Limitations of FEM modelling of chloride diffusion when considering different parameters of binary and ternary concrete mixtures

• Autorzy: Lehner Petr , Hornakova Marie , Konecny Petr

Identyfikatory

DOI

10.17512/bozpe.2020.2.07

• Języki publikacji: EN

Abstrakty

EN

The numerical modelling of chloride diffusion in concrete structures requires an appropriate description of input parameters. The main inputs for the model are the diffusion coefficient of concrete and derived aging factor. The model itself can be susceptible to the values of these parameters because of the size of the finite elements and size of the time step. Due to the potential use in probabilistic calculations, which requires millions of simulations, it is desirable to create a highly optimized model. It is important to pay attention to the accuracy of the calculation, but also to its calculation time. The presented results show the possible limits of the finite element model of the diffusion in a concrete structure. This is demonstrated on the reference ordinary Portland cement mixture and 32 various binary and ternary concrete mixtures, which show a significant effect of different diffusion coefficients and aging factors on the overall convergence. This study provides guidance on which extreme material parameters, out of the potential range, may adversely affect model results.

Słowa kluczowe

EN

numerical analysis; chlorine; concrete; high-performance concrete; binary mixtures; ternary mixtures

PL

analiza numeryczna; chlor; beton; beton wysokiej wytrzymałości; mieszanki binarne; mieszanki trójskładnikowe

• Wydawca: Wydawnictwo Politechniki Częstochowskiej
• Czasopismo: Budownictwo o Zoptymalizowanym Potencjale Energetycznym
• Rocznik: 2020
• Tom: Vol. 9 Nr 2
• Strony: 61--69
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Lehner Petr

• VSB-Technical University of Ostrava

autor

Hornakova Marie

• VSB-Technical University of Ostrava

autor

Konecny Petr

• VSB-Technical University of Ostrava

Bibliografia

• 1.Bitaraf, M. & Mohammadi, S. (2008) Analysis of chloride diffusion in concrete structures for prediction of initiation time of corrosion using a new meshless approach. Construction and Building Materials, 22(4), 546-556. doi: 10.1016/j.conbuildmat.2006.11.005.
• 2.FIB (2013) Interface Characteristics, fib Model Code for Concrete Structures 2010, 152-189. doi: 10.1002/9783433604090.ch6.
• 3.Ghosh, P. et al. (2017) Probabilistic time-dependent sensitivity analysis of HPC bridge deck exposed to chlorides. Computers and Concrete, 19(3), 305-313. doi: 10.12989/cac.2017.19.3.305.
• 4.Ghosh, P., Hammond, A. & Tikalsky, P.J. (2011) Prediction of equivalent steady-state chloride diffusion coefficients. ACI Materials Journal, 108(1), 88-94.
• 5.Ghosh, P. & Tran, Q. (2015) Correlation between bulk and surface resistivity of concrete. International Journal of Concrete Structures and Materials, 9(1), 119-132. doi: 10.1007/s40069-014-0094-z.
• 6.Glass, G.K. & Buenfeld, N.R. (1997) The presentation of the chloride threshold level for corrosion of steel in concrete. Corrosion Science. doi: 10.1016/S0010-938X(97)00009-7.
• 7.Han, S.-H. (2007) Influence of diffusion coefficient on chloride ion penetration of concrete structure. Construction and Building Materials, 21(2), 370-378. doi: 10.1016/J.CONBUILDMAT.2005.08.011.
• 8.Hooton, R. (2012) Life-365. Service Life Prediction Model and Computer Program for Predicting the Service Life and Life-Cycle Cost of Reinforced Concrete Exposed to Chlorides, Life-365 User Manual, 1-80.
• 9.Janas, P., Krejsa, M. & Krejsa, V. (2009) Structural reliability assessment using a direct determined probabilistic calculation. Proceedings of the Twelfth International Conference on Civil. Structural and Environmental Engineering Computing. doi: 10.4203/ccp.91.72.
• 10.Konečný, P. et al. (2020) Comparison of procedures for the evaluation of time dependent concrete diffusion coefficient model. Construction and Building Materials, 258, 119535. doi: 10.1016/ j.conbuildmat.2020.119535.
• 11.Konecny, P. & Lehner, P. (2017) Effect of cracking and randomness of inputs on corrosion initiation of reinforced concrete bridge decks exposed to chlorides. Frattura ed Integrita Strutturale, 11(39), 29-37. doi: 10.3221/IGF-ESIS.39.04.
• 12.Lehner, P., Ghosh, P. & Konečný, P. (2018) Statistical analysis of time dependent variation of diffusion coefficient for various binary and ternary based concrete mixtures. Construction and Building Materials, 183, 75-87. doi: 10.1016/j.conbuildmat.2018.06.048.
• 13.Lehner, P. & Konečný, P. (2015) Analysis of durability of high performance and ordinary concrete mixtures with respect to chlorides. Applied Mechanics and Materials, 769, 281-284. doi: 10.4028/www.scientific.net/amm.769.281.
• 14.Lehner, P. & Konečný, P. (2019) Effect of different concrete material parameters on the accuracy of FEM model of diffusion. AIP Conference Proceedings, 120015. doi: 10.1063/1.5114117.
• 15.Lehner, P. & Konečnỳ, P. (2016) Probabilistic durability evaluation of binary and ternary concrete mixtures considering aging effect. ARPN Journal of Engineering and Applied Sciences, 11(3), 1992-1997.
• 16.Lehner, P., Konečný, P. & Brožovský, J. (2016) Optimization of time step and finite elements on the model of diffusion of chlorides. ARPN Journal of Engineering and Applied Sciences, 11(3), 2083-2088.
• 17.Mangat, P.S. & Molloy, B.T. (1994) Prediction of long term chloride concentration in concrete. Materials and Structures, 27(6), 338-346. doi: 10.1007/BF02473426.
• 18.Marsavina, L. et al. (2009) Experimental and numerical determination of the chloride penetration in cracked concrete. Construction and Building Materials, 23(1), 264-274. doi: 10.1016/j.conbuildmat.2007.12.015.
• 19.Martı́n-Pérez, B. et al. (2000) A study of the effect of chloride binding on service life predictions. Cement and Concrete Research. Pergamon, 30(8), 1215-1223. doi: 10.1016/S0008-8846(00)00339-2.
• 20.Stewart, M.G. & Rosowsky, D.V. (1998) Time-dependent reliability of deteriorating reinforced concrete bridge decks. Structural Safety, 20(1), 91-109. doi: 10.1016/S0167-4730(97)00021-0.
• 21.Sun, Y. et al. (2018) A new mixture design methodology based on the packing density theory for high performance concrete in bridge engineering. Construction and Building Materials, 182, 80-93. doi: 10.1016/J.CONBUILDMAT.2018.06.062.
• 22.Teplý, B. & Podroužek, J. (2017) Service life, reliability and their role in the life cycle analysis of concrete structures. Advances in Environmental Research, 55, 47-63.
• 23.Teplý, B. & Vořechovská, D. (2012) Reinforcement corrosion: Limit states, reliability and modelling. Journal of Advanced Concrete Technology, 10(11), 353-362. doi: 10.3151/jact.353.
• 24.Thomas, M.D.A. & Bamforth, P.B. (1999) Modelling chloride diffusion in concrete effect of fly ash and slag. Cement and Concrete Research, 29(4), 487-495. doi: 10.1016/S0008-8846(98)00192-6.
• 25.Tikalsky, P.J., Pustka, D. & Marek, P. (2005) Statistical variations in chloride diffusion in concrete bridges. ACI Structural Journal, 102(3), 481-486. doi: 10.14359/14420.
• 26.Vořechovská, D. et al. (2009) Modeling of chloride concentration effect on reinforcement corrosion. Computer-Aided Civil and Infrastructure Engineering, 24(6), 446-458. doi: 10.1111/j.1467-8667.2009.00602.x.
• 27.Yao, L. et al. (2016) Prediction of chloride diffusion in concrete structure using meshless methods. Advances in Materials Science and Engineering, 2016. doi: 10.1155/2016/3824835.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).