Analysis Technique for Chloride Behavior Using Apparent Diffusion Coefficient of Chloride Ion from Neural Network Algorithm

Abstract

Evaluation of chloride penetration is very important, because induced chloride ion causes corrosion in embedded steel. Diffusion coefficient obtained from rapid chloride penetration test is currently used, however this method cannot provide a correct prediction of chloride content since it shows only ion migration velocity in electrical field. Apparent diffusion coefficient of chloride ion based on simple Fick's Law can provide a total chloride penetration magnitude to engineers. This study proposes an analysis technique to predict chloride penetration using apparent diffusion coefficient of chloride ion from neural network (NN) algorithm and time-dependent diffusion phenomena. For this work, thirty mix proportions with the related diffusion coefficients are studied. The components of mix proportions such as w/b ratio, unit content of cement, slag, fly ash, silica fume, and fine/coarse aggregate are selected as neurons, then learning for apparent diffusion coefficient is trained. Considering time-dependent diffusion coefficient based on Fick's Law, the technique for chloride penetration analysis is proposed. The applicability of the technique is verified through test results from short, long term submerged test, and field investigations. The proposed technique can be improved through NN learning-training based on the acquisition of various mix proportions and the related diffusion coefficients of chloride ion.

Strength and Resistance to Chloride Penetration in Concrete Containing GGBFS with Ages

“…그러나 장기간의 실험기간과 질산은 적정에 따른 실험오차 가 많이 문제시 되므로 RCPT (Rapid Chloride Penetration Test) 와 같은 전기영동실험을 통하여 자유염소 이온의 전기장 내 의 속도를 평가하는 방법이 많이 사용되고 있다. 18,19) 촉진확 산계수를 이용하여 염화물 침투를 해석하기 위해서는 자유 염화물과 고정염화물과의 상평형과 확산, 침투, 흡착을 고 려한 해석 프레임이 필요하지만, [5][6][7]20)…”