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A Probabilistic Prediction Method of Reinforcement Corrosion Rate in Concrete
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A steel bar corrosion and probability prediction technology, applied in complex mathematical operations, design optimization/simulation, calculation, etc., can solve problems such as the inability to consider the influence of ambient temperature steel bar corrosion rate and the inability to describe the probability distribution characteristics of concrete steel bar corrosion rate
Active Publication Date: 2020-07-07
GUANGXI UNIV
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[0009] In a dissertation titled "Research on the Corrosion Mechanism and Practical Prediction Model of Corrosion Rate of Reinforcement in Concrete" published by Wu Ming in 2013, the water-cement ratio of concrete, the content of chloride ions and the relative humidity of the air were used as control parameters to establish a A deterministic empirical prediction model for the corrosion rate of steel bars, but the influence of ambient temperature on the corrosion rate of steel bars cannot be considered
[0010] The above-mentioned deterministic empirical prediction model of the corrosion rate of steel bars in concrete is determined based on the least squaresregression analysis, which can only guarantee the overall optimal prediction results in the sense of mean value, and cannot describe the probability distribution characteristics of the corrosion rate of steel bars in concrete
However, due to the randomness of the raw materials of concrete, the distribution of internal defects and pores in concrete, and the spatial distribution of steel bars, the corrosion rate of steel bars in concrete often has significant randomness under the same material parameters and environmental conditions.
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Embodiment 1
[0040] This example is to utilize the present invention to determine the probability prediction value of steel bar corrosion rate in concrete, and carry out the specific example of comparative analysis with the calculated value of traditional deterministic empirical prediction model and the measured value of steel bar corrosion rate, comprise the following steps:
[0041] (1) Generate random sample points of probability model parameters:
[0042] Determining the probabilistic model parameters θ i (i=1,2,…,6) probability distribution type, mean, standard deviation and correlation coefficient, as shown in Table 1:
[0043] Table 1θ i (i=1,2,...,6) probability distribution type, mean standard deviation and correlation coefficient
[0044]
[0045] According to the probability model parameters θ in Table 1 i (i=1,2,…,6) probability distribution type, mean, standard deviation and correlation coefficient, use Monte Carlo method for random sampling, each probability model p...
Embodiment 2
[0057] This example is a concrete example of determining a probabilistic predictor of the corrosion rate of reinforcement in concrete and involves the following steps:
[0058] (1) Generate random sample points of probability model parameters:
[0059] Determining the probabilistic model parameters θ i (i=1,2,…,6) probability distribution type, mean, standard deviation and correlation coefficient, as shown in Table 1. According to the probability model parameters θ in Table 1 i (i=1,2,…,6) probability distribution type, mean, standard deviation and correlation coefficient, use Monte Carlo method for random sampling, each probability model parameter θ i (i=1,2,...,)6 generate n random sample points θ ij (i=1,2,...,6; j=1,2,...,n). The number of samples in this example is selected as n=10000. Probabilistic model parameter θ 1 , θ 2 , θ 3 , θ 4 , θ 5 , θ 6 The respective 10,000 random sample points are as follows Figure 1 to Figure 6 shown; using the probability mode...
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Abstract
The invention discloses a probability prediction method for reinforcing bar corrosion rate of concrete. The method includes steps: (1) generating random sample points of probability model parameters; (2) calculating random sample points of the reinforcing bar corrosion rate; (3) calculating mean value and standard deviation of the reinforcing bar corrosion rate. According to the method, the mean value and the standard deviation of the reinforcing bar corrosion rate in the concrete can be determined according to water-cement ratio and chlorineion content of the concrete and temperature and relative humidity of environments of concrete structures, probability distribution characteristics of the reinforcing bar corrosion rate in the concrete can be reasonably described, prediction accuracy of a traditional deterministic empirical prediction model can be calibrated, so that the method overcomes the shortcoming that the traditional deterministic empirical prediction model cannot describe the probability distribution characteristics of the reinforcing bar corrosion rate of the concrete.
Description
technical field [0001] The invention relates to a method for predicting the corrosion rate of steel bars in concrete, in particular to a probabilistic prediction method for the corrosion rate of steel bars in concrete. Background technique [0002] Affected by concrete carbonation and chlorideionerosion, steel reinforcement corrosion often occurs in in-service reinforced concrete structures, resulting in durability degradation. Since the corrosion rate of steel bars is a key parameter that determines the durability degradation of reinforced concrete structures, the analysis and prediction of steel bar corrosion rates are of great significance for the service life evaluation and maintenance and reinforcement decisions of reinforced concrete structures in service. [0003] Chinese patent application 201010253580.7 discloses an on-line corrosion detector and method for reinforced concrete, using a detector device consisting of a disc electrode, a polarization loop and a curre...
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