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Concrete Mix Design for Service Life of RC Structures under Carbonation Using Genetic Algorithm

机译:基于遗传算法的碳化混凝土结构使用寿命的混凝土配合比设计。

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Steel corrosion in reinforced concrete (RC) structure is such a critical problem to structural safety that many researches have been performed for maintaining required performance during intended service life. This paper is for a numerical technique for obtaining optimum concrete mix proportions through genetic algorithm (GA) for RC structures under carbonation which is considered as a serious deterioration in underground sites and big cities. For this study, mix proportions and CO2diffusion coefficients are analyzed through the previous studies, and then the fitness function of CO2diffusion coefficient is derived through regression analysis. The fitness function from 69 test results includes 5 variables of mix proportions such as w/c (water to cement) ratio, cement content, sand content percentage, coarse aggregate content, and R.H. (relative humidity). Through GA technique, simulated mix proportions are obtained for 12 cases of verification and they show reasonable results with average relative error of 4.6%. Assuming intended service life and design parameters, intended CO2diffusion coefficients and cement contents are determined and then related mix proportions are simulated. The proposed technique can provide initial concrete mix proportions which satisfy service life under carbonation.
机译:钢筋混凝土(RC)结构中的钢腐蚀是结构安全的关键问题,因此进行了许多研究,以在预期使用寿命内保持所需的性能。本文是一种数值技术,它通过遗传算法(GA)获得碳化下钢筋混凝土结构的最佳混凝土配合比,这被认为是地下场所和大城市的严重恶化。在本研究中,通过先前的研究分析了混合比例和CO2扩散系数,然后通过回归分析得出了CO2扩散系数的适应度函数。来自69个测试结果的适应度函数包括5个混合比例变量,例如w / c(水与水泥)比,水泥含量,砂含量百分比,粗骨料含量和R.H.(相对湿度)。通过遗传算法,获得了12个验证案例的模拟混合比例,它们显示出合理的结果,平均相对误差为4.6%。假设预期的使用寿命和设计参数,确定预期的CO2扩散系数和水泥含量,然后模拟相关的配合比。所提出的技术可以提供满足碳化条件下使用寿命的初始混凝土配合比。

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