Application of an Artificial Neural Network for Modeling the Mechanical Behavior of Carbonate Soils
Publication: International Journal of Geomechanics
Volume 14, Issue 1
Abstract
Carbonate soils have some distinctive features such as compressibility and skeletal particle crushability that make them distinguishable from other types of soils. Many experimental models have been developed to describe the complex behavior of carbonate soils, but despite these numerous works, there is no unified approach that can model the behavior of various types of these soils. In this paper, a new approach based on artificial neural networks is presented to predict the mechanical behavior of different carbonate soils. The network had five input neurons, namely, relative density, axial strain, maximum void ratio, calcium carbonate content, and confining pressure; ten neurons in the hidden layer; and two neurons in the output layer, namely, deviatoric stress and volumetric strain at the end of each increment. The network was trained and tested using a database that included results from a comprehensive set of triaxial tests on three carbonate soils. Comparison of the model prediction and experimental results revealed that the proposed approach was accurate and trustworthy in representing the mechanical behavior of various carbonate soils.
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References
Akin, S., and Karpuz, C. (2008). “Estimating drilling parameters for diamond bit drilling operations using artificial neural networks.” Int. J. Geomech., 68–73.
Al-Douri, R. H., and Poulos, H. G. (1991). “Static and cyclic direct shear tests on carbonate sands.” J. ASTM Geotech Test., 15(2), 138–157.
Alipour, A., Jafari, A., and Hossaini, S. M. F. (2012). “Application of ANNs and MVLRA for estimation of specific charge in small size tunnel.” Int. J. Geomech., 189–192.
Angemeer, J., Carlson, E., and Klick, J. H. (1973). “Techniques and results of offshore pile load testing in calcareous soil.” Proc., Int. Conf. on Offshore Technology, Offshore Technology Conference, Houston, 677–699.
Angemeer, J., and Mc-Neilan, T. W. (1982). “Surface variability—The geotechnical properties, behavior and performance of calcareous soils.” ASTM STP777, ASTM, West Conshohocken, PA, 36–53.
Baghdadi, Z. A., Ghazali, F. M., and Khan, A. M. (1991). “Model pile testing in calcareous sediment of Red Sea.” Can. Geotech. J., 28(3), 423–433.
Balakrishnan, S. N., and Weil, R. D. (1996). “Neurocontrol: A literature survey.” Math. Comput. Model., 23(1–2), 101–118.
Basheer, I., and Hajmeer, M. (2000). “Artificial neural networks: Fundamentals, computing, design, and application.” J. Microbiol. Methods, 43(1), 3–31.
Baxter, C. W., Stanley, S. J., Zhang, Q., and Smith, D. W. (2002). “Developing artificial neural network models of water treatment processes: A guide for utilities.” J. Environ. Eng. Sci., 1(3), 201–211.
Beringen, F. L., Kolk, H. J., and Windle, D. (1982). “Cone penetration and laboratory testing in marine calcareous sediments.” ASTM STP 777, ASTM, West Conshohocken, PA, 179–209.
Brandes, H. G. (2011). “Simple shear behavior of calcareous and quartz sands.” Geotech. Geol. Eng., 29(1), 113–126.
Catano, J., and Pando, M. A. (2010). “Static and dynamic properties of a calcareous sand from southwest Puerto Rico.” Proc., Int. Conf. on Advances in Analysis, Modeling and Design, ASCE, Reston, VA, 842–851.
Celestino, T. B., and Mitchell, J. K. (1983). “Behavior of carbonate sands for foundations of offshore structures.” Proc., Int. Symp. on Offshore Engineering, Offshore Technology Conference, Rio de Janeiro, Brazil, 85–102.
Chaney, R. C., Slonim, S. M., and Slonim, S. S. (1982). “Determination of calcium carbonate content in soils.” ASTM STP28907S, ASTM, West Conshohocken, PA, 3–15.
Coop, M. R. (1990). “The mechanics of uncemented carbonate sands.” Geotechnique, 40(4), 607–626.
Das, S., Samui, P., and Sabat, A. (2012). “Prediction of field hydraulic conductivity of clay liners using an artificial neural network and support vector machine.” Int. J. Geomech., 606–611.
Datta, M., Gulhati, S. K., and Rao, G. V. (1979). “Crushing of calcareous sand during shear.” Proc., Int. Conf. on Offshore Technology, Offshore Technology Conference, Houston, 1459–1474.
Demuth, H., Beale, M., and Hagan, M. (2007). Neural Network Toolbox 5 user’s guide, MathWorks, Natick, MA.
Ellis, G. W., Yao, C., Zhao, R., and Penumadu, D. (1995). “Stress-strain modeling of sands using artificial neural networks.” J. Geotech. Geoenviron. Eng., 429–435.
Fausett, L. V. (1994). Fundamentals of neural networks: Architecture, algorithms, and applications, Prentice Hall, Englewood Cliffs, NJ.
Flood, I., and Kartam, N. (1994). “Neural networks in civil engineering. I: Principles and understanding.” J. Comput. Civ. Eng., 131–148.
Fookes, P. G. (1988). “The geology of carbonate soils and rocks and their engineering characterisation and description.” Proc., Int. Conf. on Calcareous Sediments, Balkema, Rotterdam, Netherlands, 787–805.
Griffiths, K. A., and Andrews, R. C. (2011). “Application of artificial neural networks for filtration optimization.” J. Environ. Eng., 1040–1047.
Grine, K., Attar, A., Aoubed, A., and Breysse, A. (2011). “Using the design of experiment to model the effect of silica sand and cement on crushing properties of carbonate sand.” Mater. Struct., 44(1), 195–203.
Grine, K., and Glendinning, S. (2007). “Creation of an artificial carbonate sand.” Geotech. Geol. Eng., 25(4), 441–448.
Habibagahi, G. (1998). “Reservoir induced earthquakes analyzed via radial basis function networks.” Soil. Dyn. Earthquake Eng., 17(1), 53–59.
Hagenaar, J. (1982). “The use and interpretation of SPT results for the determination of axial bearing capacities of piles driven into carbonate soils and corals.” Proc., European Symp. on Penetration Testing, Balkema, Rotterdam, Netherlands, 51–55.
Hassanlourad, M. (2008). “Triaxial shear behavior of non-cemented and chemically grouted carbonate sands.” Ph.D. thesis, Iran Univ. of Science and Technology, Tehran, Iran.
Hassanlourad, M., Salehzadeh, H., and Shahnazari, H. (2008). “Dilation and particle breakage effects on the shear strength of calcareous sands based on energy aspects.” Int. J. Civ. Eng., 6(2), 108–119.
Hecht-Nielsen, R. (1990). Neurocomputing, Addison-Wesley, Boston.
Jewell, R. J. (1993). “An introduction to calcareous sediments.” Research Rep. No. G1075, Dept. of Civil Engineering, Univ. of Western Australia., Crawley, WA, Australia.
Johari, A., Habibagahi, G., and Ghahramani, A. (2006). “Prediction of soil-water characteristic curve using genetic programming.” J. Geotech. Geoenviron. Eng., 661–665.
Johari, A., Javadi, A. A., and Habibagahi, G. (2011). “Modelling the mechanical behaviour of unsaturated soils using a genetic algorithm-based neural network.” Comput. Geotech., 38(1), 2–13.
Krose, B., and van der Smagt, P. (1996). “Back-propagation.” Chapter 4, An introduction to neural networks, 8th Ed., Univ. of Amsterdam, Amsterdam, Netherlands, 35–36.
Kwag, J. M., Ochiai, H., and Yasufuku, N. (1999). “Yielding stress characteristics of carbonate sand in relation to individual particle fragmentation strength.” Proc., Int. Conf. on Engineering for Calcareous Sediments, Balkema, Rotterdam, Netherlands, 79–86.
Maier, H. R., and Dandy, G. C. (2000). “Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications.” Environ. Model. Softw., 15(1), 101–124.
Maren, A., Harston, C., and Pap, R. (1990). Handbook of neural computing applications, Academic Press, San Diego.
MATLAB R2009a [Computer software]. Natick, MA, MathWorks.
Nelson, M. M., and Illingworth, W. T. (1991). A practical guide to neural nets, Addison-Wesley, Boston.
Noorany, I. (1989). “Classification of marine sediments.” J. Geotech. Engrg., 23–27.
Ong, S. E., Joer, H. A., and Randolph, M. F. (1999). “Frictional behavior in calcareous soils.” Proc., Int. Conf. on Engineering for Calcareous Sediments, Balkema, Rotterdam, Netherlands, 219–228.
Romo, M., García, S., Mendoza, M., and Taboada-Urtuzuástegui, V. (2001). “Recurrent and constructive-algorithm networks for sand behavior modeling.” Int. J. Geomech., 371–387.
Salehzadeh, M. (2000). “The behavior of non-cemented and artificially cemented carbonate sand under monotonic and reversed cyclic shearing.” Ph.D. thesis, Univ. of Manchester, Manchester, U.K.
Samui, P., and Sitharam, T. (2010). “Site characterization model using artificial neural network and kriging.” Int. J. Geomech., 171–180.
Semple, R. (1988). “State of the art report on engineering properties of carbonate soils.” Proc., Int. Conf. on Calcareous Sediments, Balkema, Rotterdam, Netherlands, 807–836.
Zaman, M., Solanki, P., Ebrahimi, A., and White, L. (2010). “Neural network modeling of resilient modulus using routine subgrade soil properties.” Int. J. Geomech., 1–12.
Zurada, J. M. (1992). Introduction to artificial neural systems, West, Eagan, MN.
Information & Authors
Information
Published In
International Journal of Geomechanics
Volume 14 • Issue 1 • February 2014
Pages: 142 - 150
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Dec 30, 2011
Accepted: Feb 22, 2013
Published online: Feb 25, 2013
Published in print: Feb 1, 2014
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