Method and system for predicting fatigue life of rusted steel bar

Abstract

The invention discloses a method and system for predicting the fatigue life of a rusted steel bar, and the method comprises the steps: considering the influence of a physical field factor on the crack propagation of the steel bar, and constructing a fatigue life prediction correction factor; performing nonlinear regression fitting on the fatigue life prediction correction factor to obtain an expression of the correction factor; setting the expression of the correction factor as a correction item to the Paris formula to form a corrected Paris formula; and performing integral processing on the corrected Paris formula to obtain a fatigue life prediction model. According to the method, the accuracy and applicability of steel bar corrosion fatigue life prediction can be remarkably improved.

Description

Technical Field

[0001] The invention relates to the field of material corrosion, and in particular to a fatigue life prediction method and system for corroded steel bars. Background Art

[0002] Steel bars are widely used in concrete structures such as bridges, buildings and tunnels. They are important core load-bearing components in structures and have advantages such as high strength and high durability. However, steel bars are very susceptible to corrosion due to long-term exposure to complex natural environments, especially in coastal or marine environments with high humidity and salt content. Corrosion will form pitting holes on the surface of the steel bars, leading to local stress concentration and accelerating the initiation and expansion of fatigue cracks in the steel bars.

[0003] At present, the fatigue life of steel bars is mainly predicted by the Pairs formula proposed in the BS7910 specification, but the Pairs formula does not specifically consider the influence of parameters such as temperature, humidity, and corrosion rate on the crack propagation of steel bars, resulting in low prediction accuracy and difficulty in meeting actual engineering needs. Therefore, in order to solve the above problems, a fatigue life prediction method and system for corroded steel bars is needed, which can significantly improve the accuracy and applicability of steel bar corrosion fatigue life prediction. Summary of the invention

[0004] In view of this, the purpose of the present invention is to overcome the defects in the prior art and provide a fatigue life prediction method and system for corroded steel bars, which can significantly improve the accuracy and applicability of steel bar fatigue life prediction.

[0005] The fatigue life prediction method of corroded steel bars of the present invention comprises:

[0006] Considering the influence of physical field factors on the crack growth of steel bars, fatigue life prediction correction factors are constructed;

[0007] Perform nonlinear regression fitting on fatigue life prediction correction factor to obtain the expression of correction factor;

[0008] The expression of the correction factor is set as a correction term to the Paris formula to form a corrected Paris formula;

[0009] The modified Paris formula is integrated to obtain the fatigue life prediction model.

[0010] Furthermore, the fatigue life prediction correction factor is: f(T,H,C r ), where f(·) is the correction factor function, T is temperature, H is humidity, C r is the corrosion rate.

[0011] Furthermore, nonlinear regression fitting is performed on the fatigue life prediction correction factor, including:

[0012] Setting the correction factor to the Paris formula, we get the following improved formula:

[0013] in, is the crack growth rate; the values ​​of C and m are 1×10 6 and 3; ΔK is the range of stress intensity factor variation, Δσ is the stress amplitude, a is the crack length; f(T,H,C r ) is the correction factor;

[0014] Carry out salt spray corrosion test to determine and the value of ΔK, we get f(T,H,C r ) under different test conditions, and obtain the value of f(T,H,C r ) The corresponding values ​​of temperature, humidity and corrosion rate;

[0015] Taking temperature, humidity and corrosion rate as independent variables, f(T,H,C r ) is the dependent variable, and nonlinear regression fitting is performed to obtain the expression of the correction factor:

[0016]

[0017] Furthermore, the modified Paris formula is determined according to the following formula:

[0018]

[0019] Furthermore, the fatigue life prediction model is determined according to the following formula:

[0020]

[0021] Where N is the predicted fatigue life; a0 is the crack initiation threshold, a c is the fracture threshold of the crack; the crack initiation threshold a0 follows a normal distribution with a mean of 0.1 mm and a variance of 0.03 mm; the fracture threshold a c The value is (d3-λ0,d3+λ0), d is the diameter of the steel bar, and λ0 is the fluctuation threshold.

[0022] A fatigue life prediction system for corroded steel bars, comprising a correction factor unit and a life prediction unit;

[0023] The correction factor unit is used to consider the influence of physical field factors on the crack propagation of steel bars and construct a fatigue life prediction correction factor; perform nonlinear regression fitting on the fatigue life prediction correction factor to obtain an expression of the correction factor;

[0024] The life prediction unit is used to set the expression of the correction factor as a correction term to the Paris formula to form a corrected Paris formula; and perform integration processing on the corrected Paris formula to obtain a fatigue life prediction model.

[0025] Furthermore, the fatigue life prediction correction factor is: f(T,H,C r ), where f(·) is the correction factor function, T is temperature, H is humidity, C r is the corrosion rate.

[0026] Furthermore, nonlinear regression fitting is performed on the fatigue life prediction correction factor, including:

[0027] Setting the correction factor to the Paris formula, we get the following improved formula:

[0028] in, is the crack growth rate; the values ​​of C and m are 1×10 6 and 3; ΔK is the range of stress intensity factor variation, Δσ is the stress amplitude, a is the crack length; f(T,H,C r ) is the correction factor;

[0029] Carry out salt spray corrosion test to determine and the value of ΔK, we get f(T,H,C r ) under different test conditions, and obtain the value of f(T,H,C r ) The corresponding values ​​of temperature, humidity and corrosion rate;

[0030] Taking temperature, humidity and corrosion rate as independent variables, f(T,H,C r ) is the dependent variable, and nonlinear regression fitting is performed to obtain the expression of the correction factor:

[0031]

[0032] Furthermore, the modified Paris formula is determined according to the following formula:

[0033]

[0034] Furthermore, the fatigue life prediction model is determined according to the following formula:

[0035]

[0036] Where N is the predicted fatigue life; a0 is the crack initiation threshold, a cis the fracture threshold of the crack; the crack initiation threshold a0 follows a normal distribution with a mean of 0.1 mm and a variance of 0.03 mm; the fracture threshold a c The value is (d3-λ0,d3+λ0), d is the diameter of the steel bar, and λ0 is the fluctuation threshold.

[0037] The beneficial effects of the present invention are as follows: a method and system for predicting the fatigue life of corroded steel bars disclosed in the present invention introduces an environmental correction term into the traditional Paris formula, comprehensively considers the influence of multi-physical field factors such as temperature, humidity, corrosion rate, etc. on the expansion of steel bar cracks, makes the prediction result more in line with the complex conditions in the actual service environment, significantly improves the accuracy of steel bar corrosion fatigue life prediction, and provides more reliable technical support for the safety and durability assessment of civil engineering structures such as bridges, buildings and tunnels. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0039] Figure 1 It is a schematic flow chart of the fatigue life prediction method of the present invention;

[0040] Figure 2 It is a schematic diagram for comparing the corrosion fatigue life of the steel bars of the present invention. DETAILED DESCRIPTION

[0041] The present invention is further described below in conjunction with the accompanying drawings, as shown in the drawings:

[0042] This embodiment discloses a method for predicting fatigue life of corroded steel bars, comprising the following steps:

[0043] Considering the influence of physical field factors on the crack growth of steel bars, fatigue life prediction correction factors are constructed;

[0044] Perform nonlinear regression fitting on fatigue life prediction correction factor to obtain the expression of correction factor;

[0045] The expression of the correction factor is set as a correction term to the Paris formula to form a corrected Paris formula;

[0046] The modified Paris formula is integrated to obtain the fatigue life prediction model.

[0047] In this embodiment, the physical field factors include temperature, humidity and corrosion rate. By introducing physical field factors, the influence of multiple physical fields on the crack growth law of steel bars can be more comprehensively considered, thereby improving the accuracy and applicability of structural fatigue life prediction.

[0048] The fatigue life prediction correction factor is: f(T,H,C r), where f(·) is the correction factor function, T is temperature, H is humidity, C r is the corrosion rate. By setting the correction factor, it is used to analyze the influence of temperature, humidity and corrosion rate on the crack growth law of steel bars.

[0049] In this embodiment, nonlinear regression fitting is performed on the fatigue life prediction correction factor, specifically including:

[0050] Setting the correction factor to the Paris formula, we get the following improved formula:

[0051] Among them, the is the Paris formula;

[0052] is the crack growth rate. The values ​​of C and m can be obtained from experiments or set by the specification. Here they are 1×10 6 and 3, ΔK is the range of stress intensity factor variation, Δσ is the stress amplitude, a is the crack length, and π is 3.14; f(T,H,C r ) is the correction factor;

[0053] Conduct salt spray corrosion tests to determine crack growth rates and the value of stress intensity factor variation range ΔK, we can get f(T,H,C r ) under different test conditions, and obtain the value of f(T,H,C r ) The corresponding values ​​of temperature, humidity and corrosion rate;

[0054] Taking temperature, humidity and corrosion rate as independent variables, f(T,H,C r ) is the dependent variable, and nonlinear regression fitting is performed, such as polynomial regression or neural network regression, to obtain the expression of the correction factor:

[0055]

[0056] In this embodiment, the expression of the correction factor is set as a correction term to the Paris formula, and the corrected Paris formula is determined according to the following formula:

[0057]

[0058] In this embodiment, the modified Paris formula is integrated to determine the fatigue life prediction model according to the following formula:

[0059]

[0060] Where N is the predicted fatigue life; a0 is the crack initiation threshold, a c is the fracture threshold of the crack; the crack initiation threshold a0 follows a normal distribution with a mean of 0.1 mm and a variance of 0.03 mm; the fracture threshold a c The value is (d3-λ0, d3+λ0), where d is the steel bar diameter and λ0 is the fluctuation threshold. The fluctuation threshold can be set according to actual working conditions, for example, the value can be 0.

[0061] The present invention also relates to a fatigue life prediction system for corroded steel bars. The prediction system corresponds to the prediction method of the above embodiment and can be understood as a system for implementing the above prediction method. The system includes a correction factor unit and a life prediction unit.

[0062] The correction factor unit is used to consider the influence of physical field factors on the crack propagation of steel bars and construct a fatigue life prediction correction factor; perform nonlinear regression fitting on the fatigue life prediction correction factor to obtain an expression of the correction factor;

[0063] The life prediction unit is used to set the expression of the correction factor as a correction term to the Paris formula to form a corrected Paris formula; and perform integration processing on the corrected Paris formula to obtain a fatigue life prediction model.

[0064] In order to verify the accuracy of the prediction of the present invention, the corrosion fatigue life of the steel bars was tested by a fatigue testing machine after the steel bars were corroded under different working conditions, and compared with the calculation results of the fatigue life prediction model of the present invention. The results are shown in the figure. Figure 2 The results show that the prediction results of the model of the present invention are consistent with the test results of the test machine, indicating that the prediction model proposed by the present invention has high accuracy.

[0065] The present invention provides an objective and scientific fatigue life prediction method and system for corroded steel bars, improves the traditional Paris formula, fully considers the influence of multi-physical field factors on the crack propagation law of steel bars, and constructs a new fatigue life prediction model, which can more accurately evaluate the fatigue life of steel bars in actual service environments and improve the applicability of steel bar fatigue life prediction.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for predicting fatigue life of corroded steel bars, characterized in that: include: Considering the influence of physical field factors on the crack growth of steel bars, fatigue life prediction correction factors are constructed; Perform nonlinear regression fitting on fatigue life prediction correction factor to obtain the expression of correction factor; The expression of the correction factor is set as a correction term to the Paris formula to form a corrected Paris formula; The modified Paris formula is integrated to obtain the fatigue life prediction model.

2. The fatigue life prediction method of corroded steel bars according to claim 1, characterized in that: The fatigue life prediction correction factor is: f(T,H,C r ), where f(·) is the correction factor function, T is temperature, H is humidity, C r is the corrosion rate.

3. The fatigue life prediction method of corroded steel bars according to claim 1, characterized in that: The fatigue life prediction correction factor is fitted with nonlinear regression, including: Setting the correction factor to the Paris formula, we get the following improved formula: in, is the crack growth rate; the values ​​of C and m are 1×10 6 and 3; ΔK is the range of stress intensity factor variation, Δσ is the stress amplitude, a is the crack length; f(T,H,C r ) is the correction factor; Carry out salt spray corrosion test to determine and the value of ΔK, we get f(T,H,C r ) under different test conditions, and obtain the value of f(T,H,C r ) The corresponding values ​​of temperature, humidity and corrosion rate; Taking temperature, humidity and corrosion rate as independent variables, f(T,H,C r ) is the dependent variable, and nonlinear regression fitting is performed to obtain the expression of the correction factor:

4. The fatigue life prediction method of corroded steel bars according to claim 1, characterized in that: The modified Paris formula is determined according to the following formula:

5. The fatigue life prediction method of corroded steel bars according to claim 1, characterized in that: The fatigue life prediction model is determined according to the following formula: Where N is the predicted fatigue life; a0 is the crack initiation threshold, a c is the fracture threshold of the crack; the crack initiation threshold a0 follows a normal distribution with a mean of 0.1 mm and a variance of 0.03 mm; the fracture threshold a c The value is (d3-λ0,d3+λ0), d is the diameter of the steel bar, and λ0 is the fluctuation threshold.

6. A fatigue life prediction system for corroded steel bars, characterized in that: Includes correction factor unit and life prediction unit; The correction factor unit is used to consider the influence of physical field factors on the crack propagation of steel bars and construct a fatigue life prediction correction factor; Perform nonlinear regression fitting on fatigue life prediction correction factor to obtain the expression of correction factor; The life prediction unit is used to set the expression of the correction factor as a correction term to the Paris formula to form a corrected Paris formula; The modified Paris formula is integrated to obtain the fatigue life prediction model.

7. The fatigue life prediction system of corroded steel bars according to claim 6, characterized in that: The fatigue life prediction correction factor is: f(T,H,C r ), where f(·) is the correction factor function, T is temperature, H is humidity, C r is the corrosion rate.

8. The fatigue life prediction system of corroded steel bars according to claim 6, characterized in that: The fatigue life prediction correction factor is fitted with nonlinear regression, including: Setting the correction factor to the Paris formula, we get the following improved formula: in, is the crack growth rate; the values ​​of C and m are 1×10 6 and 3; ΔK is the range of stress intensity factor variation, Δσ is the stress amplitude, a is the crack length; f(T,H,C r ) is the correction factor; Carry out salt spray corrosion test to determine and the value of ΔK, we get f(T,H,C r ) under different test conditions, and obtain the value of f(T,H,C r ) The corresponding values ​​of temperature, humidity and corrosion rate; Taking temperature, humidity and corrosion rate as independent variables, f(T,H,C r ) is the dependent variable, and nonlinear regression fitting is performed to obtain the expression of the correction factor:

9. The fatigue life prediction system of corroded steel bars according to claim 6, characterized in that: The modified Paris formula is determined according to the following formula:

10. The fatigue life prediction system of corroded steel bars according to claim 6, characterized in that: The fatigue life prediction model is determined according to the following formula: Where N is the predicted fatigue life; a0 is the crack initiation threshold, a c is the fracture threshold of the crack; the crack initiation threshold a0 follows a normal distribution with a mean of 0.1 mm and a variance of 0.03 mm; the fracture threshold a c The value is (d3-λ0,d3+λ0), d is the diameter of the steel bar, and λ0 is the fluctuation threshold.

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