Neural Network Analysis of Chloride Diffusion in Concrete
Publication: Journal of Materials in Civil Engineering
Volume 14, Issue 4
Abstract
Chloride diffusion is one of the major causes of deterioration of concrete structures. A large amount of research has been conducted to study the chloride diffusion of concrete, both theoretically and experimentally. Because chloride diffusion experiments are time consuming, it is desired to develop a model to predict the chloride profiles in both steady and unsteady states. This paper studies the feasibility of using a neural network as an adaptive synthesizer as well as a predictor to meet such a requirement. The cascade-correlation algorithm is adopted in the present investigation to predict the chloride profiles diffused through concrete specimens. It is found that the predictions given by the cascade-correlation algorithm are in good agreement with the test results in both steady and unsteady states. The cascade-correlation algorithm can also synthesize an appropriate architecture and train the network simultaneously. It has the potential of becoming an effective tool in the prediction of durability problems. The investigation results demonstrate that the addition of fly ash and microsilica improves the resistance of mixtures to chloride diffusion. However, the addition of calcium nitrite solution degrades the improvement caused by the incorporation of these mineral admixtures, so calcium nitrite should be used in practical engineering with caution.
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References
Berke, N. S., Pfeifer, D. W., and Weil, T. G.(1988). “Protection against chloride-induced corrosion.” Concr. Int.: Des. Constr., 10(11), 45–56.
Brown, R. D.(1982). “Design prediction of the life of reinforced concrete in marine and other chloride environments.” Durability Build. Mat., 1, 113–125.
Buenfeld, N. R., and Newman, J. B.(1987). “Examination of three methods for studying ion diffusion in cement pastes, mortars, and concrete.” Mater. Struct., 20, 3–10.
Cabrera, G. J. (1985). “Use of pulverized fuel ash to produce durable concrete.” Improvement of concrete durability, Thomas Telford, London, 29–57.
Cheu, R. L., Ritchie, S. G., Recker, W. W., and Bavarian, B. (1991). “Investigation of a neural network model for freeway incident detection.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp Press, Oxford, U.K., 1, 267–274.
Crank, J. (1983). The mathematics of diffusion, Clarendon, Oxford, U.K.
El-Dieb, A. S., and Hooton, R. D.(1994). “Evaluation of the Katz-Thompson model for estimating the water permeability of cement-based materials from mercury intrusion porosimetry data.” Cem. Concr. Res., 24(3), 443–455.
Fahlman, S. E., and Lebiere, C. (1990). “The cascade-correlation learning architecture.” Rep. CMU-CS-90-100, Carnegie Mellon Univ., Pittsburgh.
Frey, R., Balogh, T., and Balazs, G. L.(1994). “Kinetic method to analyse chloride diffusion in various concretes.” Cem. Concr. Res., 24(5), 863–873.
Furuta, H., Suglura, K., Tonegawa, T., and Wanatabe, E. (1991). “A neural network system for aesthetic design of dam structures.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp, Oxford, U.K., 2, 273–278.
Hajela, B., Fu, B., and Berke, L. (1991). “ART networks in automated conceptual design of structural systems.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp, Oxford, U.K., 2, 263–271.
Kamarthi, S. V., Sanvido, V. E., and Kumara, S. R. T.(1992). “Neuroform–neural network system for vertical formwork selection.” J. Comput. Civ. Eng., 6(6), 178–199.
Karunanithi, N., Grenney, W. J., Whitley, D., and Bovee, K.(1994). “Neural networks for river flow prediction.” J. Comput. Civ. Eng., 8(2), 201–220.
Karunanithi, N., Whitley, D., and Malaiya, Y. K.(1992a). “Prediction of software reliability using connectionist models.” IEEE Trans. Software Eng., 18(7), 563–574.
Karunanithi, N., Whitley, D., and Malaiya, Y. K.(1992b). “Using neural network in reliability predictions.” IEEE Software, 9(4), 53–59.
Li, Z., Peng, J., Ma, B.(1999). “Investigation of chloride diffusion for high-performance concrete containing fly ash, microsilica, and chemical admixtures.” ACI Mater. J., 96(3), 391–396.
Lippmann, R. P.(1987). “An introduction to computing with neural nets.” IEEE ASSP Magazine, 4(2), 4–22.
Mangat, P. S., and Molloy, B. T.(1992). “Factors influencing chloride-induced corrosion of reinforcement in concrete.” Mater. Struct., 25, 404–411.
Mangat, P. S., and Molloy, B. T.(1994a). “Prediction of long term chloride concentrations in concrete.” Mater. Struct., 27, 338–346.
Mangat, P. S., and Molloy, B. T.(1994b). “Prediction of free chloride concentration in concrete using routine inspection data.” Mag. Concr. Res., 46, 279–287.
Marsh, B. K., Day, R. L., and Bonner, D. G.(1985). “Pore structure characteristics affecting the permeability of cement paste containing fly ash.” Cem. Concr. Res., 15, 1027–1038.
Moselhi, O., Hagazy, T., and Fazio, P. (1991). “Markup estimation using AI methodology.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp Press, Oxford, U.K., 1, 257–266.
Nagataki, S., and Ujike, I. (1986). “Air permeability of concrete mixed with fly ash and condensed silica fume.” Proc., 2nd Int. Conf. on the Use of Fly Ash, Blast Furnace Slag, and Silica Fume in Concrete, Madrid, 2, 1049–1068.
Ozyildirim, C. (1988). “Experimental installation of a concrete bridge-deck overlay containing silica fume.” Transportation Research Record 1204, Transportation Research Board, Washington, D.C., 36–41.
Ramirez, M. R., and Arghya, D. (1991). “A faster learning algorithm for BP neural networks in NDE application.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp, Oxford, U.K., 1, 275–283
Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986). “Learning internal representations by error propagation.” Parallel distribution processing, Vol. 1, D. E. Rumelhart and J. MacClellend, eds., MIT Press, Cambridge, Mass.
Saetta, A. V., Scotta, R. V., and Vitaliani, R. V.(1993). “Analysis of chloride diffusion into partially saturated concrete.” ACI Mater. J., 90(5), 441–451.
Saricimen, H., Maslehuddin, M., Abdulhamid, J. A.-T., and Al-Mana, A.(1995). “Permeability and durability of plain and blended cement concretes cured in field and laboratory conditions.” ACI Mater. J., 92(2), 111–116.
Shiyuan, H. (1981). “Hydration of fly ash cement and microstructure of fly ash cement paste.” Rep. No. Fo.2.81, Swedish Cement and Concrete Research Institute, Stockholm.
Tumidajski, P. J., and Chan, G. W.(1996). “Boltzmann-Matano analysis of chloride diffusion into blended cement concrete.” J. Mater. Civ. Eng., 8(4), 195–200.
Tumidajski, P. J., Chan, G. W., Feldman, R. F., and Strathdee, G.(1995). “A Boltzmann-Matano analysis of chloride diffusion.” Cement and Concr., 25, 1556–1566.
Xihui, L., Baocheng, S., and Wenyuan, F. (1991). “Fuzzy reasoning with engineering application using neural networks.” Proc., 2nd Int. Conf. on Applicability of AI to Civil and Structural Engineering, B. H. V. Topping, ed., Civil-Comp, Oxford, U.K., 2, 279–285.
Weigend, A. S., Huberman, B. A., and Rumelhart, D. E.(1990). “Predicting the future: a connectionist approach.” Int. J. Neural Syst., 1, 193–209.
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Published In
Journal of Materials in Civil Engineering
Volume 14 • Issue 4 • August 2002
Pages: 327 - 333
Copyright
Copyright © 2002 American Society of Civil Engineers.
History
Received: Feb 24, 1999
Accepted: Jul 12, 2000
Published online: Jul 15, 2002
Published in print: Aug 2002
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