Analysis Technique for Chloride Behavior Using Apparent Diffusion Coefficient of Chloride Ion from Neural Network Algorithm

신경망 이론을 이용한 염소이온 겉보기 확산계수 추정 및 이를 이용한 염화물 해석

  • 이학수 (한남대학교 건설시스템공학과) ;
  • 권성준 (한남대학교 건설시스템공학과)
  • Received : 2012.04.24
  • Accepted : 2012.06.18
  • Published : 2012.08.31


Evaluation of chloride penetration is very important, because induced chloride ion causes corrosion in embedded steel. Diffusion coefficient obtained from rapid chloride penetration test is currently used, however this method cannot provide a correct prediction of chloride content since it shows only ion migration velocity in electrical field. Apparent diffusion coefficient of chloride ion based on simple Fick's Law can provide a total chloride penetration magnitude to engineers. This study proposes an analysis technique to predict chloride penetration using apparent diffusion coefficient of chloride ion from neural network (NN) algorithm and time-dependent diffusion phenomena. For this work, thirty mix proportions with the related diffusion coefficients are studied. The components of mix proportions such as w/b ratio, unit content of cement, slag, fly ash, silica fume, and fine/coarse aggregate are selected as neurons, then learning for apparent diffusion coefficient is trained. Considering time-dependent diffusion coefficient based on Fick's Law, the technique for chloride penetration analysis is proposed. The applicability of the technique is verified through test results from short, long term submerged test, and field investigations. The proposed technique can be improved through NN learning-training based on the acquisition of various mix proportions and the related diffusion coefficients of chloride ion.


  1. Broomfield, J. P., "Corrosion of Steel in Concrete: Understanding," Investigation and Repair, London, E&FN, 1997, pp. 1-15.
  2. RILEM, "Durability Design of Concrete Structures," Report of RILEM Technical Committee 130-CSL, E&FN, 1994, pp. 28-52.
  3. Thomas, M. D. A. and Bentz, E. C., Computer Program for Predicting the Service Life and Life-Cycle Costs of Reinforced Concrete Exposed to Chlorides, Life365 Manual, SFA, 2002, pp. 12-56.
  4. CEB-FIP, Model Code for Service Life Design, The International Federation for Structural Concrete (fib), Task Group 5.6, 2006, pp. 16-33.
  5. Song, H. W., Pack, S. W., Lee, C. H., and Kwon, S. J., "Service Life Prediction of Concrete Structures under Marine Environment Considering Coupled Deterioration," Journal of Restoration of Building and Monument, Vol. 12, No. 1, 2006, pp. 265-284.
  6. Maekawa, K., Ishida, T., and Kishi, T., "Multi-Scale Modeling of Concrete Performance," Journal of Advanced Concrete Technology, Vol. 1, No. 2, 2003, pp. 91-126.
  7. 송하원, 권성준, 변근주, 박찬규, "혼화재를 사용한 고성능 콘크리트의 배합특성을 고려한 염화물 확산 해석기법에 관한 연구," 대한토목학회 논문집, 25권, 1A호, 2005, pp. 213-223.
  8. Kwon, S. J., Na, U. J., Park, S. S., and Jung, S. H., "Service Life Prediction of Concrete Wharves with Early-Aged Crack: Probabilistic Approach for Chloride Diffusion," Structural Safety, Vol. 31, No. 1, 2009, pp. 75-83.
  9. Park, S. S., Kwon, S. J., Jung, S. H., and Lee, S. W., "Modeling of Water Permeability in Early Aged Concrete with Cracks Based on Micro Pore Structure," Construction and Building Materials, Vol. 27, No. 1, 2012, pp. 597-604.
  10. Park, S. S., Kwon, S. J., and Jung, S. H., "Analysis Technique for Chloride Penetration in Cracked Concrete Using Equivalent Diffusion and Permeation," Construction and Building Materials, Vol. 29, No. 2, 2012, pp. 183-192.
  11. Tang, L., "Electrically Accelerated Methods for Determining Chloride Diffusivity in Concrete-Current Development," Magazine of Concrete Research, Vol. 48, No. 176, 1996, pp. 173-179.
  12. NORDTEST, Chloride Migration Coefficient from Non- Steady-State Migration Experiments, NT BUILD 492, 1999, pp. 1-11.
  13. Maekawa, K., Ishida, T., and Kishi, T., Multi-Scale Modeling of Structural Concrete, Tylor & Francis, London and Newyork, 1st Ed., 2009, pp. 291-352.
  14. Thomas, M. D. A. and Bamforth, P. B., "Modeling Chloride Diffusion in Concrete: Effect of Fly Ash and Slag," Cement and Concrete Research, Vol. 29, No. 4, 1999, pp. 487-495.
  15. 양승일, 윤영수, 이승훈, 김규동, "신경망을 이용한 고성능 콘크리트의 배합설계," 한국콘크리트학회 봄 학술대회, 14권, 1호, 2002, pp. 545-550.
  16. 오주원, 이종원, 이인원, "콘크리트 배합설계에 있어서 신경망의 이용," 콘크리트 학회지, 9권, 2호, 1997, pp. 145-151.
  17. Wang, J. Z., Ni, H. G., and He, J. Y., "The Application of Automatic Acquisition of Knowledge to Mix Design of Concrete," Cement and Concrete Research, Vol. 29, No. 12, 1999, pp. 1875-1880.
  18. Yeh, I. C., "Modeling of Strength of High-Performance Concrete Using Artificial Neural Networks," Cement and Concrete Research, Vol. 28, No. 12, 1988, pp. 1797-1808.
  19. Stegemann, J. A. and Buenfeld, N. R., "Prediction of Unconfined Compressive Strength of Cement Paste with Pure Metal Compound Additions," Cement and Concrete Research, Vol. 32, No. 6, 2002, pp. 903-913.
  20. Park, K. B., Noguchi, T., and Plawsky, J., "Modeling of Hydration Reactions Using Neural Networks to Predict the Average Properties of Cement Paste," Cement and Concrete Research, Vol. 35, No. 9, 2005, pp. 1676-1684.
  21. Song, H. W. and Kwon, S. J., "Evaluation of Chloride Penetration in High Performance Concrete Using Neural Network Algorithm and Micro Pore Structure," Cement and Concrete Research, Vol. 39, No. 9, 2009, pp. 814-824.
  22. 권성준, 송하원, 변근주, 박찬규, "신경망 이론과 마이크로 모델링을 통한 혼화재를 사용한 콘크리트의 염화물 침투해석," 대한토목학회 논문집, 27권, 1A호, 2007, pp. 117-129.
  23. 권성준, 송하원, 변근주, "인공신경망을 통한 확산계수의 도출과 공극구조변화를 고려한 콘크리트 탄산화 해석," 대한토목학회 논문집, 27권, 1A호, 2007, pp. 107-116.
  24. 삼성건설 기술 연구소, 고내구성 콘크리트의 염소이온 확산특성 평가, 2003, pp. 17-68
  25. McCulloch, W. and Pitt, W., "A Logical Calaulus of the Ideas Immanent," Bulletin of Mathematical Biophysics 5, 1943, pp. 115-133.
  26. Kwon, S. J. and Song, H. W., "Analysis of Carbonation Behavior in Concrete Using Neural Network Algorithm and Carbonation Modeling," Cement and Concrete Research, Vol. 40, No. 1, 2010, pp. 119-127.
  27. Demuth, H. and Beagle, M., Neural Network Toolbox for Use with MATLAB, ver. 4, The MathWorks, 2002, pp. 21-85.
  28. Jang, S. Y., "Modeling of Chloride Transport and Carbonation in Concrete and Prediction of Service Life of Concrete Structures Considering Corrosion of Steel Reinforcement," Ph. D. Dissertation, Dept. of Civil Engineering, Seoul National University, Korea, 2003, pp. 32-48.
  29. Poulsen, E., On a Model of Chloride Ingress into Concrete, Nordic Miniseminar, Chloride Transport, Building Materials, Chalmers University of Technology, Gothenburg, 1993, pp. 1-8.
  30. 한국레미콘 공업협회, 콘크리트의 배합설계, 2005, pp. 319-330.

Cited by

  1. Evaluation of Chloride Penetration in Concrete with Ground Granulated Blast Furnace Slag considering Fineness and Replacement Ratio vol.1, pp.1, 2013,
  2. Analysis Technique for Chloride Penetration in High Performance Concrete Behavior Considering Time-Dependent Accelerated Chloride Diffusivity vol.25, pp.2, 2013,
  3. Experimental Study on the Relationship between Time-Dependent Chloride Diffusion Coefficient and Compressive Strength vol.24, pp.6, 2012,