Coupled systems mechanics

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Spatial interpolation of SPT data and prediction of consolidation of clay by ANN method

  • Kim, Hyeong-Joo (Department of Civil Engineering, Kunsan National University) ;
  • Dinoy, Peter Rey T. (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Choi, Hee-Seong (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Lee, Kyoung-Bum (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Mission, Jose Leo C. (Department of Civil and Environmental Engineering, Kunsan National University)
  • Received : 2019.03.08
  • Accepted : 2019.11.13
  • Published : 2019.12.25
⟨ Previous Next ⟩

Abstract

Artificial Intelligence (AI) is anticipated to be the future of technology. Hence, AI has been applied in various fields over the years and its applications are expected to grow in number with the passage of time. There has been a growing need for accurate, direct, and quick prediction of geotechnical and foundation engineering models especially since the success of each project relies on numerous amounts of data. In this study, two applications of AI in the field of geotechnical and foundation engineering are presented - spatial interpolation of standard penetration test (SPT) data and prediction of consolidation of clay. SPT and soil profile data may be predicted and estimated at any location and depth at a site that has no available borehole test data using artificial intelligence techniques such as artificial neural networks (ANN) based on available geospatial information from nearby boreholes. ANN can also be used to accelerate the calculation of various theoretical methods such as the one-dimensional consolidation theory of clay with high efficiency by using lesser computation resources. The results of the study showed that ANN can be a valuable, powerful, and practical tool in providing various information that is needed in geotechnical and foundation design.

Keywords

Acknowledgement

Supported by : Korea Institute of Energy Technology Evaluation and Planning (KETEP)

This work was supported by Kunsan National University, and the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20183010025200).

References

  1. Abbas, N.E., Khamlichi, A. and Bezzazi, M. (2016), "Seismic response of foundation-mat structure subjected to local uplift", Coupled Syst. Mech., 5(4), 285-304. https://doi.org/10.12989/csm.2016.5.4.285.
  2. Ayat, H., Kellouche, Y., Ghrici, M. and Boukhatem, B. (2018), "Compressive strength prediction of limestone filler concrete using artificial neural networks", Adv. Comput. Des., 3(3), 289-302. https://doi.org/10.12989/acd.2018.3.3.289.
  3. Booker, J.R. and Small, J.C. (1975), "An investigation of the stability of numerical Solutions of Biot's equations of consolidation", Int. J. Solids Struct., 11(7-8), 907-917. https://doi.org/10.1016/0020-7683(75)90013-X.
  4. Brandenberg, S.J. (2016), "iConsol.js: JavaScript implicit finite-difference code for nonlinear consolidation and secondary compression", Int. J. Geomech., 17(6), 1-11. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000843.
  5. Cao, W., Chen, Y. and Wolfe, W.E. (2014), "New load transfer hyperbolic model for pile-soil interface and negative skin friction on single piles embedded in soft soils", Int. J. Geomech., 14(1), 92-100. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000289.
  6. Chakraverty, S. and Nayak, S. (2012), "Fuzzy finite element method for solving uncertain heat conduction problems", Coupled Syst. Mech., 1(4), 345-360. http://doi.org/10.12989/csm.2012.1.4.345.
  7. Chore, H.S. and Magar, R.B. (2017), "Prediction of unconfined compressive and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes using multiple linear regression and artificial neural network", Adv. Comput. Des., 2(3), 225-240. https://doi.org/10.12989/acd.2017.2.3.225.
  8. Cover, T.M. and Hart, P.E. (1967), "Nearest neighbor pattern classification", IEEE T. Inform. Theor., 13(1), 21-27. https://doi.org/10.1109/TIT.1967.1053964.
  9. Demuth, H., Beale, M., and Hagan, M. (2009), Neural Networks Toolbox User Guide, The Math Works Inc., Natick, Massachusetts, U.S.A.
  10. Erzin, Y. and Gul, T. (2013), "The use of neural networks for the prediction of the settlement of pad footings on cohesionless soils based on standard penetration test", Geomech. Eng., 5(6), 541-564. https://doi.org/10.12989/gae.2013.5.6.541.
  11. Forsythe, G.E. and Wasow, W.R. (1960), Finite Difference Methods for Partial Differential Equations, John Wiley & Sons, Inc., New York, U.S.A.
  12. Fox, P.J., Pu, H.F. and Berles, J.D. (2014), "CS3: Large strain consolidation model for layered soils", J. Geotech. Geoenviron. Eng., 140(8), 1-13. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001128.
  13. Ganaie, A.H. and Sawant, V.A. (2015), "Analysis of a strip footing on a homogeneous soil using element free Galerkin method", Coupled Syst. Mech., 4(4), 365-383. https://doi.org/10.12989/csm.2015.4.4.365.
  14. Gibson, R.E., England, G.L. and Hussey, M.J.L. (1967), "The theory of one-dimensional consolidation of saturated clays", Geotechnique, 17(3), 261-273. https://doi.org/10.1680/geot.1967.17.3.261.
  15. Hazzard, J. and Yacoub, T. (2008), "Consolidation in multi-layered soils: A hybrid computational scheme", Proceedings of the GeoEdmonton, 08 61st Canadian Geotechnical Conference and 9th Joint CGS/IAH-CNC Groundwater Conference, Edmonton, Canada, September.
  16. Kim, H.J. and Mission, J.L. (2011), "Probabilistic evaluation of economical factors of safety for the geotechnical design of pile axial load capacity using Monte Carlo simulation", KSCE J. Civ. Eng., 15(7), https://doi.org/1167-1176.10.1007/s12205-011-0948-8.
  17. Kim, H.J., Hirokane, S., Yoshikuni, H., Moriwaki, T., and Kusakabe, Q. (1995), "Consolidation behavior of dredged clay ground improved by horizontal drain method," Proceedings of the International Symposium on Compression and Consolidation Clay Soils, Hiroshima, Japan, May.
  18. Kim. H.J., Mission, J.L., Park, T.W. and Dinoy, P.R. (2018), "Analysis of negative skin-friction on single piles by one-dimensional consolidation model test", Int. J. Civ. Eng., 16(10), 1445-1461. https://doi.org/10.1007/s40999-018-0299-7.
  19. Liu, J., Gao, H. and Liu, H. (2012), "Finite element analyses of negative skin friction on a single pile", Acta Geotech., 7(3), 239-252. https://doi.org/10.1007/s11440-012-0163-x.
  20. Lopez-Chavarria, S., Luevanos-Rojas, A. and Medina-Elizondo, M. (2017), "Optimal dimensioning for the corner combined footings", Adv. Comput. Des., 2(2), 107-121. https://doi.org/10.12989/acd.2017.2.2.169.
  21. Lopez-Chavarria, S., Luevanos-Rojas, A., Medina-Elizondo, M., Sandoval-Rivas, R. and Velazquez-Santillan, F. (2019), "Optimal design for the reinforced concrete circular isolated footings", Adv. Comput. Des., 4(3), 273-294. https://doi.org/10.12989/acd.2019.4.3.273.
  22. MAA Geotechnics Co., Ltd. (2013), Final Geotechnical Investigation Report for Upstream Project for Hygiene and Value Added Products-IRPC Public Company Limited, 27 February 2013.
  23. Mandal, A. and Maity, D. (2019), "Seismic analysis of dam-foundation-reservoir coupled system using direct coupling method", Coupled Syst. Mech., 8(5), 393-414. https://doi.org/10.12989/csm.2019.8.5.393.
  24. MATLAB (2012), The MathWorks, Inc., www.mathworks.com.
  25. Mission, J.L., Kim, H.J. and Lee, K.H. (2013), "Artificial neural network (ANN) application for spatial interpolation of standard penetration test (SPT) and soil profile data", Proceedings of the 2013 World Congress on Advances in Structural Engineering and Mechanics (ASEM13), Jeju, Korea, September.
  26. Singh, M. and Sawant, V.A. (2014), "Parametric study on flexible footing resting on partially saturated soil", Coupled Syst. Mech., 3(2), 233-245. https://doi.org/10.12989/csm.2014.3.2.233.
  27. Sunny, M.R., Mulani, S.B., Sanyal, S. and Kapania, R.K. (2016), "An artificial neural network residual kriging based surrogate model for curvilinearly stiffened panel optimization", Adv. Comput. Des., 1(3), 235-251. https://doi.org/10.12989/acd.2016.1.3.235.
  28. Terzaghi, K. (1943), Theoretical Soil Mechanics, John Wiley & Sons, Inc. New York, U.S.A.
  29. Velazquez-Santillan, F., Luevanos-Rojas, A., Lopez-Chavarria, S., Medina-Elizondo, M. and Sandoval-Rivas, R. (2018), "Numerical experimentation for the optimal design for reinforced concrete rectangular combined footings", Adv. Comput. Des., 3(1), 49-69. https://doi.org/10.12989/acd.2018.3.1.049.