Issue 45

X. Z. Wang, Frattura ed Integrità Strutturale, 45 (2018) 100-107; DOI: 10.3221/IGF-ESIS.45.08 104 bars(mm 2 ); S 1 —sectional area after failure(mm 2 ). Select the strength standard value of the steel bar as its initial strength that is ky y f f , 0  (17) The safety factor is 1.2, so that the strength damage threshold of the steel bar is: 2.1/ ' y ys f f  (18) When other factors are not considered, the sectional area of steel bars has not changed, S 0 =S 1 . Substituting formula (17) and formula (18) into formula (16), the threshold value of bearing capacity loss rate is calculated to be 16.67%. In the case of corrosion, not only the sectional area of steel will decrease, but also the yield strength will decrease. When the corrosion rate of steel bar is greater than 10% and less than 60%, the yield strength before and after corrosion has the following relations: ky, s s ys 1 1.028 0.985 f ρ ρ f    (19) In the formula, f ys —yield strength of corroded steel bars: f y,k —yield strength of steel bar before corrosion: ρ s —cross sectional loss rate of steel bar. Substituting formula (19) into formula (16), the following formula can be obtained. s 0 ky, 1 ys 0 ky, 1.028 0.015 Δ ρ S f Sf S f P P     (20) When the loss rate threshold value of bearing capacity is 16.67%, the corresponding steel section loss rate is obtained by formula (20), and it is 14.76%. Because the test steel is completely immersed in water, it is considered that the corrosion of steel bar is overall and uniform, and the weight loss rate is linear with the cross-section loss rate of steel bar. Thus, the weight loss rate of the steel bar is 14.76%, which is used as the threshold value of the grey prediction data sequence. Feasibility test of the grey prediction According to the characteristics of MATLAB, two file functions are compiled, namely GREYCCH and GREYNUM, and their basic algorithms are the same. GREYCCH is used to judge the feasibility of modeling, and GREYNUM is used to sequence grey prediction. The data sequence for the GM (1,1) model under different corrosion conditions is shown in Tab. 2. When the absolute value of the development coefficient is less than or equal to 0.3, it is feasible to predict the weight loss rate of anchor specimens in the medium and long term by GM (1,1) model. In order to further verify the feasibility of grey prediction by using the corrosion test data of steel bars, the first part of the original data sequence is used as the modeling data, and the rest of the experimental data is used as prediction and verification. The results are shown in Tab. 3, the first 8 sets of data were used to predict the latter 3 sets of data, the predicted value and the actual value are relatively close, and the error is small. It shows that the grey prediction method is feasible and has high confidence. Results and analysis of grey prediction With the weight loss rate as the prediction sequence, the parameters, test indexes and prediction results of the model are shown in Tab. 4. (1) From the parameters of GM (1,1) model, it can be seen that the absolute values of the development coefficient are much less than 0.3, which shows that the model can be used for medium and long-term prediction. At the same time, the average precision of the model is more than 0.95, and the maximum deviation of the average class ratio is only 0.0373, which meets the requirements of modeling and the accuracy of the model is higher. (2) From the comparison between the prediction curve and the original data points (as shown in Fig. 2-5), it can be seen that the prediction curve passes through the original data points and then develops upwards, and the development trend