DOI QR코드

DOI QR Code

Probabilistic real-time updating for geotechnical properties evaluation

  • Ng, Iok-Tong (Department of Civil and Environmental Engineering. Faculty of Science and Technology, University of Macau) ;
  • Yuen, Ka-Veng (Department of Civil and Environmental Engineering. Faculty of Science and Technology, University of Macau) ;
  • Dong, Le (Department of Civil and Environmental Engineering. Faculty of Science and Technology, University of Macau)
  • Received : 2014.12.02
  • Accepted : 2015.03.12
  • Published : 2015.04.25

Abstract

Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.

Keywords

References

  1. Asaoka, A. and A-Grivas, D. (1982), "Spatial variability of the undrained strength of clays", J. Geotech. Eng., ASCE, 108(5), 743-756.
  2. Baecher, G.B. and Christian, J.T. (2003), Reliability and Statistics in Geotechnical Engineering, John Wiley & Sons, Hoboken, New Jersey.
  3. Beck, J.L. and Katafygiotis, L.S. (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)
  4. Beck, J.L. and Yuen, K.V. (2004), "Model selection using response measurements: Bayesian probabilistic approach", J. Eng. Mech., 130(2), 192-203. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:2(192)
  5. Bjerrum, L. and Simons, N.E. (1960), "Comparison of shear strength characteristics of normally consolidated clays", Proceedings of the 1st ASCE Specialty Conference on Shear Strength of Cohesive Soils, Boulder, Colorado, 711-726.
  6. Cao, Z. and Wang,Y. (2013), "Bayesian approach for probabilistic site characterization using cone penetration tests", J. Geotech. Geoenviron. Eng., 139(2), 267-276. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000765
  7. Cao, Z. and Wang Y. (2014a), "Bayesian model comparison and characterization of undrained shear strength", J. Geotech. Geoenviron. Eng., 140(6), Article number 04014018.
  8. Cao, Z. and Wang Y. (2014b), "Bayesian model comparison and selection of spatial correlation functions for soil parameters", Struct. Saf., 49, 10-17. https://doi.org/10.1016/j.strusafe.2013.06.003
  9. Chandler, R.J. (1988), "The in-situ measurement of the undrained shear strength of clays using the field vane", Vane Shear Strength Testing in Soils: Field and Laboratory Studies, 13-44.
  10. Ching, J., Phoon, K.K. and Chen, Y.C. (2010), "Reducing shear strength uncertainties in clays by multivariate correlations", Can. Geotech. J., 47(1), 16-33. https://doi.org/10.1139/T09-074
  11. Chiu, C.F., Yan, W.M. and Yuen, K.V. (2012a), "Estimation of water retention curve of granular soils from particle-size distribution-a Bayesian probabilistic approach", Can. Geotech. J., 49(9), 1024-1035. https://doi.org/10.1139/t2012-062
  12. Chiu, C.F., Yan, W.M. and Yuen, K.V. (2012b), "Reliability analysis of soil-water characteristics curve and its application to slope stability analysis", Eng. Geol., 135, 83-91.
  13. Hvorslev, M.J. (1949), "Subsurface exploration and sampling of soils for civil engineering purposes", Waterways Experiment Station, Vicksburg.
  14. Jaksa, M.B., Brooker, P.I. and Kaggwa, W.S. (1997), "Inaccuracies associated with estimating random measurement errors", J. Geotech. Geoenviron. Eng., 123(5), 393-401. https://doi.org/10.1061/(ASCE)1090-0241(1997)123:5(393)
  15. Jaksa, M.B., Goldsworthy, J.S., Fenton, G.A., Kaggwa, W.S., Griffiths, D.V., Kuo, Y.L. and Poulos, H.G. (2005), "Towards reliable and effective site investigations", Geotechnique, 55(2), 109-121. https://doi.org/10.1680/geot.2005.55.2.109
  16. Kaloop, M.R., Sayed, M.A., Kim, D. and Kim, E. (2014), "Movement identification model of port container crane based on structural health monitoring system", Struct. Eng. Mech., 50, 105-119. https://doi.org/10.12989/sem.2014.50.1.105
  17. Kulhawy, F.H. and Trautmann, C.H. (1996), "Estimation of in-situ test uncertainty", Uncert. Geol. Envir., F. Theory Pract., Geotechnical Special Publication, 58(1), 269-286.
  18. Kuok, S.C. and Yuen, K.V. (2012), "Structural health monitoring of Canton tower using Bayesian framework", Smart Struct. Syst., 10(4-5), 375-391. https://doi.org/10.12989/sss.2012.10.4_5.375
  19. Ladd, C.C., Foote, R., Ishihara, K., Schlosser, F. and Poulos, H.G. (1977), "Stress-deformation and strength characteristics", Proceedings of 9th International Conference on Soil Mechanics and Foundation Engineering, 2, Tokyo.
  20. Larsson, R. (1980), "Undrained shear strength in stability calculation of embankments and foundations on clays", Can. Geotech. J., 17(4), 591-602. https://doi.org/10.1139/t80-066
  21. Lei, Y., Lai, Z., Zhu, S. and Zhang, X. (2014a), "Experimental study on impact induced damage detection using an improved extended Kalman filter", Int. J. Struct. Stab. Dyn., 14(5), 1440007. https://doi.org/10.1142/S0219455414400070
  22. Lei, Y., Chen, F. and Zhou, H. (2014b), "An algorithm based on two-step Kalman filter for intelligent structural damage detection", Struct. Control Hlth. Monit., 22, 694-706.
  23. Lumb , P. (1966), "The variability of natural soils", Can. Geotech. J., 3(2), 74-79. https://doi.org/10.1139/t66-009
  24. Lumb, P. and Holt, J.K. (1968), "The undrained shear strength of a soft marine clay from Hong Kong", Geotechnique, 18(1), 25-36. https://doi.org/10.1680/geot.1968.18.1.25
  25. Mayne, P.W. (2012), "Quandary in geomaterial characterization: new versus the old", Shaking the Foundations of Geo-engineering Education, 15-26.
  26. Mesri, G. (1975), "Discussion on new design procedures for stability of soft clays", J. Geotech. Eng., ASCE, 101(4), 409-412.
  27. Mu, H.Q. and Yuen, K.V. (2015), "Novel outlier-resistant extended Kalman filter for robust online structural identification", J. Eng. Mech., ASCE, 141(1), 04014100. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000810
  28. Ng, I.T., Yuen, K.V. and Dong, L. (2014), "Nonparametric estimation of undrained shear strength for normally consolidated clays", Marine Geores. Geotech., DOI:10.1080/1064119X.2014.970305.
  29. Osterberg, J.O. (1989), "Necessary redundancy in geotechnical engineering", J. Geotech. Eng., ASCE, 115(11), 1513-1531. https://doi.org/10.1061/(ASCE)0733-9410(1989)115:11(1513)
  30. Phoon, K.K. and Kulhawy, F.H. (1999), "Characterization of geotechnical variability", Can. Geotech. J., 36(4), 612-624. https://doi.org/10.1139/t99-038
  31. Rezaiee-Pajand, M. and Kazemiyan, M.S. (2014), "Damage identification of 2D and 3D trusses by using complete and incomplete noisy measurements", Struct. Eng. Mech., 52, 149-172. https://doi.org/10.12989/sem.2014.52.1.149
  32. Skempton, A.W. (1957), "Discussion of the planning and design of the new Hong Kong Air Port", Proceedings of the Institution of Civil Engineers, London, 7(2), 305-307. https://doi.org/10.1680/iicep.1957.2568
  33. Standard, B. (1981), Code of Practice for Site Investigations, British Standards Institution, London.
  34. Vanmarcke, E.H. (1983), Random Fields, MIT Press, Cambridge.
  35. Wang, V.Z. and Ginger, J.D. (2014), "Maximum a posteriori estimation based wind fragility analysis with application to existing linear or hysteretic shear frames", Struct. Eng. Mech., 50, 653-664. https://doi.org/10.12989/sem.2014.50.5.653
  36. Wang, Y., Au, S.K. and Cao, Z. (2010), "Bayesian approach for probabilistic characterization of sand friction angles", Eng. Geol., 114(3-4), 354-363. https://doi.org/10.1016/j.enggeo.2010.05.013
  37. Wang, Y. and Cao, Z. (2013), "Probabilistic characterization of Young's modulus of soil using equivalent samples", Eng. Geol., 159, 106-118. https://doi.org/10.1016/j.enggeo.2013.03.017
  38. Whitman, R.V. (1984), "Evaluating calculated risk in geotechnical engineering", J. Geotech. Eng., ASCE, 110(2), 145-188.
  39. Wroth, C.P. and Houlsby, G.T. (1985), "Soil mechanics-property characterization and analysis procedures", Proceedings of the 11th International Conference on Soil Mechanics and Foundation Engineering, 1, San Francisco.
  40. Yan, W.M., Yuen, K.V. and Yoon, G.L. (2009), "Bayesian probabilistic approach for the correlations of compressibility index for marine clays", J. Geotech. Geoenviron. Eng., 135(12), 1932-1940. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000157
  41. Yuen, K.V. (2010), "Recent developments of Bayesian model class selection and applications in civil engineering", Struct. Saf., 32(5), 338-346. https://doi.org/10.1016/j.strusafe.2010.03.011
  42. Yuen, K.V., Hoi, K.I. and Mok, K.M. (2007), "Selection of noise parameters for Kalman filter", Earthq. Eng. Eng. Vib., 6(1), 49-56. https://doi.org/10.1007/s11803-007-0659-9
  43. Yuen, K.V. and Katafygiotis, L.S. (2005), "Model updating using noisy response measurements without knowledge of the input spectrum", Earthq. Eng. Struct. Dyn., 34(2), 167-187. https://doi.org/10.1002/eqe.415
  44. Yuen, K.V., Liang, P.F. and Kuok, S.C. (2013), "Online estimation of noise parameters for Kalman filter", Struct. Eng. Mech., 47(3), 361-381. https://doi.org/10.12989/sem.2013.47.3.361
  45. Yuen, K.V. and Mu, H.Q. (2011), "Peak ground acceleration estimation by linear and nonlinear models with reduced order Monte Carlo simulation", Comput. Aid. Civil Infrastr. Eng., 26(1), 30-47.
  46. Yuen, K.V. and Mu, H.Q. (2012), "Novel probabilistic method for robust parametric identification and outlier detection", Probab. Eng. Mech., 30, 48-59. https://doi.org/10.1016/j.probengmech.2012.06.002
  47. Zhang, L. M., Tang, W. H., Zhang, L.L. and Zheng, J. G. (2004), "Reducing uncertainty of prediction from empirical correlations", J. Geotech. Geoenviron. Eng., 130(5), 526-534. https://doi.org/10.1061/(ASCE)1090-0241(2004)130:5(526)
  48. Zhang, L.M. and Dasaka, S.M. (2010), "Uncertainties in geologic profiles versus variability in pile founding depth", J. Geotech. Geoenviron. Eng., 136(11), 1475-1488. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000364
  49. Zhang, J., Zhang, L.M. and Tang, W.H. (2009), "Bayesian framework for characterizing geotechnical model uncertainty", J. Geotech. Geoenviron. Eng., 135(7), 932-940. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000018
  50. Zhang, J., Tang, W.H., Zhang, L.M. and Huang, H.W. (2012), "Characterising geotechnical model uncertainty by hybrid Markov Chain Monte Carlo simulation", Comput. Geotech., 43, 26-36. https://doi.org/10.1016/j.compgeo.2012.02.002
  51. Zhou, W.H., Yuen, K.V. and Tan, F. (2013), "Estimation of maximum pullout shear stress of grouted soil nails using Bayesian probabilistic approach", Int. J. Geomech., 13(5), 659-664. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000259

Cited by

  1. Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework vol.17, pp.3, 2016, https://doi.org/10.12989/sss.2016.17.3.445
  2. Probabilistic Characterization of Site-Specific Inherent Variability of Undrained Shear Strength Using Both Indirect and Direct Measurements vol.4, pp.1, 2018, https://doi.org/10.1061/AJRUA6.0000941
  3. Hydrostatic-season-time model updating using Bayesian model class selection vol.169, 2018, https://doi.org/10.1016/j.ress.2017.07.018
  4. Uncertainty reduction of seismic fragility of intake tower using Bayesian Inference and Markov Chain Monte Carlo simulation vol.63, pp.1, 2017, https://doi.org/10.12989/sem.2017.63.1.047
  5. Dynamic performance investigation of a long-span suspension bridge using a Bayesian approach vol.168, pp.None, 2022, https://doi.org/10.1016/j.ymssp.2021.108700