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Probability Distribution of Cross-sectional radius of Corroded Steel Bars in Concrete and Its application

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The impress current method is applied to acquire corroded steel bars embedded in concrete, and three-dimensional(3D) laser scanning techniques are applied on corroded steel bars to obtain the cross-sectional radius of corroded steel bars. Statistical analysis shows that with the increase of corrosion degree, the variation of radius of corroded steel bars increases linearly. For different types of steel bars, plain round steel bars have a larger sensitivity to corrosion than ribbed ones. Original radius of steel bars and mixture proportion of concrete have negligible effect on the variability of radius of corroded steel bars. A normal distribution model is obtained to describe radius data of corroded steel bars. For the convenience of practical application, the indicator,R, which is the ratio of the average to the minimum cross-sectional areas of corroded steel bars, is introduced to quantify the longitudinal variation of the cross-sectional areas. By using Monte-Carlo simulation, the indicator, R, of corroded steel bars are achieved based on the probability distribution of radius. The indicator R can be fitted well by the Gumbel distribution, and the distribution parameters increase linearly with the increases of corrosion degree.
Title: Probability Distribution of Cross-sectional radius of Corroded Steel Bars in Concrete and Its application
Description:
The impress current method is applied to acquire corroded steel bars embedded in concrete, and three-dimensional(3D) laser scanning techniques are applied on corroded steel bars to obtain the cross-sectional radius of corroded steel bars.
Statistical analysis shows that with the increase of corrosion degree, the variation of radius of corroded steel bars increases linearly.
For different types of steel bars, plain round steel bars have a larger sensitivity to corrosion than ribbed ones.
Original radius of steel bars and mixture proportion of concrete have negligible effect on the variability of radius of corroded steel bars.
A normal distribution model is obtained to describe radius data of corroded steel bars.
For the convenience of practical application, the indicator,R, which is the ratio of the average to the minimum cross-sectional areas of corroded steel bars, is introduced to quantify the longitudinal variation of the cross-sectional areas.
By using Monte-Carlo simulation, the indicator, R, of corroded steel bars are achieved based on the probability distribution of radius.
The indicator R can be fitted well by the Gumbel distribution, and the distribution parameters increase linearly with the increases of corrosion degree.

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