Method for evaluating failure of copper alloy material and predicting corrosion rate under different seawater flow rates

Abstract

The method for failure evaluation and corrosion rate prediction of copper alloy material under different seawater flow rates belongs to the field of copper alloy corrosion in marine environment. First, the XRD pattern of the copper alloy corroded in flowing seawater is analyzed to determine the micro-strain level and dislocation density; the atomic-level axial tensile strain is applied to the (111) crystal surface by using the density functional theory, and the microstructure model under different seawater flow rates is established. The dissolution potential, surface energy, work function and dissolution activation energy barrier of copper atoms on the alloy surface are analyzed, and the relationship between the dissolution rate and the activation energy barrier is explored. A prediction model of seawater flow rate and corrosion rate of copper alloy in seawater dynamic environment is established. The corrosion kinetics characteristics of copper alloy under different seawater flow rates are obtained, the corrosion failure dynamics process of copper alloy induced by atomic-level axial tension is analyzed, and thus a theoretical basis is provided for the corrosion prevention design of copper alloy components.

Description

Technical Field

[0001] This invention belongs to the field of research on corrosion and protection of copper alloys in marine environments. Specifically, it involves simulating the influence of different seawater flow velocities on the microstructure of copper alloys, and based on the analysis of corrosion kinetic parameters such as dissolution activation barrier, dissolution potential, and dissolution rate, to achieve quantitative characterization and prediction of alloy corrosion tendency under dynamic and complex seawater environments. This invention is of great significance for improving the safety, reliability, and economic benefits of marine engineering. Background Technology

[0002] Propellers and seawater pipelines are critical components of ships, and their durability in the dynamic seawater environment directly affects the ship's safety and operational efficiency. Copper alloys, due to their excellent mechanical properties and corrosion resistance, are widely used in marine engineering. However, under extreme high flow rates and pressures, copper alloys face severe corrosion challenges. The corrosion mechanisms in seawater environments are not fully understood, limiting their long-term reliability. Therefore, in-depth research into the corrosion behavior of copper alloys in dynamic seawater environments not only provides a scientific basis for their protection but also has significant engineering application value.

[0003] Recent studies have shown that mechanical factors such as seawater flow velocity and pressure significantly affect the corrosion process of copper alloys. High flow velocities can damage the surface microstructure of copper alloys, indicating that increased seawater flow velocity promotes mass transfer and generates wall shear stress, accelerating the corrosion rate. When the seawater flow velocity exceeds the critical velocity, corrosion products detach from the alloy surface, further accelerating the corrosion process. Furthermore, different seawater flow velocities can induce localized lattice distortion on the copper alloy surface, lowering the metal's equilibrium potential and making the alloy more susceptible to corrosion.

[0004] Current technology lacks a method to systematically study the corrosion behavior and microstructure evolution of copper alloys in seawater environments by combining experimental and simulation calculations. This invention proposes an innovative research method that constructs corrosion structure models of copper alloys under different seawater flow velocities based on density functional theory (DFT), analyzing corrosion kinetic parameters such as dissolution activation barrier, dissolution potential, and dissolution rate. Simultaneously, through macroscopic corrosion weight loss experiments, the influence of different seawater flow velocities on the alloy corrosion behavior is investigated. The study finds that with increasing seawater flow velocity, the mass loss and corrosion rate of copper alloys increase significantly, while corrosion resistance decreases. This method, combining simulation and experimental results, provides a scientific basis for corrosion protection of copper alloys in dynamic seawater environments and establishes a copper alloy corrosion rate prediction model based on atomic-level axial stretching. Summary of the Invention

[0005] To overcome the limitations of existing technologies, this invention aims to combine experimental and simulation calculations to study the corrosion behavior of copper alloys in dynamic seawater environments and develop a method for predicting the corrosion failure behavior of copper alloys based on atomic-level axial tensile strain. This method first determines the micro-strain level and dislocation density under different seawater flow velocities by analyzing the XRD patterns of copper alloys after corrosion by flowing seawater. Then, atomic-level axial tensile strain is applied to the (111) crystal plane using density functional theory to establish a microstructure model under different seawater flow velocities. Further, by combining the structural evolution under micro-strain conditions, the dissolution potential, surface energy, work function, and dissolution activation barrier of copper atoms on the alloy surface are analyzed to explore the relationship between the dissolution rate and the activation barrier. The intrinsic diffusion coefficient of copper atoms is calculated using the modified Sutherland equation, establishing a predictive model for the relationship between seawater flow velocity and copper alloy corrosion rate in dynamic seawater environments. This invention quantitatively simulates the influence of seawater flow velocity on the corrosion behavior of copper alloys, analyzes the corrosion kinetic characteristics of copper alloys under different seawater flow velocities, and realizes the analysis of the corrosion failure kinetic process of copper alloys induced by atomic-level axial tension, thus providing a theoretical basis for the anti-corrosion design of copper alloy components.

[0006] To achieve the invention's objective, the present invention employs the following technical solution: The micro-strain values, axial tensile strain values, and dislocation densities of copper alloys under different seawater flow velocities are determined by XRD analysis of diffraction peak shapes and peak broadening. A microstructural model of the copper alloy is established using density functional theory (DFT), and strain is applied by precisely controlling the lattice axial parameters to establish a microstructure along the z-direction of the (111) crystal plane. A vacuum layer was used to release the top two atomic layers to simulate the alloy surface, while fixing the other atomic layers to simulate the internal structure of the alloy. Geometry optimization was performed using the DMol3 module of Materials Studio, and a COSMO-like conductor shielding model and the dielectric constant of seawater were used to simulate the seawater environment. Furthermore, the relativistic effects of nuclear electrons were handled using the DFT semi-nuclear pseudopotential DSPP method, and the corrosion kinetic characteristic parameters of the copper alloy were calculated using dual numerical plus polarized DNP basis sets. The equivalent dissolution activation barrier was determined using transition state theory (TST), and the dissolution transition state of the copper alloy was optimized using linear and quadratic simultaneous transfer (LST / QST) methods to establish a linear relationship between the dissolution rate and the activation barrier. Using the intrinsic diffusion coefficient of copper atoms obtained from the Sutherland equation, a model was established to predict the corrosion rate of the copper alloy under dynamic seawater conditions.

[0007] A method for evaluating the failure and predicting the corrosion rate of copper alloy materials under different seawater flow velocities, characterized by the following steps:

[0008] (1) Analysis of atomic-level axial tensile strain of copper alloy: Based on the X-ray diffraction (XRD) test results of copper alloy after corrosion by different seawater flow rates, the micro-strain values ​​were determined by analyzing the diffraction peak shape and using peak broadening, thereby obtaining the axial tensile micro-strain and dislocation density of the internal lattice of the alloy.

[0009] By determining the full width at half maximum (FWHM) β and Bragg angle θ of the diffraction peaks, the axial tensile microstrain ε of the copper alloy structure under different seawater flow velocities is calculated according to formula (1):

[0010]

[0011] The diffraction peak broadening caused by grain size was calculated using the Scherrer formula, where K is the shape factor (usually taken as 0.9) and λ is the X-ray wavelength. Based on formulas (2) and (3), the grain size d and dislocation density ρ of the copper alloy under different seawater flow rates were determined:

[0012]

[0013] This method shows that as the seawater flow velocity increases, the axial tensile strain and dislocation density of copper alloys increase, indicating that high seawater flow velocity will cause changes in the surface structural defects of the alloy, accelerate the corrosion process of copper alloys, and lead to a decrease in their corrosion resistance.

[0014] (2) Quantitatively simulate the mechanical effect of different seawater flow rates on the alloy surface. Based on the axial tensile micro-strain ε determined in step (1), establish a microstructure model of copper alloy with different seawater flow rates through atomic-level axial tensile strain: By adjusting the lattice axial parameters, apply strain along the (111) crystal plane direction. By precisely controlling the lattice constant of copper alloy in the seawater environment, gradually increase the lattice parameters in the (111) direction, introduce axial tensile strain corresponding to the increase in flow rate, and keep the lattice parameters in other directions unchanged, thereby realizing atomic-level strain control applied to the (111) crystal plane.

[0015] (3) Calculation of copper alloy dissolution potential or copper alloy dissolution potential shift under different seawater flow velocities in dynamic seawater environment: Based on the axial tensile microstrain determined in step (1) and the microstructure model under different seawater flow velocities established in step (2), the energy of the alloy vacancy model under different flowing seawater is calculated, and then the copper alloy dissolution potential or copper alloy dissolution potential shift under different seawater flow velocities is obtained.

[0016] By determining the energy E of the alloy model without axial tensile strain alloy Energy of alloy model under axial tensile strain And the energy E of the alloy vacancy model without axial tensile strain alloy-vac Energy of alloy vacancy model under axial tensile strain The shift in the metal dissolution electrode potential caused by the introduction of tensile strain in copper alloys is calculated according to formula (4).

[0017]

[0018] This method quantitatively analyzes the dissolution tendency of copper alloys in a flowing seawater environment by describing the dissolution electrode potential of the metal during the corrosion process. The results show that as the seawater flow rate increases, the dissolution electrode potential of the copper alloy shifts to the negative direction, resulting in a decrease in the metal dissolution potential and a decrease in corrosion resistance. This verifies that the model in step (2) is suitable for simulating the corrosion behavior of copper alloys in a dynamic seawater environment.

[0019] (4) Calculation of surface energy and work function of copper alloy under different seawater flow rates in dynamic seawater environment: Based on steps (1)-(3), by constructing the (111) crystal plane alloy structure model under different axial tensile strains, energy minimization calculation is performed to obtain the energy state of the alloy surface. By calculating the potential of the alloy model under different seawater flow rates and the contact potential difference between it and the seawater interface, the influence of seawater flow rate on the surface structure and stability of copper alloy, i.e. the corresponding work function, is quantitatively analyzed.

[0020] By determining the total energy E of the surface models with different axial tension in step (2) slab and alloy bulk phase atoms N atoms Average energy E bulk The surface energy state E of the alloy under different seawater flow velocities is calculated according to formula (5). surf :

[0021]

[0022] Through the contact potential difference at the interface between copper alloy and seawater Based on the potential values ​​ψ of the alloy model at different seawater flow velocities, the work function Φ required for the copper alloy to remove surface electrons at different seawater flow velocities is calculated according to formula (6):

[0023]

[0024] The simulation results of this method show that as the seawater flow velocity increases, the surface energy of the copper alloy increases, the work function decreases, the atomic energy state of the alloy surface rises, and electrons are more likely to escape from the surface, further illustrating that the flowing seawater accelerates the corrosion kinetics of the alloy.

[0025] (5) Calculation of dissolution activation energy barrier and dissolution rate of copper alloy under different seawater flow rates in dynamic seawater environment: Based on steps (1)-(4), the dissolution activation energy barrier of copper alloy atoms under different flow rates is quantitatively analyzed by using the transition state search method, and then the dissolution rate is calculated.

[0026] The dissolution activation energy barrier ΔE(t) of the alloy under different seawater flow velocities was obtained through transition state search, where σ is the degeneracy of the reaction path, taking a value of 1, and P... 0 The standard pressure in the gas phase is 0.1 MPa, t is the corresponding room temperature or atmospheric temperature, and h is Planck's constant of 6.626 × 10⁻⁶. -34 J·s,k b The Boltzmann constant is 1.381 × 10⁻⁶. -23 J.K. -1 R is the universal gas constant, 8.314 J·K. -1 ·mol -1 In the unimolecular reaction, Δn = 0. The dissolution rate k under different seawater flow rates is calculated according to formula (7). TST :

[0027]

[0028] This method shows that as the seawater flow rate increases, the dissolution activation barrier decreases significantly, the dissolution resistance of metal atoms decreases, and the dissolution rate increases accordingly. This method can accurately assess the influence of atomic-level axial tensile strain on the corrosion kinetics of alloys under different seawater flow rates, and realize the simulation and prediction of the corrosion tendency of copper alloys under high flow rate environments.

[0029] (6) Establishment of a copper alloy corrosion rate prediction model based on atomic-level axial tension under dynamic seawater environment: Based on the axial tensile strain model of copper alloy under different seawater flow velocities in steps (1)-(2), the dissolution activation energy barrier is determined by transition state search. According to formula (7), the linear relationship between dissolution rate and activation energy barrier is established to obtain the copper alloy dissolution rate under different seawater flow velocities. Combined with parameters such as the intrinsic diffusion coefficient D of copper atoms, correction coefficient k, and time conversion factor T, the above pairs of different seawater flow velocity variables are fitted with the dissolution rate x, and the dissolution rate spectrum is transformed into a relationship model between seawater flow velocity and copper alloy corrosion rate y under dynamic seawater environment. The unit is mm / a (millimeters per year), where k is the correction coefficient, D is the intrinsic diffusion coefficient, T is the time conversion factor, α is the fitting coefficient, and C is a parameter related to the alloy, which can be obtained by fitting x with the dissolution rate, thus achieving accurate prediction of the corrosion rate of copper alloys in complex seawater environments.

[0030] In a preferred embodiment of the present invention, the copper alloy types include manganese aluminum bronze alloy (MAB) for propellers and copper-nickel alloy (B10) for seawater pipelines, etc.

[0031] In a preferred embodiment of the present invention, in step (1), the seawater flow velocity of the manganese aluminum bronze alloy MAB used for the propeller is 0-12 m / s, including 0, 2, 4, 6, 8, and 12 m / s.

[0032] In a preferred embodiment of the present invention, in step (1), the seawater flow velocity of the copper-nickel alloy B10 used in the seawater pipeline is 0-4 m / s, including 0, 1, 2, 3, and 4 m / s.

[0033] In a preferred embodiment of the present invention, in step (2), a microstructure model of the copper alloy is established based on atomic-level axial tensile strain. The method for simulating seawater flow velocity is as follows: the axial tensile strain values ​​of the copper alloy at different seawater flow velocities are obtained by XRD analysis; the microstructure model of the copper alloy is established using density functional theory (DFT); the lattice axial parameters are precisely controlled to apply strain; and a microstructure model is established in the z-direction of the (111) crystal plane. A vacuum layer is used to release the surface of the top two atomically simulated alloy layers while fixing the internal structure of the other atomically simulated alloy layers. The lattice parameters in other directions are kept constant, and the axial lattice parameters are gradually increased to introduce axial tensile strain corresponding to the increase in flow rate, thereby achieving atomic-level strain control of the copper alloy.

[0034] In a preferred embodiment of the present invention, the simulation calculation method for the characteristic parameters of copper alloy corrosion kinetics under different seawater flow velocities in steps (3)-(5) is as follows: the PBE generalized gradient approximation (GGA) method in the Materials Studio simulation package is used for geometric structure optimization. The Brillouin zone of the alloy surface is sampled on a (2×2×1) k-point grid using the Monkhorst-Pack method. The COSMO-type conductor shielding model is used, combined with the seawater dielectric constant to simulate the seawater environment, and an implicit seawater solvation model is established. The DFT semi-nuclear pseudopotential DSPP method is used to handle the relativistic effects of nuclear electrons. The basis set adopts dual numerical plus polarized DNP. In the structural optimization, the convergence tolerance and self-consistent field (SCF) convergence criterion are set to 2.72×10. -3 eV was used to calculate the corrosion kinetics characteristic parameters of copper alloys under dynamic seawater conditions.

[0035] In a preferred embodiment of the present invention, in step (6), the calculation method for the dissolution rate and corrosion rate of copper alloy under different seawater flow rates is as follows: the equivalent dissolution activation energy barrier is adopted using the transition state theory (TST), the dissolution transition state of copper alloy under seawater environment is optimized by the linear simultaneous transfer (LST) and quadratic simultaneous transfer (QST) methods, the dissolution rate is calculated based on the Sobereva method, a linear relationship between the dissolution rate and the activation energy barrier is established, and the intrinsic diffusion coefficient of copper atoms obtained by the Sutherland equation is used to transform the relationship between seawater flow rate and dissolution rate into a prediction model of corrosion rate under dynamic seawater environment.

[0036] In a preferred embodiment of the present invention, the corrosion rate prediction model for MAB alloys in a dynamic seawater environment is as follows: R 2=0.998 (Correction coefficient k1 = 1.91 × 10) -7 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 , α=-20.34).

[0037] In a preferred embodiment of the present invention, the corrosion rate prediction model for B10 alloy under dynamic seawater environment is as follows: R 2 =0.996 (Correction coefficient k2 = 2.78 × 10) -9 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 , β=-0.29).

[0038] In a preferred embodiment of the present invention, the corrosion behavior of copper alloys under dynamic seawater environments is predicted. The simulated corrosion rate shows a consistent trend with the measured value, and the prediction accuracy deviation is less than 10%. This reveals the dissolution acceleration mechanism of copper alloys under seawater environments, providing a theoretical basis for their corrosion protection design.

[0039] Compared with existing methods for predicting the corrosion rate of copper alloys, this invention has the following advantages:

[0040] This invention, through simulation calculations, can not only predict the corrosion rate of alloys but also provide in-depth analysis and understanding of the microscopic mechanisms involved in the corrosion process, such as electronic behavior and chemical reaction pathways. This in-depth understanding promotes innovation in new alloy design and provides a scientific basis for developing corrosion-resistant materials and improving structural design.

[0041] This invention obtains corrosion data of alloys under specific conditions through experiments and performs in-depth analysis using simulation calculations, making corrosion rate predictions more accurate and reliable. This process, by simulating corrosion reactions under different environmental parameters and supplementing it with experimental verification, significantly improves the accuracy of the prediction results.

[0042] The method of this invention effectively reduces the number and scale of experiments by optimizing experimental design and combining it with simulation calculations to predict the corrosion process. This combination of experimental and simulation calculation methods significantly improves the efficiency and accuracy of predicting alloy corrosion rates in flowing seawater environments, demonstrating significant practical value and broad application prospects. Attached Figure Description

[0043] The present invention will be further described below with reference to the accompanying drawings. The drawings are only for illustrative purposes and do not limit the scope of the present invention.

[0044] Figure 1 These are the XRD patterns of the MAB alloy under different seawater flow rates in Example 1.

[0045] Figure 2 This refers to the microstrain level and dislocation density of MAB alloys at different seawater flow rates in Example 1.

[0046] Figure 3 This is Example 1, which shows the microstructure model of the copper alloy under different seawater flow rates and the change in dissolution electrode potential caused by strain.

[0047] Figure 4 These are the surface energy and work function of the MAB alloy under atomic axial tensile strain in Example 1.

[0048] Figure 5 The activation energy barrier and dissolution rate of MAB alloy at different seawater flow rates are shown in Example 1.

[0049] Figure 6 This is the corrosion weight loss rate and corrosion rate prediction model of MAB alloy under different seawater flow rates in Example 1.

[0050] Figure 7 These are the XRD patterns of the B10 alloy under different seawater flow rates in Example 2.

[0051] Figure 8 This refers to the microstrain level and dislocation density of B10 alloy at different seawater flow rates in Example 2.

[0052] Figure 9 These are the surface energy and work function of the B10 alloy under atomic axial tensile strain in Example 2.

[0053] Figure 10 The activation energy barrier and dissolution rate of B10 alloy at different seawater flow rates are shown in Example 2.

[0054] Figure 11 This is the corrosion weight loss rate and corrosion rate prediction model of B10 alloy under different seawater flow rates in Example 2. Detailed Implementation

[0055] The following detailed description is based on specific embodiments, but the scope of protection of the present invention is not limited to the specific implementation methods.

[0056] Example 1: High-manganese aluminum bronze alloy (MAB) for propellers

[0057] The XRD diffraction peaks of MAB alloys under different seawater flow rates were analyzed using GSAS-II software, such as... Figure 1 As shown, micro-strain was determined by peak broadening, yielding the axial tensile strain and dislocation density of the alloy's internal lattice. With increasing seawater flow velocity (0-12 m / s), the axial tensile strain and dislocation density of the copper alloy gradually increased. Figure 2As shown, the atomic-level axial tensile strains of the MAB alloy under different seawater flow rates were 0.98%, 1.02%, 1.45%, 2.05%, 2.55%, and 3.32%, respectively. This indicates that high seawater flow rates increase surface structural defects in the alloy, leading to reduced corrosion resistance.

[0058] A 3×3×4 microstructure model of the MAB alloy was established using the DMol3 module of Materials Studio, with a lattice constant of . The alloy's elemental composition is CuAlMn, with copper, aluminum, and manganese in a ratio of 22:12:2. For example... Figure 3 As shown, the geometry is optimized using the PBE DFT method, with the z-axis direction of the model set... A vacuum layer is used to prevent interaction with adjacent plates. The surface and subsurface layers relax, while the bottom two layers remain fixed as the matrix. Tensile strain caused by seawater flow lowers the alloy's dissolution electrode potential, thus accelerating the corrosion process. Strain causes the atomic bonds on the alloy surface to stretch, weakening interatomic interactions and accelerating corrosion kinetics.

[0059] DFT calculations show that the surface energy of the MAB alloy increases with increasing strain under different elastic strains, indicating a higher energy state due to increased interatomic spacing. Microstrain induces a redistribution of surface electron density, altering the alloy's work function and chemical potential. Figure 4 As shown, with the increase of strain, the work function decreases from 4.84 eV to 4.62 eV. The decrease in work function indicates a negative shift in corrosion potential, increased surface activity, and accelerated dissolution of the copper alloy.

[0060] Simulating the activation energy barrier of copper alloy dissolution at different seawater flow velocities, such as Figure 5 As shown: (1) Initial state of MAB alloy (IS); (2) Cu atoms on the surface dissolve and leave metal vacancies on the surface (VAC1); (3) Cu atom migration transition state (TS); (4) Cu atoms in the subsurface spontaneously migrate to the surface vacancies, forming subsurface vacancies (VAC2); (5) Cu atoms further dissolve, forming a double-vacancy structure (FS). The increase in seawater flow velocity reduces the dissolution resistance of the alloy and significantly accelerates the dissolution kinetics process. Based on the transition state theory of the partition function (TST), by fitting the dissolution rate and activation energy barrier under different flow velocities, a linear correlation spectrum between the dissolution rate and the seawater flow velocity is obtained.

[0061] Based on establishing a linear relationship between dissolution rate and seawater flow velocity, and incorporating parameters such as the intrinsic diffusion coefficient D of copper atoms, correction coefficient k, and time conversion factor T, the dissolution rate was fitted to several pairs of different seawater flow velocity variables. The dissolution rate graph was then transformed into a predictive model for the corrosion rate of copper alloys under dynamic seawater conditions. Experimental verification was conducted in artificial seawater, measuring the corrosion weight loss rate of MAB alloys after immersion for 12 hours at different seawater flow velocities. The results show that the corrosion rate of the MAB alloy under axial tensile strain model in dynamic seawater conditions is basically consistent with the experimental corrosion rate, with a prediction accuracy deviation of less than 10%, achieving accurate prediction of the corrosion rate of copper alloys in complex seawater environments. Figure 6 As shown, the final fitting yields a corrosion rate prediction model for MAB alloys under dynamic seawater conditions: R 2 =0.998 (Correction coefficient k1 = 1.91 × 10) -7 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 , α=-20.34).

[0062] Example 2: B10 alloy for seawater pipelines

[0063] The XRD diffraction peaks of B10 alloy under different seawater flow rates were analyzed using GSAS-II software, such as... Figure 7 As shown, by determining the micro-strain through peak broadening, the axial tensile strain and dislocation density of the alloy's internal lattice were obtained. With increasing seawater flow velocity (0-4 m / s), the axial tensile strain and dislocation density of the copper-nickel alloy gradually increased. Figure 8 As shown, the atomic-level axial tensile strains of B10 alloy under different seawater flow rates were 0.23%, 0.25%, 0.30%, 0.36%, and 0.72%, respectively. This indicates that high seawater flow rates lead to an increase in surface structural defects in the B10 alloy and accelerate corrosion.

[0064] A 3×3×4 microstructure model of B10 alloy was established using the DMol3 module of Materials Studio, with a lattice constant of . The alloy has an elemental composition of CuNi, with a copper:nickel ratio of 24:12. The geometry was optimized using the PBE DFT method, and the model's z-axis direction was set... A vacuum layer is used to prevent interaction with adjacent plates. The surface and subsurface layers relax, while the bottom two layers remain fixed as the matrix. DFT calculations show that the surface energy of the B10 alloy increases with increasing strain under different elastic strains, indicating a higher energy state due to increased interatomic spacing. Figure 9As shown, with the increase of axial tensile strain, the work function decreases from 4.63 eV to 4.55 eV. The decrease in work function reflects the negative shift of corrosion potential, which accelerates the dissolution process of B10 alloy.

[0065] Simulation of the activation energy barrier for B10 alloy dissolution at different seawater flow velocities, such as Figure 10 As shown, increasing the seawater flow velocity from 0 to 4 m / s reduces the dissolution resistance of the alloy and accelerates the alloy dissolution kinetics. Based on the transition state theory (TST) of the partition function, a linear relationship between the dissolution rate and the seawater flow velocity is obtained by fitting the dissolution rate and activation energy barrier under different flow velocities.

[0066] Based on establishing a linear relationship between dissolution rate and seawater flow velocity, and incorporating parameters such as the intrinsic diffusion coefficient D of copper atoms, correction coefficient k, and time conversion factor T, the dissolution rate of several pairs of different seawater flow velocity variables was fitted to the dissolution rate. The dissolution rate spectrum of B10 alloy was then transformed into a corrosion rate prediction model under dynamic seawater conditions. Experimental verification was conducted in artificial seawater, measuring the corrosion weight loss rate of B10 alloy after immersion for 12 hours at different seawater flow velocities. The results show that the corrosion rate of B10 alloy under the axial tensile strain model in dynamic seawater conditions is basically consistent with the experimental corrosion rate. This further demonstrates that the model can accurately assess the influence of seawater flow on the material corrosion kinetics, enabling the simulation and prediction of the corrosion tendency of high-flow-velocity copper alloys, overcoming the difficulties of experimental measurement under high-flow-velocity conditions. Figure 6 As shown, the final fitting yields a corrosion rate prediction model for B10 alloy under dynamic seawater conditions: R 2 =0.996 (Correction coefficient k2 = 2.78 × 10) -9 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 , β=-0.29).

[0067] Figure 1 These are the XRD patterns of the MAB alloy under different seawater flow rates in Example 1. As the seawater flow rate increases from 0 to 12 m / s, the axial tensile strain and dislocation density of the MAB alloy (111) crystal plane increase.

[0068] Figure 2 This section describes the microstrain levels and dislocation densities of the MAB alloy at different seawater flow rates in Example 1. The atomic-level axial tensile strains of the MAB alloy at different seawater flow rates were 0.98%, 1.02%, 1.45%, 2.05%, 2.55%, and 3.32%, respectively. This indicates that high seawater flow rates cause changes in the surface structural defects of the alloy, accelerate the corrosion process of the copper alloy, and lead to a decrease in its corrosion resistance.

[0069] Figure 3 This is Example 1, showing the microstructure model of the copper alloy under different seawater flow rates and the strain-induced changes in the dissolution electrode potential. Seawater flow induces tensile strain on the alloy surface, reducing the dissolution electrode potential and accelerating the corrosion kinetics. This indicates that the micro-strain caused by seawater flow leads to the stretching of atomic bonds on the alloy surface and weakens the interactions between atoms, demonstrating a decrease in the stability of the copper alloy.

[0070] Figure 4 These are the surface energy and work function of the MAB alloy under atomic-axis tensile strain in Example 1. The results show that the surface energy of the alloy increases with increasing strain, the interatomic spacing increases, and it is in a high-energy state. Microstrain causes a redistribution of surface electron density, altering the work function and chemical potential. With increasing strain, the work function decreases, the corrosion potential shifts negatively, and the dissolution process of the copper alloy is accelerated.

[0071] Figure 5 This section describes the activation barrier and dissolution rate of MAB alloy at different seawater flow rates in Example 1. It demonstrates that increasing the flow rate reduces the dissolution resistance of the alloy and significantly accelerates the dissolution kinetics process. Based on the transition state theory (TST) of the partition function, a linear model of the dissolution rate versus the seawater flow rate is obtained by fitting the relationship between the dissolution rate and the activation barrier at different flow rates.

[0072] Figure 6 This is the corrosion weight loss rate and corrosion rate prediction model of MAB alloy under different seawater flow velocities in Example 1. The results show that the corrosion rate of MAB alloy increases significantly with increasing seawater flow velocity, indicating that seawater flow accelerates the corrosion process. Compared with the measured corrosion rate, this demonstrates that the model can effectively predict the corrosion behavior of MAB alloy under dynamic seawater conditions.

[0073] Figure 7 The images show the XRD patterns of the B10 alloy under different seawater flow rates in Example 2. As the seawater flow rate increases from 0 to 4 m / s, the axial tensile strain and dislocation density of the B10 alloy on the (111) crystal plane increase.

[0074] Figure 8 This refers to the microstrain level and dislocation density of the B10 alloy at different seawater flow rates in Example 2. The atomic-level axial tensile strain of the MAB alloy at different seawater flow rates were 0.23%, 0.25%, 0.30%, 0.36%, and 0.72%, respectively, indicating that high seawater flow rates cause changes in the surface structural defects of the alloy.

[0075] Figure 9These are the surface energy and work function of the B10 alloy under atomic axial tensile strain in Example 2. The results show that the surface energy of the alloy increases with increasing strain, the interatomic spacing on the surface increases, and it is in a high-energy state. Microstrain causes a redistribution of surface electron density, and the increase in axial tensile strain leads to a decrease in work function, a negative shift in corrosion potential, and accelerates the dissolution process of the B10 alloy.

[0076] Figure 10 This section describes the activation energy barrier and dissolution rate of B10 alloy at different seawater flow rates in Example 2. It demonstrates that increasing the flow rate reduces the dissolution resistance of the alloy and significantly accelerates the dissolution kinetics process. Based on the transition state theory (TST) of the partition function, a linear model of the dissolution rate versus the seawater flow rate is obtained by fitting the relationship between the dissolution rate and the activation energy barrier of B10 alloy at different flow rates.

[0077] Figure 11 This is the corrosion weight loss rate and corrosion rate prediction model of B10 alloy under different seawater flow velocities in Example 2. The results show that the corrosion rate of B10 alloy increases significantly with increasing seawater flow velocity, indicating that seawater flow accelerates the corrosion process. Compared with the measured corrosion rate, this demonstrates that the model can effectively predict the corrosion behavior of B10 alloy under dynamic seawater conditions.

[0078] The above detailed embodiments describe the basic principles and main features of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and any changes or modifications conceived without creative effort should be covered within the scope of protection of the present invention. Various changes and modifications can be made to the present invention without departing from its scope, and all such changes and modifications will fall within the scope of protection claimed.

Claims

1. A method for evaluating the failure of copper alloy materials under different seawater flow velocities, characterized in that, Includes the following steps: S1. Analysis of Atomic-Level Axial Tensile Strain of Copper Alloy: Based on the X-ray diffraction (XRD) test results of copper alloy after corrosion by different seawater flow rates, the micro-strain values ​​were determined by analyzing the diffraction peak shape and using peak broadening, thereby obtaining the axial tensile micro-strain and dislocation density of the internal lattice of the alloy. By determining the full width at half maximum (FWHM) β and Bragg angle θ of the diffraction peaks, the axial tensile microstrain ε of the copper alloy structure under different seawater flow velocities is calculated according to formula (1): (1) The diffraction peak broadening caused by grain size was calculated using the Scherrer formula, where K is the shape factor and is taken as 0.9, and λ is the X-ray wavelength. Based on formulas (2) and (3), the grain size d and dislocation density ρ of the copper alloy under different seawater flow velocities were determined: (2) (3) As the seawater flow velocity increases, the axial tensile strain and dislocation density of copper alloys increase, indicating that high seawater flow velocity will cause changes in the surface structural defects of the alloy, accelerate the corrosion process of copper alloys, and reduce their corrosion resistance. S2. Quantitatively simulate the mechanical effects of different seawater flow velocities on the alloy surface. Based on the axial tensile micro-strain ε determined in S1, establish a microstructure model of copper alloy with different seawater flow velocities through atomic-level axial tensile strain: By adjusting the lattice axial parameters, apply strain along the (111) crystal plane direction. By precisely controlling the lattice constant of the copper alloy in the seawater environment, gradually increase the lattice parameters in the (111) direction, introduce axial tensile strain corresponding to the increase in flow velocity, and keep the lattice parameters in other directions unchanged, thereby achieving atomic-level strain control applied to the (111) crystal plane. S3. Calculation of copper alloy dissolution potential or copper alloy dissolution potential shift under different seawater flow velocities in dynamic seawater environment: Based on the axial tensile microstrain determined in S1 and the microstructure model under different seawater flow velocities established in S2, the energy of the alloy vacancy model under different flowing seawater is calculated, and then the copper alloy dissolution potential or copper alloy dissolution potential shift under different seawater flow velocities is obtained. By determining the energy of the alloy model without axial tensile strain Energy of alloy model under axial tensile strain Energy of alloy vacancy model without axial tensile strain Energy of alloy vacancy model under axial tensile strain The shift in the metal dissolution electrode potential caused by the introduction of tensile strain in copper alloys is calculated according to formula (4). : (4)； By describing the dissolution electrode potential of metals during corrosion, the dissolution tendency of copper alloys in flowing seawater is quantitatively analyzed. As the seawater flow rate increases, the dissolution electrode potential of copper alloys shifts to the negative direction, resulting in a decrease in the metal dissolution potential and a decline in corrosion resistance. This method is suitable for simulating the corrosion behavior of copper alloys in dynamic seawater environments. S4. Calculation of surface energy and work function of copper alloy under different seawater flow rates in dynamic seawater environment: Based on S1-S3, by constructing the (111) crystal plane alloy structure model under different axial tensile strains, energy minimization calculation is performed to obtain the energy state of the alloy surface. By calculating the potential of the alloy model under different seawater flow rates and the contact potential difference between it and the seawater interface, the influence of seawater flow rate on the surface structure and stability of copper alloy, i.e. the corresponding work function, is quantitatively analyzed. By determining the total energy of the S2 tensile surface model with different axial directions and alloy body phase atoms Average energy E bulk The surface energy state E of the alloy under different seawater flow velocities is calculated according to formula (5). surf : (5) Through the contact potential difference at the interface between copper alloy and seawater Based on the potential values ​​ψ of the alloy model at different seawater flow velocities, the work function Φ required for the copper alloy to remove surface electrons at different seawater flow velocities is calculated according to formula (6): (6) As the seawater flow velocity increases, the surface energy of the copper alloy increases, the work function decreases, the atomic energy state of the alloy surface rises, and electrons are more likely to escape from the surface, indicating that the flowing seawater accelerates the corrosion kinetics of the alloy. S5. Calculation of dissolution activation energy barrier and dissolution rate of copper alloy under different seawater flow velocities in dynamic seawater environment: Based on S1-S4, the dissolution activation energy barrier of copper alloy atoms under different flow velocities is quantitatively analyzed using the transition state search method, and then the dissolution rate is calculated. The dissolution activation energy barrier ΔE(t) of the alloy under different seawater flow velocities was obtained through transition state search, where σ is the degeneracy of the reaction path, taking a value of 1, and P... 0 The standard pressure in the gas phase is 0.1 MPa, t is the corresponding room temperature or atmospheric temperature, and h is Planck's constant of 6.626 × 10⁻⁶. -34 J·s,k b The Boltzmann constant is 1.381 × 10⁻⁶. -23 J.K. -1 R is the universal gas constant, 8.314 J·K. -1 ·mol -1 In the unimolecular reaction, Δn = 0. The dissolution rate k under different seawater flow rates is calculated according to formula (7). TST : (7) As the seawater flow velocity increases, the dissolution activation energy barrier decreases significantly, the dissolution resistance of metal atoms decreases, and the dissolution rate increases accordingly. This allows for accurate assessment of the influence of atomic-level axial tensile strain on the corrosion kinetics of alloys under different seawater flow velocities, enabling the simulation and prediction of the corrosion tendency of copper alloys under high flow velocity environments.

2. The method according to claim 1, characterized in that, Copper alloy types include the manganese-aluminum bronze alloy MAB for propellers and the copper-nickel alloy B10 for seawater pipelines; In S1, the seawater flow velocity of the manganese aluminum bronze alloy MAB used for the propeller is 0-12 m / s; In S1, the seawater flow velocity of the copper-nickel alloy B10 used in the seawater pipeline is 0-4 m / s.

3. The method according to claim 1, characterized in that, In S2, a microstructure model of copper alloy is established based on atomic-level axial tensile strain. The method for simulating seawater flow velocity is as follows: the axial tensile strain values ​​of copper alloy at different seawater flow velocities are obtained by XRD analysis. The microstructure model of copper alloy is established by density functional theory (DFT). The axial parameters of the lattice are precisely controlled to apply strain. A 15Å vacuum layer is established in the z direction of the (111) crystal plane. The top two atomic simulation alloy surfaces are released. At the same time, the internal structure of other atomic simulation alloy layers is fixed. The lattice parameters in other directions are kept unchanged. The axial lattice parameters are gradually increased. The axial tensile strain corresponding to the increase of flow velocity is introduced to achieve atomic-level strain control of copper alloy.

4. The method according to claim 1, characterized in that, The simulation calculation methods for the corrosion kinetics characteristics of copper alloys under different seawater flow velocities in S3-S5 are as follows: Geometric optimization is performed using the PBE generalized gradient approximation (GGA) method in the Materials Studio simulation package. The Brillouin zone of the alloy surface is sampled using the Monkhorst-Pack method on a 2×2×1 k-point grid. An implicit seawater solvation model is established by using a COSMO-like conductor shielding model and simulating the seawater environment using the seawater dielectric constant. The relativistic effects of nuclear electrons are handled using the DFT semi-nuclear pseudopotential (DSPP) method. The basis set is a dual numerical plus polarized DNP. In the structural optimization, the convergence tolerance and the self-consistent field SCF convergence criterion are set to 2.72 × 10⁻⁶. -3 eV was used to calculate the corrosion kinetics characteristic parameters of copper alloys in a dynamic seawater environment.

5. The method according to claim 1, characterized in that, In S5, the calculation methods for the dissolution rate and corrosion rate of copper alloy under different seawater flow rates are as follows: The equivalent dissolution activation energy barrier of the transition state theory (TST) is adopted, and the dissolution transition state of copper alloy under seawater environment is optimized by the linear simultaneous transfer of LST and the secondary simultaneous transfer of QST. The dissolution rate is calculated based on the Sobereva method, and a linear relationship between the dissolution rate and the activation energy barrier is established.

6. A method for establishing a copper alloy corrosion rate prediction model based on atomic-level axial tension under dynamic seawater environment, characterized in that, Based on the axial tensile strain model of S1-S2 copper alloy under different seawater flow rates as described in claim 1, the dissolution activation energy barrier is determined by transition state search. A linear relationship between the dissolution rate and the activation energy barrier is established according to formula (7), and the dissolution rate of copper alloy under different seawater flow rates is obtained. Combining the intrinsic diffusion coefficient D of copper atoms, the correction coefficient k, and the time conversion factor T, several pairs of different seawater flow rate variables are fitted with the dissolution rate x, and the dissolution rate spectrum is transformed into a relationship model between seawater flow rate and copper alloy corrosion rate y under dynamic seawater environment. The unit is mm / a (millimeters per year), where k is the correction coefficient, D is the intrinsic diffusion coefficient, T is the time conversion factor, α is the fitting coefficient, and C is a parameter related to the alloy, which can be obtained by fitting x with the dissolution rate, thus achieving accurate prediction of the corrosion rate of copper alloys in complex seawater environments.

7. The method according to claim 6, characterized in that, The calculation methods for the dissolution rate and corrosion rate of copper alloys under different seawater flow velocities are as follows: The equivalent dissolution activation energy barrier of the transition state theory (TST) is adopted, and the dissolution transition state of copper alloys under seawater environment is optimized by the linear simultaneous transfer (LST) and the secondary simultaneous transfer (QST) methods. The dissolution rate is calculated based on the Sobereva method, and a linear relationship between the dissolution rate and the activation energy barrier is established. The intrinsic diffusion coefficient of copper atoms obtained by the Sutherland equation is used to transform the relationship between seawater flow velocity and dissolution rate into a prediction model of corrosion rate under dynamic seawater environment.

8. The method according to claim 6, characterized in that, Corrosion rate prediction model for MAB alloys in dynamic seawater environments: The correction coefficient k1 = 1.91 × 10 -7 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 α = -20.34; Corrosion rate prediction model for B10 alloy in dynamic seawater environment: The correction factor k2 = 2.78 × 10 -9 The intrinsic diffusion coefficient of copper atoms, D, is 1.06 × 10⁻⁶. -7 The time conversion factor T = 3.15 × 10 7 , β=-0.29.

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