Non-destructive investigation of corrosion current density in steel reinforced concrete by artificial neural networks

Archives of Civil and Mechanical Engineering

Volumn 13, Issue 1, 2013, Pages 104-111

  Sadowski, L ^a  

^a WROCLAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Artificial intelligence; Non destructive testing; Polarisation; Resistivity; Steel reinforced concrete

Indexed keywords

CORROSION CURRENT DENSITIES; INSPECTION TECHNIQUE; LINEAR POLARISATION RESISTANCES; NON DESTRUCTIVE TESTING; RESISTIVITY MEASUREMENT; RESISTIVITY METHODS; STEEL REINFORCED CONCRETE; STEEL REINFORCEMENTS;

ARTIFICIAL INTELLIGENCE; CIVIL ENGINEERING; CONCRETE REINFORCEMENTS; CORROSION RATE; CURRENT DENSITY; ELECTRIC CONDUCTIVITY; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; POLARIZATION; REPAIR;

CONCRETES;

EID: 84875794081     PISSN: 16449665     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acme.2012.10.007     Document Type: Article

References (42)

1. Shia X., Xiec N., Fortunea K., Gongd J. Durability of steel reinforced concrete in chloride environments: an overview. Construction and Building Materials 2012, 30:125-138.
2. Blaszczynski T. The influence of crude oil products on RC structure destruction. Journal of Civil Engineering and Management 2011, 17(1):146-156.
3. Melchers R. Modelling immersion corrosion of structural steels in natural fresh and brackish waters. Corrosion Science 2006, 48:4174-4201.
4. Liu J., Lin Y., Li X. Numerical simulation for carbon steel flow-induced corrosion in high-velocity flow seawater. Anti-Corrosion Methods and Materials 2008, 55:66-72.
5. Hajeeh M. Estimating corrosion: a statistical approach. Materials & Design 2003, 24:509-518.
6. Andrade C., Alonso C. Test methods for on-site corrosion rate measurement of steel reinforcement in concrete by means of the polarization resistance method. Materials and Structures 2004, 37:623-643.
7. Millard S. Measuring the corrosion rate of reinforced concrete using linear polarization resistance. Concrete 2003, 36-38.
8. Grantham M., Associates M., Barnet H., Broomfield J. The use of linear polarisation corrosion rate measurements in aiding rehabilitation options for the deck slabs of a reinforced concrete underground car park. Construction and Building Materials 1997, 11-4:215-224.
9. Law D., Millard S., Bungey J. Linear polarisation resistance measurements using a potentiostatically controlled guard ring. NDT&E International 2000, 1:15-21.
10. Wenner F. A method of measuring earth resistivity. Bulletin of the Bureau of Standards 1912, 12:469-478.
11. Angst U., Elsener B., Larsen C., Vennesland O. Chloride induced reinforcement corrosion: rate limiting step of early pitting corrosion. Electrochimica Acta 2011, 56:5877-5889.
12. Hope B., Ip A., Manning D. Corrosion and electrical impedance in concrete. Cement and Concrete Research 1985, 15-3:525-534.
13. Gulikers J. Theoretical considerations on the supposed linear relationship between concrete resistivity and corrosion rate of steel reinforcement. Materials and Corrosion 2005, 56(5):393-403.
14. Morris W., Vico A., Vazquez M., de Sanchez S. Corrosion of reinforcing steel evaluated by means of concrete resistivity measurements. Corrosion Science 2002, 44(1):81-99.
15. Ramezanianpour A., Pilvar A., Mahdikhani M., Moodi F. Practical evaluation of relationship between concrete resistivity, water penetration, rapid chloride penetration and compressive strength. Construction and Building Materials 2011, 25(5):2472-2479.
16. McCarter W., Starrs G., Kandasami S., Jones R., Chrisp M. Electrode configurations for resistivity measurements on concrete. ACI Materials Journal 2009, 106(3):258-264.
17. Schuetze A., Lewis W., Brown C., Geerts W. A laboratory on the four-point probe technique. American Journal of Physics 2004, 72(2):149.
18. Sadowski L. New non-destructive method for linear polarisation resistance corrosion rate measurement. Archives of Civil and Mechanical Engineering 2010, 10(2):109-116.
19. Hola J., Ksiazek M. Research on usability of sulphur polymer composite for corrosion protection of reinforcing steel in concrete. Archives of Civil and Mechanical Engineering 2009, 9(1):47-59.
20. Ksiazek M. The experimental and innovative research on usability of sulphur polymer composite for corrosion protection of reinforcing steel and concrete. Composites. Part B: Engineering 2011, 42(5):1084-1096.
21. Blaszczynski T. Assessment of RC structures influenced by crude oil products. Archives of Civil and Mechanical Engineering 2011, 11(1):5-17.
22. Haykin S. Neural Networks: A Comprehensive Foundation 1999, Prentice Hall.
23. Hola J., Schabowicz K. New technique of nondestructive assessment of concrete strength using artifiligaturecial intelligence. NDT&E International 2005, 38:251-259.
24. Langaros N., Papadrakakis M. Neural network based prediction schemes of the non-linear seismic response of 3D buildings. Advances in Engineering Software 2012, 44:92-115.
25. Kaveh A., Ahangaran M. Discrete cost optimization of composite floor system using social harmony search model. Applied Soft Computing 2012, 12:372-381.
26. Hola B., Schabowicz K. Estimation of earthworks execution time cost by means of artifiligaturecial neural networks. Automation in Construction 2010, 19:570-579.
27. Kappatos V., Chamos A.N., Pantelakis S.G. Assessment of the effect of existing corrosion on the tensile behaviour of magnesium alloy AZ31 using neural networks. Materials & Design 2010, 31:336-342.
28. Shaw M., Millard S., Molyneaux T., Taylor M., Bungey J. Location of steel reinforcement in concrete using ground penetrating radar and neural networks. NDT&E International 2005, 38(3):203-212.
29. Parthiban T., Ravi R., Parthiban G.T., Srinivasan S., Ramakrishnan K.R., Raghavan M. Neural network analysis for corrosion of steel in concrete. Corrosion Science 2005, 47:1625-1642.
30. He S., Zou Y., Quan D., Wang H. Application of RBF neural network and ANFIS on the prediction of corrosion rate of pipeline steel in soil. Recent Advances in Computer Science and Information Engineering, Lecture Notes in Electrical Engineering 2012, 124:639-644.
31. Topçu I., Boǧa A., Hocaoǧlu F. Modelling corrosion currents of reinforced concrete using ANN. Automation in Construction 2009, 18:145-152.
32. Wen Y., Cai C., Liu X., Pei J., Zhu X., Xiao T. Corrosion rate prediction of 3C steel under different seawater environment by using support vector regression. Corrosion Science 2009, 51:349-355.
33. R. Eberhart, Computational intelligence PC tools, in: Proceedings of AP Professional, New York, 1996.
34. Halawa K. A method to improve the performance of multilayer perceptron by utilizing various activation functions in the last hidden layer and the least squares method. Neural Processing Letters 2011, 34(3):293-303.
35. Panchal G., Ganatra A., Kosta P., Panchal D. Behaviour analysis of multilayer perceptrons with multiple hidden neurons and hidden layers. International Journal of Computer Theory and Engineering 2011, 3(2):332-337.
36. Dawson W., Wilby R. An artificial neural network approach to Rainfall-Runoff modelling. Hydrological Sciences Journal 1998, 43(1):47-66.
37. Stigler M. Francis Galton's account of the invention of correlation. Statistical Science 1989, 4(2):73-79.
38. Smith S., Sincich T. Stability over time in the distribution of population forecast errors. Demography 1988, 25:461-474.
39. Rumelhart D., Hinton G., Williams R. Learning representations by back-propagating errors. Nature 1986, 323:533-536.
40. Chien W., Chen L., Wei C., Hsu H., Wang T. Modeling slump flow of high-performance concrete using back-propagation network. Applied Mechanics and Materials 2010, 20(23):838-842.
41. H. Moon, J. Kim, Intelligent crack detecting algorithm on the concrete crack image using neural network, in: Proceedings of the 28th ISARC, Seoul, Korea, 2011, pp. 1461--1467.
42. B. Taylor, M. Darrah, C. Moats, Verification and validation of neural networks: a sampling of research in progress, in: Kevin L. Priddy, Peter J. Angeline (Eds.), Intelligent Computing: Theory and Applications, Proceedings of SPIE 5103 (2003) 8-16.