least-Squares QR Decomposition Method vol.24, pp.8, 2019, https://doi.org/10.1061/(asce)be.1943-5592.0001458
  16. Non-contact structural health monitoring of a cable-stayed bridge: case study vol.15, pp.8, 2019, https://doi.org/10.1080/15732479.2019.1609529
  17. A Novel Runtime Algorithm for the Real-Time Analysis and Detection of Unexpected Changes in a Real-Size SHM Network with Quasi-Distributed FBG Sensors vol.21, pp.8, 2012, https://doi.org/10.3390/s21082871
  18. Eliminating the Influence of Axle Parameters in Influence Line Identification vol.16, pp.4, 2021, https://doi.org/10.7250/bjrbe.2021-16.547