Elbow scouring corrosion rate model prediction method, system, electronic device and medium

Abstract

The present application relates to a kind of elbow scouring corrosion rate model prediction method, system, electronic equipment and medium, belong to scouring corrosion rate prediction field.The method obtains the corrosion accelerated erosion rate test value of elbow under different impact angles and impact speeds by multi-angle scouring corrosion test and establishes corrosion accelerated erosion model accordingly;According to the change of strain energy of elbow after particle impact, erosion accelerated corrosion model is established;According to corrosion accelerated erosion model and erosion accelerated corrosion model, elbow scouring corrosion rate comprehensive prediction model is established to predict the scouring corrosion rate of elbow in water, sand, CO2 system.Compared with the interaction model summarized by predecessors, the elbow scouring corrosion rate comprehensive prediction model of the present application also considers the effect of corrosion on erosion, and the predicted value of scouring corrosion rate at the most dangerous position outside the outlet of elbow is more accurate.

Description

Technical Field

[0001] This invention relates to the field of erosion corrosion rate prediction technology, and in particular to a method, system, electronic device and medium for predicting the erosion corrosion rate of elbows. Background Technology

[0002] In the oil and gas industry, extracted oil and gas typically contain solid particles. As oilfields enter the later stages of extraction, the produced fluids often contain high levels of sand. When these solid particles enter the oil and gas gathering and transportation pipelines, they cause numerous problems. Besides increasing pipeline pressure drop and causing blockages, they can also lead to erosion corrosion. The mechanical action of high-speed flowing sand particles can severely damage the pipeline's inner wall. Compared to single electrochemical corrosion or single mechanical erosion, erosion corrosion exhibits a significant synergistic effect, resulting in a total metal loss exceeding the sum of corrosion and mechanical erosion, making equipment and pipelines more susceptible to failure.

[0003] While there is considerable research and relatively mature understanding of the simulation and related theories of physical erosion and corrosion, with many developed models achieving good prediction results under various working conditions, the interaction between erosion and corrosion remains a challenge. Due to the complexity of the process, no interaction model has yet emerged that can be effectively applied to the geometric conditions required in practical engineering. Considering the erosion corrosion process of special flow components such as elbows, the fundamental factor lies in the different dynamic parameters of particles impacting the metal surface at different locations, namely, the different incident angles and impact velocities. Most existing erosion corrosion prediction models only consider partial interactions and lack a comprehensive model. Furthermore, they often use empirical constants to calculate the weight loss rate of the interaction based on the relationship between the corrosion rate or erosion rate, without corroding it with the dynamic parameters of particle motion. This lack of theoretical basis significantly reduces the applicability of the models and results in inaccurate predictions. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, electronic device, and medium for predicting the erosion corrosion rate of elbows, which can improve the accuracy of elbow erosion corrosion rate prediction.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] On one hand, the present invention provides a method for predicting the erosion corrosion rate model of elbows, comprising:

[0007] The corrosion acceleration rate of the elbow under different impact angles and velocities was obtained by multi-angle scouring corrosion test.

[0008] A corrosion-accelerated erosion model was established based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities.

[0009] A model of erosion-accelerated corrosion was established based on the change in strain energy of the elbow after particle impact.

[0010] A comprehensive prediction model for the erosion rate of elbows is established based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model.

[0011] The comprehensive prediction model for elbow erosion corrosion rate is used to predict the erosion corrosion rate of elbows in a water, sand, and CO2 system.

[0012] Optionally, obtaining the corrosion acceleration erosion rate test values ​​of the elbow under different impact angles and velocities through multi-angle erosion corrosion testing specifically includes:

[0013] Test pieces were made from the same steel as the elbow to be predicted;

[0014] The test specimen was subjected to multi-angle erosion corrosion test. The test media included water, sand and CO2. During the test, the impact angle and impact velocity of the test media were changed. The erosion corrosion rate of the test specimen was obtained by weight loss measurement. The total corrosion rate of the test specimen was obtained by electrochemical impedance spectroscopy and polarization curve measurement.

[0015] The specimen was subjected to a multi-angle pure erosion test. The test medium consisted only of water and sand. During the test, the impact angle and impact velocity of the test medium were changed. The pure erosion rate of the specimen during the test was obtained by using weightlessness measurement.

[0016] Based on the test values ​​of the erosion rate, total corrosion rate, and pure erosion rate of the test specimens, the corrosion acceleration erosion rate of the elbow under different impact angles and impact velocities is calculated.

[0017] Optionally, establishing a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities specifically includes:

[0018] The corrosion-accelerated erosion rate of the elbow under different impact angles and velocities was re-analyzed multiple times using the least squares method to obtain the relationship between the corrosion-accelerated erosion rate and the impact angle and velocity, which was then used as the corrosion-accelerated erosion model.

[0019] Optionally, the step of establishing an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact specifically includes:

[0020] Determine the relationship between the strain energy of the elbow after particle impact and the particle incident angle and incident velocity;

[0021] Based on the relationship between strain energy and particle incident angle and incident velocity, a formula for corrosion current after particle collision deformation is established.

[0022] Based on the corrosion current formula after particle collision deformation, an erosion-accelerated corrosion model is established.

[0023] Where ΔC represents the erosion-accelerated corrosion rate; M represents the relative atomic weight of the metal; z represents the number of electrons transferred in the metal; ρ represents the metal density; i corr The current density before deformation is represented by v; the incident velocity of the particle is represented by θ; the incident angle of the particle is represented by μ1 and μ2; and the Poisson's ratios of the impacting particle and the metal surface are represented by m. p ρ represents the mass of the incident particle. p E represents the density of the particle; E1 and E2 represent the elastic modulus of the impacting particle and the metal surface, respectively; e t H represents the coefficient of restitution. s Indicates the hardness of a metal surface; M metal The molar mass of the metal is represented by F; F represents the Faraday constant; T represents the absolute temperature; R represents the gas constant; b a This represents the Tafel slope of the anode.

[0024] Optionally, the step of establishing a comprehensive prediction model for the erosion corrosion rate of the elbow based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model specifically includes:

[0025] Based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model, a comprehensive prediction model for the erosion corrosion rate of elbows is established: W' = C + ΔC + E + ΔE; where W' represents the erosion corrosion rate; C represents the corrosion rate; ΔC represents the erosion-accelerated corrosion rate; E represents the erosion rate; and ΔE represents the corrosion-accelerated erosion rate.

[0026] On the other hand, the present invention also provides a model prediction system for elbow erosion corrosion rate, comprising:

[0027] The multi-angle erosion corrosion test module is used to obtain the test value of the corrosion acceleration erosion rate of elbows under different impact angles and impact velocities through multi-angle erosion corrosion testing.

[0028] The corrosion-accelerated erosion model establishment module is used to establish a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities.

[0029] The erosion-accelerated corrosion model building module is used to build an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact.

[0030] The comprehensive prediction model building module is used to build a comprehensive prediction model of the erosion corrosion rate of the elbow based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model.

[0031] The erosion corrosion rate prediction module is used to predict the erosion corrosion rate of the elbow in a water, sand, and CO2 system using the comprehensive prediction model for elbow erosion corrosion rate.

[0032] On the other hand, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the elbow erosion rate model prediction method.

[0033] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the aforementioned method for predicting the erosion rate model of elbows.

[0034] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0035] This invention provides a method, system, electronic device, and medium for predicting the erosion corrosion rate of an elbow. The method includes: obtaining test values ​​of the accelerated erosion rate of the elbow under different impact angles and velocities through multi-angle erosion corrosion testing; establishing an accelerated erosion model based on the test values ​​of the accelerated erosion rate of the elbow under different impact angles and velocities; establishing an accelerated erosion corrosion model based on the change in strain energy of the elbow after particle impact; establishing a comprehensive prediction model of the elbow's erosion corrosion rate based on the accelerated erosion model and the accelerated erosion corrosion model; and using the comprehensive prediction model of the elbow's erosion corrosion rate to predict the erosion corrosion rate of the elbow in a water, sand, and CO2 system. This invention explores the interaction between two key kinetic parameters, particle impact angle and impact velocity, and erosion corrosion by controlling variables. Combining relevant theories and test results, it establishes the interaction relationship between particle impact angle, impact velocity, and erosion corrosion, thereby establishing a more reliable comprehensive prediction model for elbow erosion corrosion rate. Compared with the interaction models summarized by predecessors, the comprehensive prediction model for elbow erosion corrosion rate of this invention also considers the effect of corrosion on erosion, and the predicted value of erosion corrosion rate at the most dangerous position of the outer outlet of the elbow is more accurate. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A flowchart of a method for predicting the erosion corrosion rate model of elbows provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the multi-angle erosion corrosion testing device used in this invention.

[0039] Figure 3 Fit an equivalent circuit diagram to the impedance spectrum data;

[0040] Figure 4 A comparison chart of the regression values ​​obtained from binary linear regression and the actual values;

[0041] Figure 5 A comparison chart of regression values ​​and actual values ​​when the regression number n=4;

[0042] Figure 6 This is a comparison chart of the total erosion corrosion rate on the outer side of the elbow at a flow rate of 3.5 m / s and the test results. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] The purpose of this invention is to provide a method, system, electronic device, and medium for predicting the erosion corrosion rate of elbows, which can improve the accuracy of elbow erosion corrosion rate prediction.

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] Figure 1 A flowchart illustrating the method for predicting the erosion corrosion rate of elbows according to an embodiment of the present invention. See also... Figure 1 The present invention provides a method for predicting the erosion corrosion rate of elbows using a model, comprising:

[0047] Step 101: Obtain the corrosion acceleration rate test value of the elbow under different impact angles and impact velocities through multi-angle erosion corrosion test.

[0048] This invention involves conducting multi-angle erosion corrosion tests on elbow test pieces, changing the particle incident velocity and angle. The erosion corrosion rate W is obtained using weight loss measurement; the sum of the flow corrosion rate and the accelerated erosion corrosion rate, i.e., the total corrosion rate C+ΔC, is obtained using electrochemical impedance spectroscopy and polarization curve measurement. A multi-angle pure erosion test is then conducted, changing the particle incident velocity and angle, and the pure erosion rate E is obtained using weight loss measurement. The erosion corrosion rate W, the total corrosion rate C+ΔC, and the pure erosion rate E are then substituted into the following formula (1) to obtain the accelerated erosion rate ΔE data for the test piece.

[0049] W = C + ΔC + E + ΔE (1)

[0050] The ΔE of the specimen obtained in step 101 on the multi-angle erosion corrosion testing device is used for regression analysis in step 102.

[0051] Step 101 obtains the corrosion acceleration rate test values ​​of the elbow under different impact angles and impact velocities through multi-angle erosion corrosion testing, specifically including:

[0052] Step 1.1: Make a test piece from the same steel as the bend to be predicted.

[0053] Test pieces are made using the same steel as the elbow to be predicted. The size of the test piece needs to match the installation location of the multi-angle erosion corrosion testing device. In this specific embodiment of the invention, the test piece is 7mm long and wide, and 2mm thick. The structure of the multi-angle erosion corrosion testing device is shown below. Figure 2 The multi-angle erosion corrosion testing device used in this embodiment of the invention includes a centrifugal pump 201, a flow meter 202, a cooling pipe and a thermometer 203, a nozzle 204, a test piece 205, a stirring blade 206, a reference electrode 207, an auxiliary electrode 208, an air inlet pipe 209, a drain valve 210, and an electrochemical workstation 211. Figure 2 The square box on the platform contains the test medium (water, sand, etc.). The test piece 205 can be adjusted in angle. The test medium is pressurized by a centrifugal pump 201 and sprayed underwater through a nozzle 204, impacting the test piece 205 and causing erosion corrosion. The required parameters are determined through electrochemical measurements, weight loss measurements, etc.

[0054] pass Figure 2The multi-angle erosion corrosion testing device shown performs multi-angle erosion corrosion tests on the specimens, using controlled variables. The nozzle outlet flow velocity v is set to 1.5 m / s, 2.5 m / s, and 3.5 m / s, respectively, and the impact angle θ is set to 60°, 45°, 30°, and 15°. Each test is performed twice: once for weight loss and electrochemical impedance spectroscopy, and once for polarization curve measurement only. Each test cycle is 8 hours. To ensure the reliability of the test data, each test is repeated three times. In this invention, the impact velocity is the nozzle jet velocity in the multi-angle erosion corrosion test, which is also the particle incident velocity.

[0055] Step 1.2: Perform multi-angle erosion corrosion test on the test piece. The test medium includes water, sand and CO2. During the test, change the impact angle and impact velocity of the test medium. Use weight loss measurement to obtain the erosion corrosion rate test value of the test piece during the test. Use electrochemical impedance spectroscopy and polarization curve measurement to obtain the total corrosion rate test value of the test piece during the test.

[0056] Specifically, in the multi-angle erosion corrosion test, the test medium is a 3.5% wt sodium chloride solution, prepared from deionized water and analytical grade sodium chloride. Before the test, high-purity carbon dioxide gas is continuously introduced into the water tank containing the medium solution for 12 hours to ensure the solution reaches carbon dioxide saturation. During the test, carbon dioxide is continuously introduced to maintain the solution at carbon dioxide saturation, and the final pH of the solution reaches 4.9. Finally, 1.25% wt quartz sand is added to obtain the test medium consisting of water, sand, and CO2, thus enabling multi-angle erosion corrosion testing in a water, sand, and CO2 system.

[0057] The specific procedures for weight loss measurement and electrochemical impedance spectroscopy measurement are as follows:

[0058] Before the test, the test piece was degreased with petroleum ether, sanded with water sandpaper up to 1000 grit, rinsed with deionized water and then dehydrated with anhydrous ethanol, and then placed in a vacuum drying oven to dry for 24 hours. The weight was measured to obtain the parameter m0 in the following formula (2), and a single-component silicone rubber was used to bond it to the test position in the multi-angle erosion corrosion test device for weight loss test.

[0059]

[0060] In the formula, L is the weight loss rate of the specimen, mm / a; m0 is the weight of the specimen before the weight loss measurement, g; m1 is the weight of the specimen after the weight loss measurement, g; and s is the area of ​​the working surface, cm². 2 ρ is the density of the sample material, in g / cm³. 3 t represents the duration of the corrosion test, in hours (h).

[0061] After the weight loss test, the test piece was removed, and the silicone rubber around the test piece was cleaned. A hexamethylenetetramine hydrochloride rust removal solution was prepared according to GB / T16545-2015. The test piece was soaked for 5 minutes and then the residual corrosion products were gently brushed away with a soft brush. The test piece was rinsed with deionized water and dehydrated with anhydrous ethanol. After being placed in a vacuum drying oven for 24 hours, it was weighed to obtain the parameter m1 in formula (2). The values ​​of the parameters m0 and m1 obtained from the test were substituted into formula (2) to calculate the weight loss rate L. The test data were calculated three times, and the average value was taken as the final weight loss rate, which was used as the test value of the erosion corrosion rate W in formula (1).

[0062] See Figure 2 In the test, an electrochemical workstation 211 was used to perform in-situ electrochemical measurements on the sample 205. The sample 205 was used as the working electrode, the platinum electrode as the auxiliary electrode 208, and the saturated calomel electrode (SCE) as the reference electrode 207, thus forming a three-electrode testing system. Electrochemical impedance spectroscopy (EIS) measurements were performed, with a frequency range of 100 kHz to 10 mHz and an AC sinusoidal excitation signal amplitude of 10 mV. Figure 3 The equivalent circuit diagram shown was used to fit the impedance spectrum data using ZsimpWin software to obtain R. p . Figure 3 In the middle, R s R represents the solution resistance between the working electrode and the Luggin capillary orifice of the reference electrode. p This represents the charge transfer resistance between the metal and the solution, and CPE1 represents the constant phase angle element of the double layer between the metal substrate and the solution. In this invention, the metal is specimen 205, and the solution is a test medium including water, sand, and CO2.

[0063] The polarization curve measurement process is as follows:

[0064] Before testing, the test piece was degreased with petroleum ether, sanded with wet sandpaper up to grit 1000, rinsed with deionized water and then dehydrated with anhydrous ethanol. It was then placed in a vacuum drying oven and dried for 24 hours. One-component silicone rubber was used to bond it to the test location for testing.

[0065] Polarization curves were measured during the test. The measurement potential range was ±250mV based on the open-circuit potential, and the scan rate was 0.333mV / s. The parameter b was obtained by fitting the polarization curves using Powersuit software. a b c .

[0066] According to the Stern-Geary equation, the flow corrosion current density during the activation process can be calculated using the following formula: In the formula, i corr The corrosion current density is mA / cm².2 B is the Stern-Geary coefficient, mV; R p The polarization resistance is obtained by fitting the EIS impedance spectrum, in Ω·cm. 2 b a Tafel slope at the anode, mV; b c The cathode Tafel slope is given in mV.

[0067] Based on the magnitude of the corrosion current, it can be converted into a corrosion rate in mm / a using the following formula (3):

[0068]

[0069] In the formula, y is the corrosion rate, mm / a; M is the relative atomic weight of the metal, g / mol; z is the number of electrons transferred in the metal; and ρ is the metal density, g / cm³. 3 i corr The corrosion current density is mA / cm². 2 .

[0070] Parameter b a b c R p Substitute the test value into the formula Obtain the corrosion current density i corr The test value, and then the corrosion current density i corr The test value is substituted into formula (3) to calculate the corrosion rate y, which is then used as the test value of the total corrosion rate C+ΔC in formula (1).

[0071] Step 1.3: Perform a multi-angle pure erosion test on the test piece. The test medium consists only of water and sand. During the test, change the impact angle and impact velocity of the test medium. Use weightlessness measurement to obtain the pure erosion rate test value of the test piece.

[0072] The multi-angle pure erosion test process is as follows:

[0073] Controlled variable tests were conducted, with nozzle outlet flow velocities (v) of 1.5 m / s, 2.5 m / s, and 3.5 m / s, and impact angles (θ) of 60°, 45°, 30°, and 15°, respectively. Each test lasted 8 hours. To ensure the reliability of the test data, each test was repeated three times. The pure erosion test medium consisted of deionized water with 1.25% wt quartz sand. To eliminate the influence of electrochemical corrosion and ensure that the medium contained no corrosive ions, high-purity nitrogen gas was continuously introduced into the medium for 12 hours before the test to ensure the removal of dissolved oxygen and minimize the possibility of cathodic oxygen absorption reactions on the metal surface during the test. High-purity nitrogen gas was continuously introduced during the test.

[0074] The remaining test steps are the same as those for weight loss measurement. Substitute each test parameter into formula (2) to obtain the weight loss rate L under different erosion angles and velocities, which is used as the test value of the pure erosion rate E in formula (1). The difference between the two is that in the erosion corrosion test, the erosion corrosion rate W can be obtained by formula (2) after weight loss measurement, while in the pure erosion test, the pure erosion rate E is obtained by substituting the weight loss measurement into formula (2). In this invention, the term "weight loss" means that after pure erosion or erosion corrosion, the weight of the specimen will decrease, and the difference in weight loss is the weight loss. For the pure erosion test, the weight loss rate L is the pure erosion rate E; for the erosion corrosion test, the weight loss rate is the erosion corrosion rate W.

[0075] Step 1.4: Calculate the corrosion acceleration rate test value of the elbow under different impact angles and impact velocities based on the erosion corrosion rate test value, total corrosion rate test value and pure erosion rate test value of the test specimen in the test.

[0076] This invention employs multi-angle erosion corrosion testing on elbow test specimens, varying the particle incident velocity and angle. The erosion corrosion rate W is obtained using weight loss measurement, while the total corrosion rate C+ΔC is obtained using electrochemical impedance spectroscopy and polarization curve measurement. Multi-angle pure erosion testing is also conducted, changing the particle incident velocity and angle, and using weight loss measurement to obtain the pure erosion rate E. These test values ​​are then substituted into the formula W=C+ΔC+E+ΔE to obtain the corrosion-accelerated erosion rate ΔE of the test specimen.

[0077] Step 102: Establish a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities.

[0078] Step 102 uses the ΔE test data from step 101 to perform regression analysis using the least squares method to obtain the relationship between the corrosion-accelerated erosion rate ΔE, the particle incident velocity v, and the particle incident angle θ, which serves as the corrosion-accelerated erosion model.

[0079] Step 101 yields the final test values ​​of the corrosion-accelerated erosion rate ΔE under different angles and velocities. The independent variables controlled in the test are the particle incident velocity v and the particle incident angle θ, and the dependent variable is the corrosion-accelerated erosion rate ΔE (mm / a).

[0080] Least squares regression analysis of test data using the Python language environment. Figure 4 The image shows a comparison between the regression values ​​obtained through binary linear regression and the actual values, where the scatter plot represents the actual values ​​and the plane represents the regression values. From... Figure 4As can be seen, the actual test values ​​do not closely match the fitted regression function, therefore multiple fitting regression analyses are required.

[0081] Table 1 below lists the fitted regression values, true values, and errors for regression times n = 2, 3, and 4, respectively. It can be seen that when n = 2, the regression error ranges from -128.13% to 79%, which is quite large; when n = 3, the error ranges from -35.94% to 25.71%, showing some improvement compared to n = 2; when n = 4, the error ranges from -3.28% to 2.86%, indicating a high degree of agreement between the regression values ​​and the actual test values, and the regression effect is good. Figure 5 As shown, the scatter plot represents the actual values, and the plane represents the regression values. Figure 5 The regression values ​​and actual values ​​are highly consistent, so the fitting results when n=4 are selected as the prediction model for application.

[0082] Table 1. Fitting results and errors for different iterations (n)

[0083]

[0084]

[0085] Finally, the corrosion acceleration erosion rate ΔE obtained by least squares regression analysis for impact angle θ and impact velocity v is:

[0086] ΔE=-1.77-0.084v-0.00022θ-0.26v 2 -0.0047v·θ-0.45θ 2 +0.25v 3 -0.016v 2 ·θ+0.00041v·θ 2 +0.14θ 3 -0.062v 4 +0.0028v 3 ·θ-0.0000062v 2 ·θ 2 +0.0028v·θ 3 -0.0000026θ 4 (4)

[0087] Formula (4) is the corrosion-accelerated erosion model established in the embodiments of the present invention.

[0088] Step 103: Establish an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact.

[0089] The erosion-accelerated corrosion rate ΔC and the corrosion current density i before deformation were derived theoretically. corrParticle incident velocity v The relationship between factors such as particle incident angle θ is used as a model for erosion-accelerated corrosion.

[0090] Step 103 establishes an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact, specifically including:

[0091] Step 3.1: Determine the relationship between the strain energy of the elbow after particle impact and the particle incident angle and incident velocity; the specific process is as follows:

[0092] Erosion accelerates the corrosion rate due to the increase in strain energy after particle impact, where the strain energy is:

[0093]

[0094] Among them, M metal σ is the molar mass of the metal. S Let V be the surface stress, and V be the volume of deformation caused by a single impact.

[0095] Surface stress:

[0096]

[0097] Energy conservation equation:

[0098]

[0099] v1 and v2 represent the incident and rebound velocities of the particle, respectively; v1 is the incident velocity v of the particle. θ1 and θ2 represent the angles between the particle and the impact surface at the time of incident and rebound, respectively; θ1 is the incident angle θ of the particle.

[0100] Incident velocity, rebound velocity and coefficient of restitution e t The relationship is as follows:

[0101]

[0102] The volume of deformation produced by a single impact:

[0103]

[0104] Substituting equations (9) and (6) into equation (5), we obtain the relationship between strain energy and particle incident angle and velocity:

[0105]

[0106] Step 3.2: Establish the corrosion current formula after particle collision deformation based on the relationship between strain energy, particle incident angle, and incident velocity; the specific process is as follows:

[0107] The surface mechano-electrochemical potential of the metal, determined by local deformation and electrochemical reaction, is as follows:

[0108] μ se =μ0+RTlna+A+nFε=μ0+RTlna se (11)

[0109] The mechanical-electrochemical activity is: a se =ae (nFε+A) / RT (12)

[0110] Mechanical-electrochemical activity is expressed using overpotential as: a se =ae (αnFη+A) / RT (13)

[0111] Where μ se a represents the mechanochemical potential of a metal surface. se The expression represents the mechanical-electrochemical activity; n is the number of electrons transferred in the reaction; F is the Faraday constant, 96485 C / mol; μ0 is the standard chemical potential; R is the gas constant; T is the absolute temperature; a is the reaction activity; and ε is the potential of the electrochemical reaction.

[0112] The reaction current density i is: i = nFS. The reaction rate S is: S = ZCe -(Ae / RT) In the formula, Z is the reaction constant, C is the concentration of the reactants, and Ae is the activation energy. Then the reaction current density is:

[0113] i = nFKC (14)

[0114] Where K = Ze (-Ae / RT) .

[0115] The exchange current density i0 when the reaction reaches equilibrium is:

[0116]

[0117] The current density when the metal surface has not yet deformed is:

[0118]

[0119]

[0120] Where α and β are the transfer coefficients, α+β=1; η is the overpotential; This represents the anodic current density before the metal surface has deformed. This represents the cathode current density before the metal surface has deformed. (C) R For the concentration of the reducing agent, C O This represents the concentration of the oxide. Represents the anodic reaction rate constant. This represents the cathode reaction rate constant.

[0121] Replace the concentration term C of the anodic reaction with the mechano-electrochemical activity derived in equation (13). R The current density after surface deformation is:

[0122]

[0123]

[0124] in The anodic current density after surface deformation. The cathode current density is the result of surface deformation.

[0125] Substituting the exchange current density in equation (15) into equations (17a) and (17b), we get:

[0126]

[0127]

[0128] The net anodic polarization current density before and after deformation of the metal surface is:

[0129]

[0130]

[0131] in and i a These are the net anodic polarization current densities before and after deformation, respectively. and η a These are the overpotentials before and after deformation, respectively.

[0132] The net current density of anodic and cathodic polarization after surface deformation is:

[0133]

[0134]

[0135] in i represents the net anodic polarization current density after deformation. a,0 i represents the exchange current density of the anodic reaction. c i represents the net current density of cathode polarization. c,0 η represents the exchange current density of the cathode reaction. c This indicates the overpotential of the cathode.

[0136] The net current density of the entire deformed electrode corrosion circuit is:

[0137]

[0138] The overpotential is written in the form of potential minus equilibrium potential, i.e. and η c =EE eq,c Tafel slope b during activation polarization process a =RT / βnF, b c =RT / αnF. E is the electrode potential. E represents the anode equilibrium potential after deformation. eq,a E represents the anode equilibrium potential before deformation. eq,c b is the cathode equilibrium potential. a Let b be the Tafel slope of the anode. c The cathode Tafel slope.

[0139] Equation (21) is transformed as follows:

[0140]

[0141] In the formula, E corr This represents the corrosion potential of the undeformed surface. The change in equilibrium potential caused by deformation of the metal surface is... At this time, at the corrosion potential E corr The corrosion current density is:

[0142]

[0143] Substituting equation (23) into equation (22), we can obtain the net current density of the deformed electrode. for:

[0144]

[0145] In the formula This represents the corrosion potential of the deformed electrode surface in a corrosive medium when the net current density is zero.

[0146] Net current density i of undeformed electrode net The expression is:

[0147]

[0148] Equation (24) can be further rewritten to obtain:

[0149]

[0150] in Let be the change in corrosion potential on the deformed surface. The reaction kinetic equation is:

[0151]

[0152]

[0153] Substituting equations (27a) and (27b) into equation (26), we get:

[0154]

[0155] Therefore, the relationship between the corrosion current after particle collision deformation and the anodic current before deformation (mechanical-electrochemical effect equation) is:

[0156]

[0157] The change in corrosion potential is:

[0158]

[0159] Substituting (30) into (29) yields the formula for the corrosion current after particle collision deformation:

[0160]

[0161] Step 3.3: Establish an erosion-accelerated corrosion model based on the corrosion current formula after particle collision deformation; the specific process is as follows:

[0162] Substituting the relationship between strain energy and particle incident angle and velocity (10) into the corrosion current formula (31) after particle collision deformation, we get... We can obtain:

[0163]

[0164] Substituting equation (32) into equation (3) yields the erosion-accelerated corrosion model:

[0165]

[0166] Where ΔC represents the erosion-accelerated corrosion rate; M represents the relative atomic weight of the metal; z represents the number of electrons transferred in the metal; ρ represents the metal density; i corr The current density before deformation is represented by v; the incident velocity of the particle is represented by θ; the incident angle of the particle is represented by μ1 and μ2; and the Poisson's ratios of the impacting particle and the metal surface are represented by m. p ρ represents the mass of the incident particle. p E represents the density of the particle; E1 and E2 represent the elastic modulus of the impacting particle and the metal surface, respectively; e t H represents the coefficient of restitution. s Indicates the hardness of a metal surface; M metal The value represents the molar mass of the metal; F represents the Faraday constant; T represents the absolute temperature; and R represents the gas constant.

[0167] Step 104: Establish a comprehensive prediction model for the erosion rate of elbows based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model.

[0168] Given the formula for calculating the erosion rate (1), the corrosion-accelerated erosion model was obtained in step 102, namely the relationship between ΔE and the particle incident angle θ and incident velocity ν (4). In step 103, the erosion-accelerated corrosion model was obtained, namely the relationship between ΔC and the particle incident angle θ, incident velocity ν, and corrosion current density i before deformation. corr The relationship is (33). Substituting the corrosion-accelerated erosion model (4) and the erosion-accelerated corrosion model (33) into the erosion corrosion rate calculation formula (1), the comprehensive prediction model of the elbow erosion corrosion rate of the present invention can be established:

[0169] W'=C+ΔC+E+ΔE (34)

[0170] Where W' represents the erosion corrosion rate; C represents the corrosion rate; ΔC represents the erosion-accelerated corrosion rate; E represents the erosion rate; and ΔE represents the corrosion-accelerated erosion rate. In the comprehensive prediction model (34) of the elbow erosion corrosion rate of the present invention, ΔC and ΔE are calculated using the erosion-accelerated corrosion model (33) and the corrosion-accelerated erosion model (4) of the present invention. The corrosion rate C and the erosion rate E can be calculated using existing corrosion models (such as the electrochemical model of hydrogen ion mass transfer) and existing erosion models.

[0171] When using the comprehensive prediction model for elbow erosion rate of the present invention to predict the erosion rate, it is only necessary to use the electrochemical model of hydrogen ion mass transfer of the invention and the existing erosion model to build a 3D model on COMSOL software and set the elbow parameters to be predicted, thereby obtaining C and E at each position on the elbow. Then, according to the corrosion-accelerated erosion model and the erosion-accelerated corrosion model obtained in steps 102 and 103, ΔE and ΔC are calculated to form the four parts C, E, ΔE and ΔC of the erosion rate W at each position on the elbow. The sum of these parts is the predicted erosion rate W' output by the comprehensive prediction model for elbow erosion rate.

[0172] Step 105: Use the comprehensive prediction model for elbow erosion corrosion rate to predict the erosion corrosion rate of the elbow in a water, sand, and CO2 system.

[0173] First, a 3D elbow model was built using COMSOL software. The elbow diameter was 5.1 cm, the radius of curvature was set to 1.5D, and the lengths of the straight pipe sections before and after the elbow were 1 m and 0.5 m, respectively, to ensure that the fluid had fully developed before reaching and exiting the elbow. The mesh was generated using physics-controlled fluid dynamics options. The entire domain mesh was generated by sweeping the inlet plane after meshing, resulting in a total of 43,740 elements. The average mesh quality was 0.8288, the element volume ratio was 0.01168, the number of boundary layers was set to 5, and the stretching factor was 1.2. Fluid flow simulation within the elbow was performed using the CFD turbulence module in the software. To better obtain parameter information at the wall, the turbulence model was solved using a k-ω model. Velocity-pressure boundary conditions were used, with a normal velocity at the inlet and an outlet pressure of 1 atm. No-slip boundary conditions were applied at the wall boundaries, and the turbulent flow near the wall was treated according to the standard wall function. The inlet velocities of the elbows were set to 2.5 m / s and 3.5 m / s, respectively, with free flow at the outlet. The fluid medium's density, viscosity, and other physical properties were set according to those of water, and the fluid temperature was set to 25°C. The inlet velocity mentioned here refers to the inlet flow velocity of the elbow in the 3D model; it is a boundary condition required to simulate the actual flow velocity of the elbow to be predicted. The impact velocity *v* in this invention is a term used in multi-angle erosion corrosion testing; in the 3D model, it is the particle incident velocity, calculated from the 3D model of this COMSOL software, representing the particle incident velocity at various locations—a calculated fluid dynamics parameter.

[0174] The electrochemical module employs electroanalysis to determine reactant concentrations through the carbon dioxide hydration reaction and the stepwise ionization of carbonic acid. The outer surface of the elbow is designated as the electrode surface. The anodic reaction is set as iron oxidation, and the cathodic reactions are hydrogen evolution and direct reduction of carbonic acid. Water-based electroneutrality is applied to both the solution and the electrode surface. Initial CO2 and hydrogen ion concentrations are input at the inlet. Electrolyte convection is configured via a built-in interface using a CFD-calculated flow field, neglecting the effects of electric field migration.

[0175] The process of establishing the hydrogen ion mass transfer model is as follows:

[0176] The main component of the elbow is iron, and the anode reaction is: Fe-2e - →Fe 2+ The cathode is the site of the reduction reaction between hydrogen ions and carbonic acid: 2H₂O + +2e - →H2, The cathode reaction current density is: Where i c It is the current density generated by the cathode reaction, A / m 2 i0 is the exchange current density generated by the cathode reaction, in A / m. 2 η is the overpotential of the electrode reaction, V; b cThe Tafel slope of the cathode reaction, V. The current density generated by hydrogen ion mass transfer is: i m [H + ]=nFk m (C b -C s ), where n is the number of electrons transferred in the reaction; F is the Faraday constant, with a value of 96485 C / mol; k m It is the mass transfer coefficient, m / s; C b and C s It refers to the total concentration of reactants in the solution and the concentration of reactants at the interface, in mol / m³. 3 .

[0177] The mass transfer limiting current density is: i lim [H + ]=nFk m C b The current density i[H] in the hydrogen ion reduction reaction + The following equation is obtained by solving: i c [H + [] represents the current density during the hydrogen ion activation polarization process.

[0178] The current density for the reduction of carbonic acid caused by a chemical reaction is: In the formula C b [CO2] is the concentration of CO2 in the solution, in mol / m³. 3 ;D H2CO3 Let m be the diffusion coefficient of carbonic acid. 2 / s;K hyd k is the chemical equilibrium coefficient for the hydration reaction. f The forward reaction rate coefficient is approximately 0.03022 s⁻¹, which is the value at a greenhouse temperature. -1 The total current density i[H2CO3] during the carbonic acid reduction process is: i c [H2CO3] represents the current density during the carbonic acid activation polarization process.

[0179] The anode current density is: i[Fe 2+ ]=i[H + ]+i[H2CO3], where i[Fe 2+ [i] represents the anodic current density, the magnitude of which is related to the corrosion current density i. corr Equal. The corrosion current density i at each location in the elbow model is... corr Substituting into formula (3), the flow corrosion rate C at each location of the elbow in the electrochemical model of hydrogen ion mass transfer can be obtained. The main purpose of establishing this electrochemical model of hydrogen ion mass transfer is to obtain the flow corrosion rate C and corrosion current density i at each location of the elbow. corr .

[0180] This invention utilizes simulation software to establish a 3D model of the elbow. Specifically, the 3D model established using COMSOL software can display the corrosion current density at each location of the elbow. An electrochemical model of hydrogen ion mass transfer is then established to determine the flow corrosion current density i at each location on the elbow. corr And the pure corrosion rate C. Then, using the existing erosion model, the pure erosion rate E at each position on the elbow can be obtained. Then, using the corrosion-accelerated erosion model and the erosion-accelerated corrosion model from steps 102 and 103, ΔE and ΔC at each position on the elbow can be obtained. Substituting the obtained C, E, ΔE, and ΔC at each position on the elbow into formula (34), the predicted value W' of the erosion corrosion rate W at each position on the elbow can be obtained, which is the prediction result of elbow corrosion under the water, sand, and CO2 system of this invention. All the relationships and models used in the entire software, including the erosion-accelerated corrosion model, the corrosion-accelerated erosion model, the electrochemical model of hydrogen ion mass transfer, and the existing erosion models, are all part of the comprehensive prediction model of this invention.

[0181] This invention provides a method for predicting the erosion corrosion rate of elbows. By analyzing the main factors affecting elbow erosion corrosion, a comprehensive prediction model for elbow erosion corrosion rate under a water, sand, and CO2 system is proposed. Compared with most models, the advantage of this comprehensive prediction model for elbow erosion corrosion rate is that it not only considers the enhancement of corrosion by erosion but also focuses on the influence of corrosion on erosion, thus improving the accuracy of elbow erosion corrosion rate prediction and the model's versatility. Based on considering the particle incident angle and inlet velocity, this invention proposes a new method for establishing an elbow erosion corrosion model. Using multiple fitting regression analysis, the functional relationship between the particle incident angle, incident velocity, and the enhanced erosion rate can be calculated. The comprehensive prediction model for elbow erosion corrosion rate established based on this is particularly accurate in predicting the erosion corrosion weight loss rate at the most dangerous location on the outer outlet of the elbow, and has good engineering significance. Furthermore, the method proposed in this invention is simple to calculate, easy to implement, and more in line with engineering practice, making it convenient for engineering technicians to master and use. The method is scientific, has good processability, and is easy to apply and promote.

[0182] To verify the accuracy of the model, validation tests were conducted on elbows. The erosion corrosion weight loss rate W at several typical locations of the elbows during the tests was compared with the model's predicted values, and also compared with other existing models. The comparison results are shown in […]. Figure 6 , Figure 6In the original text, "Modeling" represents the total erosion corrosion rate W (i.e., total weight loss rate) calculated using the comprehensive prediction model for elbow erosion corrosion rate of this invention; "Experiment" represents the total weight loss rate W in the verification test conducted using an elbow; "Wood et al" represents the calculated value of the erosion corrosion model obtained by Wood et al.; and "Stack et al" represents the calculated value of the erosion corrosion model obtained by Stack et al. Figure 6 As can be seen, at positions 60° and 90° outside the elbow, the erosion corrosion rate calculated by this invention is closer to the data from the verification test than that calculated by the model developed by Wood, Stack, and others. In other words, the comprehensive prediction model for the erosion corrosion rate of the elbow in this invention is more accurate in predicting the erosion corrosion weight loss rate at the most dangerous position outside the elbow outlet.

[0183] This invention provides a method for predicting the erosion corrosion rate of elbows. This method is based on multi-angle erosion corrosion analysis and testing, plastic deformation of individual particles, and regression analysis of particle incident velocity and incident angle. First, a multi-angle erosion corrosion device is used to test the specimen, obtaining the accelerated erosion rate ΔE for regression analysis to derive the relationship of ΔE. Then, the relationship of the accelerated erosion rate ΔC is derived by examining the relationship between the strain energy of a single particle impact and the corrosion current density. Finally, a 3D model of the elbow is created using COMSOL software. C and E are obtained using the invented electrochemical model of hydrogen ion mass transfer and existing erosion models. By adding the previously obtained ΔE and ΔC to the two models, the comprehensive prediction model for the erosion corrosion rate of elbows in a water, sand, and CO2 system is finally obtained. The method of this invention conducts underwater jet tests on two influencing factors: particle incident angle and incident velocity. The test data is then analyzed and deduced, and combined with the prediction of erosion corrosion of elbows, to achieve a more accurate prediction of the most dangerous location on the elbow, the outer side of the elbow outlet, which has good engineering significance.

[0184] Based on the method provided by this invention, this invention also provides a model prediction system for elbow erosion corrosion rate, comprising:

[0185] The multi-angle erosion corrosion test module is used to obtain the test value of the corrosion acceleration erosion rate of elbows under different impact angles and impact velocities through multi-angle erosion corrosion testing.

[0186] The corrosion-accelerated erosion model establishment module is used to establish a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities.

[0187] The erosion-accelerated corrosion model building module is used to build an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact.

[0188] The comprehensive prediction model building module is used to build a comprehensive prediction model of the erosion corrosion rate of the elbow based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model.

[0189] The erosion corrosion rate prediction module is used to predict the erosion corrosion rate of the elbow in a water, sand, and CO2 system using the comprehensive prediction model for elbow erosion corrosion rate.

[0190] This invention explores the interaction between two key kinetic parameters, particle impact angle and impact velocity, and erosion corrosion using a controlled variable approach. Combining relevant theories and test results, it establishes the interaction relationship between particle impact angle, impact velocity, and erosion corrosion, thereby creating a more reliable comprehensive prediction model for elbow erosion corrosion rates. Compared to previous interaction models, this invention's comprehensive prediction model for elbow erosion corrosion rates also considers the effect of corrosion on erosion, resulting in more accurate predictions of erosion corrosion rates at the most dangerous location on the outer side of the elbow outlet.

[0191] Furthermore, the present invention also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The processor can call a computer program stored in the memory to execute the described method for predicting the erosion rate model of elbows.

[0192] Furthermore, when the computer program in the aforementioned memory is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0193] Furthermore, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, can implement the aforementioned method for predicting the erosion rate model of elbows.

[0194] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0195] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for predicting the erosion corrosion rate of elbows using a model, characterized in that, include: The corrosion acceleration rate of the elbow under different impact angles and velocities was obtained by multi-angle scouring corrosion test. A corrosion-accelerated erosion model was established based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities. An erosion-accelerated corrosion model is established based on the change in strain energy of the elbow after particle impact, specifically including: Determine the relationship between the strain energy of the elbow after particle impact and the particle incident angle and incident velocity; Based on the relationship between strain energy and particle incident angle and incident velocity, a formula for corrosion current after particle collision deformation is established. Based on the corrosion current formula after particle collision deformation, an erosion-accelerated corrosion model is established. ;in This indicates that erosion accelerates the corrosion rate. M Indicates the relative atomic weight of a metal; z Indicates the number of electrons transferred by the metal; Indicates metal density; This represents the corrosion current density before deformation; Indicates the particle incident velocity; Indicates the angle of particle incidence; and These represent the Poisson's ratios of the impacting particles and the metal surface, respectively. Indicates the mass of the incident particle; Indicates the density of the particles; and These represent the elastic modulus of the impacting particle and the metal surface, respectively. Indicates the coefficient of restitution; Indicates the hardness of a metal surface; Indicates the molar mass of a metal; F Denotes Faraday's constant; T Indicates absolute temperature; Represents the gas constant; The Tafel slope is the anode slope. A comprehensive prediction model for the erosion rate of elbows is established based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model. The comprehensive prediction model for elbow erosion corrosion rate is used to predict the erosion corrosion rate of elbows in a water, sand, and CO2 system.

2. The method for predicting the erosion corrosion rate of elbows according to claim 1, characterized in that, The method of obtaining the corrosion acceleration rate test values ​​of the elbow under different impact angles and impact velocities through multi-angle erosion corrosion testing specifically includes: Test pieces were made from the same steel as the elbow to be predicted; The test specimen was subjected to multi-angle erosion corrosion test. The test media included water, sand and CO2. During the test, the impact angle and impact velocity of the test media were changed. The erosion corrosion rate of the test specimen was obtained by weight loss measurement. The total corrosion rate of the test specimen was obtained by electrochemical impedance spectroscopy and polarization curve measurement. The specimen was subjected to a multi-angle pure erosion test. The test medium consisted only of water and sand. During the test, the impact angle and impact velocity of the test medium were changed. The pure erosion rate of the specimen during the test was obtained by using weight loss measurement. Based on the test values ​​of the erosion rate, total corrosion rate, and pure erosion rate of the test specimens, the corrosion acceleration erosion rate of the elbow under different impact angles and impact velocities is calculated.

3. The method for predicting the erosion corrosion rate of elbows according to claim 1, characterized in that, The establishment of a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities specifically includes: The corrosion-accelerated erosion rate test values ​​of the elbow under different impact angles and impact velocities were subjected to multiple regression analyses using the least squares method. The relationship between the corrosion-accelerated erosion rate and the impact angle and impact velocity was obtained as a corrosion-accelerated erosion model.

4. The method for predicting the erosion corrosion rate of elbows according to claim 1, characterized in that, The establishment of a comprehensive prediction model for the erosion rate of elbows based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model specifically includes: A comprehensive prediction model for the erosion rate of elbows is established based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model. ;in Indicates the rate of erosion and corrosion; Indicates the corrosion rate; This indicates that erosion accelerates the corrosion rate. Indicates the erosion rate; This indicates that corrosion accelerates the erosion rate.

5. A model prediction system for the erosion corrosion rate of elbows, characterized in that, The elbow erosion corrosion rate prediction method according to any one of claims 1 to 4, wherein the elbow erosion corrosion rate prediction system comprises: The multi-angle erosion corrosion test module is used to obtain the test value of the corrosion acceleration erosion rate of elbows under different impact angles and impact velocities through multi-angle erosion corrosion testing. The corrosion-accelerated erosion model establishment module is used to establish a corrosion-accelerated erosion model based on the test values ​​of the corrosion-accelerated erosion rate of the elbow under different impact angles and impact velocities. The erosion-accelerated corrosion model building module is used to build an erosion-accelerated corrosion model based on the change in strain energy of the elbow after particle impact. The comprehensive prediction model building module is used to build a comprehensive prediction model of the erosion corrosion rate of the elbow based on the corrosion-accelerated erosion model and the erosion-accelerated corrosion model. The erosion corrosion rate prediction module is used to predict the erosion corrosion rate of the elbow in a water, sand, and CO2 system using the comprehensive prediction model for elbow erosion corrosion rate.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for predicting the erosion rate of elbows as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the method for predicting the erosion corrosion rate model of elbows as described in any one of claims 1 to 4.

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