Simulation of corrosion protection methods in reinforced concrete by artificial neural networks and fuzzy logic

Abstract

In this study, the effect of protection methods regarding the corrosion decrement of steel in concrete was simulated by artificial neural networks (ANNs) and fuzzy logic (FL) approaches. Hot dip galvanizing as a protective coating, Ferrogard 901 corrosion inhibitor, a pozzolanic component, such as fly ash (FA) and micro-silica (MS), and eventually rebar AISI-304 were employed in concrete. Reinforced concrete samples were held under impres­sed voltage of 30 V in 3.5 % NaCl electrolyte for 350 hours toward a stainless-steel auxiliary electrode. Corrosion currents have been modelled using feed forward back propa­gation ANNs and FL methods. The results demonstrate good consistency between cor­rosion data and simulated models. Furthermore, the correlation coefficient criterion clearly indicates using pozzolanic materials, with a combination of MS and FA, can be introduced as one of the best corrosion protection methods, with a 35 % contribution factor in reinforced concrete.

Making a Case for Hybrid GFRP-Steel Reinforcement System in Concrete Beams: An Overview

“…The diffusive travel of corrodents is resisted by the concrete cover, typically taken to be 30-50 mm. In several studies [49][50][51][52][53][54], corrosion damage has been reported to be responsible for the reductions in service life and the ultimate capability of RC structures. Consequently, the construction industry, seeking solutions to this durabi in steel RCs, has been considering methods for the corrosion protection of ments.…”