A prediction method for electrochemical corrosion resistance of laser shock strengthened zirconium alloy

Abstract

A method for predicting the electrochemical corrosion resistance of a laser shock strengthened zirconium alloy relates to the technical field of metal surface treatment, and comprises the following steps: determining experimental parameters affecting the electrochemical corrosion resistance of an alloy material, carrying out a laser shock strengthening orthogonal test with the experimental parameters as factors on an alloy sample, pretreating the alloy sample, measuring a potentiodynamic polarization curve of the alloy sample after the laser shock strengthening orthogonal test, establishing a prediction model according to the potentiodynamic polarization result of the alloy sample and the laser shock strengthening orthogonal test result, and using the prediction model to predict the electrochemical corrosion resistance of the alloy under different parameter conditions; the method for predicting the electrochemical corrosion resistance of a laser shock strengthened zirconium alloy in the present invention can be used to study the changing law of the electrochemical corrosion resistance of the zirconium alloy after laser shock strengthening, obtain the optimal parameters of the electrochemical corrosion resistance, reduce the time and cost of the experiment, and improve the efficiency of the experiment.

Description

Technical Field

[0001] The invention relates to the technical field of metal surface treatment, and in particular to a method for predicting the electrochemical corrosion resistance of a laser shock strengthened zirconium alloy. Background Art

[0002] Zirconium alloy is the first line of defense to prevent the leakage and spread of radioactive materials in nuclear reactors. During its service, it is exposed to extreme environments such as high radiation, high temperature, high pressure and high concentration of corrosive media for a long time. This may cause the oxide film on the surface of the zirconium alloy to be destroyed, and electrochemical reactions may occur with oxidants, impurities in the reactor coolant and gases produced by fuel fission, leading to corrosion failure, huge economic losses and serious public safety accidents.

[0003] Laser shock peening technology is a new type of surface modification technology. It uses a high-energy short-pulse laser beam to act on the surface of the material. The low-melting-point material absorbs the laser energy and then undergoes explosive gasification, generating high-temperature and high-pressure plasma. These plasmas expand in a very short time, forming shock waves that act on the surface of the material, causing plastic deformation of the material surface. Plastic deformation will produce a high strain rate, leading to dislocation proliferation, lattice distortion and other phenomena, inducing the formation of greater hardness and residual compressive stress, thereby achieving surface modification of the material, which can effectively improve the electrochemical corrosion resistance of the material surface.

[0004] In current scientific research and actual production and processing, there is a serious lack of understanding of the changing laws of the electrochemical corrosion resistance of zirconium alloys after laser shock strengthening. Understanding the changes in its electrochemical corrosion resistance and the optimal processing parameters often requires a lot of experimental comparisons, resulting in a waste of experimental costs, time and resources. By predicting the electrochemical corrosion resistance of zirconium alloys after laser shock strengthening, its performance and process design can be more effectively optimized, and appropriate process parameters can be selected to meet the requirements of electrochemical corrosion resistance, reduce the risk of failure caused by corrosion, and reduce the cost of experiments and production. Summary of the invention

[0005] In view of this, the main purpose of the present invention is to provide a method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy, accurately and efficiently realize the study on the changing law of the electrochemical corrosion resistance of zirconium alloy after laser shock, and effectively save experimental costs.

[0006] The present invention provides a method for predicting the electrochemical corrosion resistance of a laser shock strengthened zirconium alloy, comprising the following steps:

[0007] Step S1: determining experimental parameters that affect the electrochemical corrosion resistance of the alloy material, wherein the experimental parameters include laser energy, spot diameter, pulse overlap rate and scanning times;

[0008] Step S2: performing an orthogonal laser shock strengthening test on the alloy sample with experimental parameters as factors;

[0009] Step S3: pre-treating the alloy sample obtained in step S2, and measuring the potentiodynamic polarization curve of the alloy sample after the laser shock strengthening orthogonal test;

[0010] Step S4: A prediction model is established based on the potentiodynamic polarization results of the alloy sample and the laser shock strengthening orthogonal test results, and the prediction model is used to predict the electrochemical corrosion resistance of the alloy under different parameter conditions.

[0011] An implementation of the present invention is that, in the experimental parameters, the laser energy ranges from 20 to 200 mJ, the spot diameter ranges from 0.2 to 1.0 mm, the pulse overlap rate ranges from 25 to 75%, and the number of scans ranges from 1 to 5 times.

[0012] One embodiment of the present invention is that the laser shock peening orthogonal test is a four-factor three-level orthogonal test L9(3 4 ).

[0013] One embodiment of the present invention is that in the orthogonal test of laser shock strengthening, the processing surface of the alloy sample is consistent with the surface level of the fixture, and the height of the processing surface of the alloy sample from the laser nozzle is 9 mm.

[0014] An embodiment of the present invention is that the pretreatment includes ultrasonic cleaning and immersion in a corrosive solution performed sequentially.

[0015] Furthermore, the ultrasonic cleaning process is to use anhydrous ethanol to ultrasonically clean the alloy sample for 15 to 20 minutes.

[0016] Furthermore, the corrosion solution immersion process is to prepare a composite solution with a boric acid concentration of 1200 mg / L and a lithium hydroxide concentration of 2.2 mg / L to prepare a corrosion solution, and immerse the alloy sample after ultrasonic cleaning for 3 to 5 hours.

[0017] One implementation of the present invention is that the method for establishing a prediction model is:

[0018] S1: Taking the experimental parameters as independent variables and the corrosion current density in the potentiodynamic polarization curve as the dependent variable, a prediction model as shown in formula (1) is established:

[0019] i corr =β0+β1·Le+β2·Sd+β3·Po+β4·St (1)

[0020] In formula (1), i corris the corrosion current density of zirconium alloy; Le is the laser energy in the experimental parameters; Sd is the spot diameter in the experimental parameters; Po is the pulse overlap rate in the experimental parameters; St is the number of scans in the experimental parameters; β0, β1, β2, β3, β4 are the correlation coefficients in the regression equation obtained after multivariate linear regression fitting of the corresponding experimental parameters and the corrosion current density;

[0021] S2: Calculate the loss function L of the prediction model and evaluate the model complexity, and perform regularization on the prediction model that does not meet the requirements;

[0022] S3: Use analysis software to calculate the correlation coefficient in the prediction model in matrix form to obtain the prediction model result, where the prediction model calculation expression is shown in formula (3):

[0023] AK=B (3)

[0024] In formula (3), A is the experimental parameter matrix; K is the correlation coefficient matrix; B is the corrosion current density result matrix;

[0025] By solving the augmented matrix A|B, we can obtain the optimal correlation coefficients β0, β1, β2, β3, and β4 for prediction, and substitute the correlation coefficients into formula (1) to obtain the prediction model results.

[0026] The technical effects of the present invention are:

[0027] The present invention provides a prediction method for the electrochemical corrosion resistance of laser shock strengthened zirconium alloy, which can be used to study the change law of the electrochemical corrosion resistance of zirconium alloy after laser shock strengthening, adjust and optimize the selected laser shock strengthening parameters within the credible error range of the model, and obtain the optimal parameters of the electrochemical corrosion resistance, thereby reducing the time and cost of the experiment, improving the efficiency of the experiment, improving the work efficiency and the quality of laser shock strengthening, and can be further used to improve the electrochemical corrosion resistance of zirconium alloy and reduce the occurrence of nuclear power safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is the laser shock peening system and schematic diagram of the present invention;

[0029] Figure 2 is a flowchart of the steps of establishing a prediction model in the present invention;

[0030] Figure 3 It is a potentiodynamic polarization curve diagram of the zirconium alloy after laser shock strengthening of the orthogonal test group for establishing the prediction model in the present invention;

[0031] Figure 4 It is a potentiodynamic polarization curve diagram of the zirconium alloy after laser shock strengthening, which is a supplementary experimental group used to verify the prediction error accuracy of the prediction model in the present invention;

[0032] Figure 1 In the figure, 1-test sample fixture, 2-operation interface, 3-ultrapure water reservoir, 4-laser, 5-nozzle, 6-test sample, 7-lifting platform. DETAILED DESCRIPTION

[0033] The present invention will be further described in detail below in conjunction with the embodiments.

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. The described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example:

[0036] like Figure 2 As shown, the present invention provides a method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy, which mainly includes the following steps:

[0037] Step S1: determining the experimental parameters that affect the electrochemical corrosion resistance of the alloy material, wherein the experimental parameters include laser energy Le, spot diameter Sd, pulse overlap rate Po, and scanning times St;

[0038] According to relevant literature and public databases, the laser shock peening parameters and their characteristic data that affect the electrochemical corrosion resistance of materials were collected. It was concluded that the laser shock peening parameters that mainly affect the electrochemical corrosion resistance of materials are the above four parameters, so they are used as subsequent experimental parameters.

[0039] Step S2: performing an orthogonal laser shock strengthening test on the alloy sample with experimental parameters as factors;

[0040] Laser shock peening orthogonal test passed Figure 1 The device shown in the figure is used. Before designing the orthogonal test, it is necessary to determine the appropriate range of processing parameters. Appropriate laser energy Le (mJ), spot diameter Sd (mm), pulse overlap rate Po (%), and number of scans St can form a uniform and dense oxide film on the surface of the zirconium alloy, thereby improving the electrochemical corrosion resistance. The laser energy Le is determined to be in the range of 20 to 200 mJ, the spot diameter Sd is in the range of 0.2 to 1.0 mm, the pulse overlap rate Po is in the range of 25 to 75%, and the number of scans St is in the range of 1 to 5 times.

[0041] In order to ensure that the diameter of the spot processed on the sample surface after laser focusing is consistent with the set size, the height of the processed surface of the test sample from the laser nozzle is set to 9 mm.

[0042] In the two-level factor orthogonal test, the effect diagram is linearly distributed, which is not conducive to a comprehensive analysis of the entire test results. Although the high-level factors above the fourth level may provide more detailed information, the distribution of their effect diagrams is more complex, which is not conducive to intuitive analysis and finding the best parameters. At the same time, the high level will increase the number and complexity of the test, and the number of tests required will also increase significantly, resulting in an increase in test costs and test cycles, and reducing test efficiency. Therefore, under the condition of ensuring sufficient information, the principle of minimizing the number of experiments and covering the selected parameter range as much as possible is adopted. The three-level design is selected for the experiment affecting the electrochemical corrosion resistance of zirconium alloy, that is, the four-factor three-level orthogonal test L9(3 4 ), the laser energy Le is 30, 80, 120 mJ, the spot diameter Sd is 0.4, 0.6, 0.8 mm, the pulse overlap rate Po is 25, 50, 75%, and the number of scans St is 1, 3, 5 times, as shown in Table 1:

[0043] Table 1 Orthogonal test parameter range

[0044] level Le(mJ) Sd(mm) Pb(%) St 1 30 0.4 25 1 2 80 0.6 50 3 3 120 0.8 75 5

[0045] Based on the above parameters, the orthogonal test designed is shown in Table 2:

[0046] Table 2 Orthogonal test table

[0047]

[0048]

[0049] Step S3: Pre-treat the alloy samples after the orthogonal test obtained in step S2, and measure the potentiodynamic polarization curves of the alloy samples after the orthogonal test respectively. The pre-treatment includes ultrasonic cleaning and corrosive solution immersion in sequence. The ultrasonic cleaning process uses anhydrous ethanol to ultrasonically clean the alloy samples for 20 minutes. The corrosive solution immersion process uses a composite solution with a boric acid content of 1200 mg / L and a lithium hydroxide content of 2.2 mg / L to immerse the alloy samples after ultrasonic cleaning for 4 hours. Then, the electrochemical workstation is used to measure the potentiodynamic polarization curve of the sample. The measurement results are as follows: Figure 3 shown.

[0050] Step S4: According to the potentiodynamic polarization results of the alloy sample and the orthogonal test results of laser shock strengthening, a prediction model is established, and the electrochemical corrosion resistance of the alloy under different parameter conditions is predicted by using the prediction model. The method for establishing the prediction model is:

[0051] S1: Taking the experimental parameters as independent variables and the corrosion current density in the potentiodynamic polarization curve as the dependent variable, a multivariate linear regression prediction model is established under the premise of satisfying the linear relationship as shown in formula (1):

[0052] i corr =β0+β1·Le+β2·Sd+β3·Po+β4·St (1)

[0053] In formula (1), i corr is the corrosion current density of zirconium alloy; Le is the laser energy in the experimental parameters; Sd is the spot diameter in the experimental parameters; Po is the pulse overlap rate in the experimental parameters; St is the number of scans in the experimental parameters; β0, β1, β2, β3, β4 are the correlation coefficients in the regression equation obtained after multivariate linear regression fitting of the corresponding experimental parameters and the corrosion current density;

[0054] S2: Calculate the loss function L of the prediction model and evaluate the model complexity, and perform regularization on the prediction model that does not meet the requirements;

[0055] According to the prior art, when fitting the multivariate linear regression equation, the actual value i of the experimental measurement and the predicted value i of the model are corr There is a certain error. In order to intuitively understand the performance of the model and prevent overfitting and underfitting, the loss function is used to evaluate the prediction model. The loss function L is shown in formula (2):

[0056]

[0057] In formula (2), L is the loss function; i s is the true value of the corrosion current density of the sth sample; n is the total number of experimental data sets;

[0058] When there is an overfitting problem, some regularization terms can be added according to existing technologies to prevent overfitting and improve the generalization ability of the model.

[0059] S3: Use analysis software to calculate the correlation coefficients in the prediction model in matrix form to obtain the prediction model results. In order to reduce the amount of calculation in the fitting process and quickly find the global optimal solution of linear regression, the coefficients of the model related parameters are solved using the least squares method. The optimal solution of the model coefficients is obtained when the value of the loss function reaches the minimum.

[0060] The professional statistical analysis software used is IBM SPSS Statistics, and the calculation of the correlation coefficient of the multivariate linear regression model is obtained in matrix form. In addition to calculating the correlation coefficient of the model, the statistical analysis software IBM SPSS Statistics can also obtain the interval estimation, residual, confidence interval and degree of fit of the correlation coefficient, which are used to judge the accuracy of the model.

[0061] The calculation expression of the prediction model is shown in formula (3):

[0062] AK=B (3)

[0063] In formula (3), A is the experimental parameter matrix; K is the correlation coefficient matrix; B is the corrosion current density result matrix, wherein the experimental parameter matrix data and the corrosion current density result matrix data are derived from the orthogonal test and the potentiodynamic polarization curve in steps S2 and S3, respectively.

[0064] The optimal correlation coefficients β0, β1, β2, β3, and β4 of the prediction are obtained by solving the augmented matrix A|B, and the correlation coefficients are substituted into formula (1) to obtain the prediction model result in this embodiment, as shown in formula (4):

[0065] i corr =7.652999+0.062703Le-10.936667Sd+0.042940Po+0.352917St (4)

[0066] Based on the obtained prediction model, the effect was evaluated and four verification experimental groups with experimental parameters as shown in Table 3 were selected as the verification objects of the prediction model for verification test:

[0067] Table 3 Experimental parameters of the validation experiment group

[0068] Serial number Le(mJ) Sd(mm) Po(%) St Ver-1 30 0.8 50 1 Ver-2 30 0.6 75 1 Ver-3 30 0.8 75 1 Ver-4 80 0.8 50 3

[0069] The experimental parameters of the verification experimental group were introduced into the above prediction model to obtain the potentiodynamic polarization prediction results of the alloy's electrochemical corrosion resistance.

[0070] Then the potentiodynamic polarization curve test was carried out on the verification experimental group, and the results are as follows Figure 4 As shown, the actual test results obtained in the potential polarization curve test are compared with the test results. The specific comparison results are shown in Table 4:

[0071] Table 4 Comparison between model prediction results and actual results

[0072]

[0073]

[0074] It can be seen that the overall prediction error accuracy of the established model for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy is less than 5%, showing excellent prediction performance.

[0075] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the embodiments of the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy, characterized in that: The following steps are involved: Step S1: determining experimental parameters affecting the electrochemical corrosion resistance of the alloy material, wherein the experimental parameters include laser energy, spot diameter, pulse overlap rate and scanning times, the laser energy ranges from 20 to 200 mJ, the spot diameter ranges from 0.2 to 1.0 mm, the pulse overlap rate ranges from 25 to 75%, and the scanning times ranges from 1 to 5 times; Step S2: performing an orthogonal laser shock strengthening test on the alloy sample with experimental parameters as factors; Step S3: pre-treating the alloy sample obtained in step S2, and measuring the potentiodynamic polarization curve of the alloy sample after the laser shock strengthening orthogonal test; Step S4: A prediction model is established based on the potentiodynamic polarization results of the alloy sample and the laser shock strengthening orthogonal test results, and the prediction model is used to predict the electrochemical corrosion resistance of the alloy under different parameter conditions.

2. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 1, characterized in that: The laser shock peening orthogonal test is a four-factor three-level orthogonal test L9(3 4 ).

3. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 1, characterized in that: In the orthogonal test of laser shock strengthening, the processing surface of the alloy sample is consistent with the surface level of the fixture, and the height of the processing surface of the alloy sample from the laser nozzle is 9 mm.

4. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 1, characterized in that: The pretreatment includes ultrasonic cleaning and corrosive solution immersion performed in sequence.

5. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 4, characterized in that: The ultrasonic cleaning process is to use anhydrous ethanol to ultrasonically clean the alloy sample for 15 to 20 minutes.

6. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 4, characterized in that: The corrosion solution immersion process is to prepare a composite solution with a boric acid concentration of 1200 mg / L and a lithium hydroxide concentration of 2.2 mg / L to prepare a corrosion solution, and immerse the alloy sample after ultrasonic cleaning for 3 to 5 hours.

7. The method for predicting the electrochemical corrosion resistance of laser shock strengthened zirconium alloy according to claim 1, characterized in that: The method for establishing the prediction model is: S1: Taking the experimental parameters as independent variables and the corrosion current density in the potentiodynamic polarization curve as the dependent variable, a prediction model as shown in formula (1) is established: I corr =β0+β1·Le+β2·Sd+β3·Po+β4·St (1) In formula (1), i corr is the corrosion current density of zirconium alloy; Le is the laser energy in the experimental parameters; Sd is the spot diameter in the experimental parameters; Po is the pulse overlap rate in the experimental parameters; St is the number of scans in the experimental parameters; β0, β1, β2, β3, β4 are the correlation coefficients in the regression equation obtained after multivariate linear regression fitting of the corresponding experimental parameters and the corrosion current density; S2: Calculate the loss function L of the prediction model and evaluate the model complexity, and introduce regularization technology to the prediction model that does not meet the requirements; S3: Use analysis software to calculate the correlation coefficient in the prediction model in matrix form to obtain the prediction model results, where: The prediction model calculation expression is shown in formula (3): AK=B (3) In formula (3), A is the experimental parameter matrix; K is the correlation coefficient matrix; B is the corrosion current density result matrix; By solving the augmented matrix A|B, we can obtain the optimal correlation coefficients β0, β1, β2, β3, and β4 for prediction, and substitute the correlation coefficients into formula (1) to obtain the prediction model results.

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