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Dehvari, Abdol Ghaium, khazaei, mohsen, sohrabi, mohammad reza, miri, mahmood. (1400). Probabilistic Optimum Percentage of Recycled Aggregates Contaminated with Chloride Ion in Concrete Mix. نشریه مهندسی عمران امیرکبیر, 5(3), 521-540. doi: 10.22060/ajce.2022.20699.5774
Abdol Ghaium Dehvari; mohsen khazaei; mohammad reza sohrabi; mahmood miri. "Probabilistic Optimum Percentage of Recycled Aggregates Contaminated with Chloride Ion in Concrete Mix". نشریه مهندسی عمران امیرکبیر, 5, 3, 1400, 521-540. doi: 10.22060/ajce.2022.20699.5774
Dehvari, Abdol Ghaium, khazaei, mohsen, sohrabi, mohammad reza, miri, mahmood. (1400). 'Probabilistic Optimum Percentage of Recycled Aggregates Contaminated with Chloride Ion in Concrete Mix', نشریه مهندسی عمران امیرکبیر, 5(3), pp. 521-540. doi: 10.22060/ajce.2022.20699.5774
Dehvari, Abdol Ghaium, khazaei, mohsen, sohrabi, mohammad reza, miri, mahmood. Probabilistic Optimum Percentage of Recycled Aggregates Contaminated with Chloride Ion in Concrete Mix. نشریه مهندسی عمران امیرکبیر, 1400; 5(3): 521-540. doi: 10.22060/ajce.2022.20699.5774

Probabilistic Optimum Percentage of Recycled Aggregates Contaminated with Chloride Ion in Concrete Mix

AUT Journal of Civil Engineering
مقاله 12، دوره 5، شماره 3، آذر 2021، صفحه 521-540    اصل مقاله (3.72 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/ajce.2022.20699.5774
نویسندگان
Abdol Ghaium Dehvari1؛ mohsen khazaei* 2؛ mohammad reza sohrabi3؛ mahmood miri3
1Department of Civil Engineering, University of Velayat, Iranshahr, Iran.
2Department of Civil Engineering, Quchan University of Technology, Quchan, Iran.
3Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran.
چکیده
This paper studies the analysis of probabilistic service life in reinforced concrete structures exposed to chloride penetration and concrete made with recycled aggregate. Therefore, by modeling this procedure, the corrosion process can be better evaluated as well as the structural durability. In this study, such durability properties of concrete samples namely electrical resistance as corrosion and diffusion evaluation indicators are experimented. The prediction models for durability parameters of concrete is obtained by using the neural network, namely Group Method of Data Handling and linear regression first, then these models are evaluated by using a simple and fast usability new method of probability evaluation, and eventually, the probabilistic values of using recycled aggregates with and without chloride ion pre-contamination and probability of failure in specific service life for achieving an environmentally friendly concrete are calculated. Probabilistic evaluation results reveal that for service lifetime of 25 years in a highly corrosive environment with the humidity of 70%, the temperature of 23 °C and aggregates chloride ion pre-contamination percentage of 3%, 5%, 8%, 10% and with adding 10% silica fume, using of recycled aggregates for above different chloride ion pre-contamination is limited to (100%, 46.60%), (100%, 34.57%), (100%, 16.69%) and (32.72%, 1.20%) for recycled coarse and fine aggregates, respectively. Also, it is concluded that in the mean value of recycled aggregate (50%, 50%) and aggregates chloride ion pre-contamination percentage of 5% and target reliability index "β" _"t" "=3.0" , the time to corrosion initiate is achieved about "t" _"i" "=22(year)" .
کلیدواژه‌ها
Recycled aggregates؛ Electrical resistance؛ Chloride diffusion coefficient؛ Neural network؛ Probability evaluation
مراجع
  1. C.Liang, Z.M.Ye, F. Vernerey, Y. Xi, Development of processing methods to improve strength of concrete with 100% recycled coarse aggregate, Materials in Civil Engineering, 27(2013).
  2. Pellegrino, F. Faleschini, Sustainability improvements in the concrete industry, use of recycled materials for structural concrete production, Springer 2016.
  3. Vázquez, Progress of recycling in the built environment, final report of the RILEM Technical Committee 217-PRE (Springer Science & Business Media, 8(2012).
  4. Biglarijoo, M. Nili, S.M. Hosseinian, M. Razmara, S.Ahmadi, P.Razmara, Modelling and optimization of concrete containing recycled concrete aggregate and waste glass,  Magazine of Concrete Research, 69(2017), 306-316.
  5. G.Li, J.Zhu, A.H.Huang, A.K.H. Kwan, L.J. Li, Combined effects of micro-silica and nano-silica on durability of mortar, Construction and Building Materials, 157(2017), 337-347.
  6. Dilbas, M.Şimşek, O.Çakır, An investigation on mechanical and physical properties of recycled aggregate concrete (RAC) with and without silica fume, Construction and Building materials, 61(2014), 50-59.
  7. R Nokken, R.D. Hooton, Electrical Conductivity Testing”, American Concrete International, 28 (2006), 58-63.
  8. Layssi, P. Ghods, A.R. Alizadeh, M.Salehi, Electrical resistivity of concrete, Concrete International, 37(2015), 41-46.
  9. Azarsa, R.Gupta, Electrical resistivity of concrete for durability evaluation, Advances in Materials Science and Engineering, 2017.
  10. Jalal, A.R. Pouladkhan, H. Norouzi, Choubdar, Chloride penetration, water absorption and electrical resistivity of high performance concrete containing nano silica and silica fume, American science, 8(2012), 278-284.
  11. C.Hou, Y.M.Su, Y.R.Chen, P.J.Chen, Effects of coarse aggregates on the electrical resistivity of Portland cement concrete, Construction and Building Materials, 133(2017), 397-408.
  12. A.Medeiros-Junior, M.G.Lima, Electrical resistivity of unsaturated concrete using different types of cement, Construction and Building Materials, 107(2017), 11-16.
  13. Yu, L.Yang, M.Wu, B.Li, Practical model for predicting corrosion rate of steel reinforcement in concrete structures, Construction and Building Materials, 54(2014), 385-401.
  14. Yu, J.Liu, Z.Chen, Probabilistic evaluation method for corrosion risk of steel reinforcement based on concrete resistivity, Construction and Building Materials, 138(2017), 101-113.
  15. G.Ivakhnenko, Polynomial theory of complex systems. IEEE transactions on Systems, Man Cybernetics, 4(1971), 364-378.
  16. J. Farlow, The GMDH algorithm of Ivakhnenko, The American Statistician, 35(1981), 210-215.
  17. B.Nezhad, M.Miri, M.R.Ghasemi, New neural network-based response surface method for reliability analysis of structures, Neural Computing and Applications, 31(2019), 777-791.
  18. Ebtehaj, H. Bonakdari, F. Khoshbin, C. Bong, H. Joo, A. Ab Ghani, Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular stormwater channel, Scientia Iranica, 24(2017), 1000-1009.
  19. Rashki, M. Miri, M.A. Moghaddam, A new efficient simulation method to approximate the probability of failure and most probable point, Structural Safety, 39(2012), 22-29.
  20. Rashki, M.Miri, M.A. Moghaddam, A simulation-based method for reliability based design optimization problems with highly nonlinear constraints, Automation in Construction, 47(2014), 24-36.
  21. Zych, Test methods of concrete resistance to chloride ingress, Czasopismo Techniczne, 2015.
  22. G.Nogueira, E.D. Leonel, Probabilistic models applied to safety assessment of reinforced concrete structures subjected to chloride ingress, Engineering Failure Analysis, 31(2013), 76-89.
  23. Saassouh, Z. Lounis, Probabilistic modeling of chloride-induced corrosion in concrete structures using first-and second-order reliability methods, Cement and Concrete Composites, 34(2012), 1082-1093.
  24. Elfmarkova, P. Spiesz, H.J.H. Brouwers, Determination of the chloride diffusion coefficient in blended cement mortars”. Cement and Concrete Research, 78(2015), 190-199.
  25. Konečný, P.Lehner, T. Ponikiewski, P. Miera, Comparison of chloride diffusion coefficient evaluation based on electrochemical methods, Procedia Engineering, 190(2017), 193-198.
  26. Deutschen Instituts für Normung, Aggregates for concrete and mortar—part 100: recycled aggregates, Germany, 4226, 2002.
  27. ASTM C 29/C 29M-97. Standard Test Method for Bulk Density (“Unit Weight”) and Voids in Aggregate.
  28. ASTM C 127-04. Standard Test Method for Density, Relative Density (Specific Gravity), and Absorption of Coarse Aggregate.
  29. ASTM C 128-04a. Standard Test Method for Density, Relative Density (Specific Gravity), and Absorption of Fine Aggregate.
  30. ASTM C 1240-12, Standard Specification for Silica Fume Used in Cementitious Mixtures.
  31. ASTM C 33- 01, Standard Specification for Concrete Aggregates.
  32. ASTM C 39/C 39M-05, Standard Test Method for Compressive Strength of Cylindrical Concrete Specimens.
  33. ASTM C 1760-12, Standard Test Method for Bulk Electrical Conductivity of Hardened Concrete.
  34. T.Build, 492–Nordtest method, Concrete, mortar and cement-based repair materials: Chloride migration coefficient from non-steady-state migration experiments. Finland: NORDTEST, 1999.
  35. B.Polder, Test methods for on-site measurement of resistivity of concrete—a RILEM TC-154 technical recommendation, Construction and building materials, 15(2001), 125-13.
  36. Thomas, R. J., Properties and Performance of Alkali-Activated Concrete, Ph.D. Thesis, Clarkson University, Department of Civil Engineering, Potsdam NY, 2016.
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