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Simulation of the effects of pozzolanic additives and corrosion inhibitor on the corrosion of reinforced concrete by artificial neural networks

Afshar, A ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. Publisher: Fundatia Serban Solacolu , 2019
  3. Abstract:
  4. In this research, we simulate the corrosive behavior of steel reinforcements on 5 different mixtures to investigate the effect of two powerful protective methods, including pozzolanic additives and corrosion inhibitor on concrete, by artificial neural networks (ANNs). Related to this model, fly ash (FA), micro silica (MS), and slag were used as pozzolanic materials at an optimum 25%, 10%, and 25% of cement weight, respectively. Moreover, Ferrogard 901 as an inhibitor was also utilized. The producer recommends using12 kg/m3 to get the best possible results. The non-linear corrosion of concrete into a marine solution (3.5% NaCl) was simulated by the feed forward back propagation (FFBP) algorithm. Data acquisition happened over a period of 180 days, and according to the ASTM C876 standard for simulating harsh conditions, a period of 10 years was selected as the simulation period. The simulated results all align with collected data. The mixture with 10% of MS has the lowest corrosion current density and corrosion rate at the end of 3600 days, which are 0.38 µA/cm2 and 0.20 mpy, respectively. It provides the best protection against reinforcement corrosion. © 2019, Fundatia Serban Solacolu. All rights reserved
  5. Keywords:
  6. Artificial neural networks ; Corrosion ; Inhibitor ; Pozzolanic concrete ; Simulation
  7. Source: Revista Romana de Materiale/ Romanian Journal of Materials ; Volume 49, Issue 4 , 2019 , Pages 535-543 ; 15833186 (ISSN)
  8. URL: http://solacolu.chim.upb.ro/pg535-543.pdf