Finite element modeling method of random corrosion component and storage medium

Abstract

The invention relates to a finite element modeling method for a random corrosion component, a storage medium and finite element software, a finite element model of an uncorroded component is established, and parameters a and b related to the corrosion degree and upper limit cut-off wave numbers of a random field in x and y directions are calculated according to the average corrosion depth and standard deviation of the random corrosion component; determining the number Mt and Nt of nodes according to the component size and the grid size; representing a corrosion depth random field by using a second type of random harmonic function so as to calculate the corrosion depth of each node; and finally, shifting the nodes of the uncorroded component model along the thickness direction according to the calculated depth so as to finish the modeling of the random corrosion model. Compared with the prior art, the method overcomes the problems of complex model, difficult grid division, long calculation time, non-convergence and the like caused by the existing random corrosion modeling method such as Boolean cutting, can accurately simulate random corrosion and reduce the modeling difficulty and calculation cost, and can be applied to the fields of engineering mechanical property analysis and the like.

Description

Technical Field

[0001] The invention relates to the technical field of computer-aided engineering, and in particular to a finite element modeling method and a storage medium for a random corrosion component. Background Art

[0002] In the field of engineering mechanics performance analysis, the finite element method occupies an extremely important position due to its high precision. When using the finite element method to solve the mechanical properties of corroded components, traditional modeling methods often assume uniform corrosion as a prerequisite for modeling. However, the actual corrosion situation often presents the characteristics of random corrosion. This assumption of uniform corrosion is significantly different from the actual situation, making it difficult to accurately simulate the actual scene, resulting in deviations between the analysis results and the mechanical performance of the actual components.

[0003] Although some studies have attempted to use random corrosion for finite element modeling, the most common one is the Boolean cutting method. However, this method has many disadvantages. The generated model structure is complex and faces many difficulties in meshing. This not only greatly prolongs the calculation time, but also easily leads to non-convergence during the solution process, which seriously affects the efficiency and accuracy of modeling and analysis. The existing traditional modeling methods are unable to effectively solve these problems and cannot meet the engineering practice's requirements for efficient and accurate finite element modeling of random corrosion components. In this context, it is particularly important to develop a finite element modeling method for random corrosion components that can overcome the above defects. It has a practical significance that cannot be ignored for improving the accuracy of engineering mechanics performance analysis and promoting the development of related fields. Summary of the invention

[0004] The purpose of the present invention is to provide a finite element modeling method and storage medium for random corrosion components in order to overcome the defects of the above-mentioned prior art. Under the premise of ensuring the accuracy of finite element modeling, the present invention overcomes the problems of difficulty in modeling irregular random corrosion components, complex meshing, non-convergence of calculation results, and excessive calculation time. The present invention reduces the difficulty of finite element modeling of random corrosion components and saves calculation time.

[0005] The invention conception process of the present invention includes:

[0006] The second kind of random harmonic function is used to characterize the random field of corrosion depth, and the corrosion depth of each finite element node is calculated. Then, the finite element modeling of random corroded components is realized by node offset on the uncorroded finite element model.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] Based on the solid unit finite element modeling method.

[0009] Based on the traditional modeling method, the corroded component is modeled before corrosion, and then the corrosion characteristics are introduced.

[0010] Based on the meshing of non-corroded components, the random field of corrosion depth is characterized by the second kind of random harmonic function, and the corrosion depth of each node of the finite element model is calculated.

[0011] The corrosion characteristics are introduced into the model of the non-corroded component to achieve the purpose of simulating component corrosion.

[0012] The purpose of the present invention can be achieved by the following technical solutions:

[0013] The present invention provides a finite element modeling method for a random corrosion component, comprising the following steps:

[0014] S1: Establish a finite element model of the uncorroded component using finite element software;

[0015] S2: Calculate the parameters a and b related to the degree of corrosion based on the average depth and standard deviation of the randomly corroded components, where a is related to the peak value of the power spectrum density and b is related to the upper limit of the harmonic component wave number;

[0016] S3: According to the average depth and standard deviation of the corrosion of the random corrosion component, the upper cutoff wave number ω of the random field in the x and y directions is calculated. 1u ,ω 2u ;

[0017] S4: According to the size of the randomly corroded component and the size of the grid, calculate the number of nodes M in the x and y directions to determine the corrosion depth t 、N t ;

[0018] S5: Based on the corrosion depth random field function and the number of nodes M obtained in S4 t 、N t , calculate the corrosion depth of each node;

[0019] S6: Based on the corrosion depth of each node obtained in S5, the nodes of the finite element model of the uncorroded component are offset to a corresponding depth in the component along the thickness direction to complete the random corrosion modeling.

[0020] Further, in S1, the process of establishing the finite element model of the uncorroded component includes: establishing a geometric model, defining materials, assigning materials, dividing meshes, setting analysis steps, setting loads and boundary conditions;

[0021] In S1, the finite element model of the uncorroded component was established using the commercial finite element software ABAQUS;

[0022] In S1, solid elements were used for modeling when establishing the finite element model of the uncorroded structure.

[0023] Furthermore, in S2, when there are test data, the parameters a and b related to the corrosion degree are fitted according to the results of the component corrosion test, where a is related to the peak value of the power spectrum density and b is related to the upper limit of the harmonic component wave number;

[0024] The intervals of scanning corrosion depth in x and y directions are Δx and Δy respectively. The two-dimensional discrete Fourier transform F(ω 1p ,ω 2q ) is obtained by the following formula:

[0025]

[0026] Where M and N are the number of points in the x and y directions where the corrosion depth needs to be measured, respectively. m and n are summation variables used to traverse all measurement points. p = 0, 1, ..., M-1; q = 0, 1, ..., N-1, ω 1p ,ω 2q is the pth and qth harmonic component wave number in the x and y directions, in rad / mm; the discrete bilateral spectral density S(ω 1P ,ω 2q ) is calculated by the following formula:

[0027]

[0028] Assuming that the distribution characteristics of the corrosion surface in all directions are the same, the power spectrum density S(ω1, ω2) of the corrosion depth is fitted using the following formula to obtain the values ​​of parameters a and b:

[0029]

[0030] In the formula, t sd is the standard deviation of the corrosion depth of the component, and a and b are the parameters fitted according to the test results.

[0031] Furthermore, in S2, when there is no corresponding test data for fitting, the values ​​of a and b are calculated according to the following formula:

[0032] a=2.33*(1-exp(-0.07656*t_e 0.64 ))

[0033] b=0.62*a

[0034] Where t_e is the average depth of component corrosion, and a and b are dimensionless parameters related to the degree of corrosion.

[0035] Furthermore, in S3, the upper cutoff wave number ω of the random field in the x and y directions is determined 1u ,ω2u , determined by the following criteria:

[0036]

[0037] In the formula, ∈<<1, for example 0.001.

[0038] Further, in S4, the specific steps include: measuring the actual size of the random corrosion component in the x and y directions, and obtaining the specific size information of the grid divided in the x and y directions of the component during finite element modeling, and then dividing the component size by the grid size according to the corresponding relationship between the component size and the grid size to determine the number of nodes M in the x direction to determine the corrosion depth t And the number of nodes N in the y direction t .

[0039] Further, in S5, the corrosion depth random field function is as follows:

[0040]

[0041] ω 1p =p△ω1,△ω1=2π / L x , M c =ω 1u / △ω1

[0042] ω 2q =q△ω2,△ω2=2π / L y , N c =ω 2u / △ω2

[0043] Where ξ(x, y) is the deviation from the average corrosion depth, ω 1u ,ω 2u is the upper cutoff wave number of the random field in the x and y directions, θ 1pq ,θ 2pq is a random phase angle uniformly distributed between [0, 2π], L x , L y M is the plane size of the component in the x and y directions, c 、N c is the number of harmonic components in the x and y directions.

[0044] Furthermore, in S5, the actual corrosion depth corresponding to each point is calculated by the following formula:

[0045] ξ(x, y) = z(x, y) - t_e

[0046] Where ξ(x, y) is the deviation from the average corrosion depth, z(x, y) is the actual corrosion depth, and t_e is the average corrosion depth.

[0047] Furthermore, S6 specifically includes the following steps:

[0048] The corrosion depth data of each node calculated in S5 is obtained, and then the position information of each node in the finite element model of the uncorroded component is identified. Then, according to the corrosion depth value of the corresponding node, the node located on the corrosion surface is accurately offset by the corresponding depth in the direction perpendicular to the corrosion surface and toward the inside of the component. For the internal nodes of the component, the offset distance is determined according to the number of layers and the number of layers divided in the thickness direction, and the offset is made in the same direction. By performing such offset operations on all nodes, the modeling of the random corrosion model is finally completed.

[0049] A second aspect of the present invention provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, is used to perform the finite element modeling method for a random corrosion component as described above.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1) Accurately simulate real corrosion characteristics: By introducing a random corrosion field to generate specific values ​​for each random corrosion pit, it can maintain consistency in time and space, effectively describe ergodicity, and reflect the influence of texture directionality and wavelength on the root mean square deviation of surface roughness. This is significantly better than the traditional uniform corrosion modeling assumption, and more accurately simulates the characteristics of real corroded components, providing a more reliable data basis for engineering mechanics performance analysis.

[0052] 2) Reduce the difficulty and complexity of modeling: The present invention reflects the characteristics of random corrosion by performing node offset on the original non-corroded components, cleverly avoiding various thorny problems faced when directly performing finite element meshing on complex spatial structures, such as complex model structure and difficult meshing, which greatly reduces the difficulty of finite element modeling of random corroded components and improves modeling efficiency.

[0053] 3) Save simulation calculation time and cost: Under the premise of ensuring the accuracy of composite material finite element modeling, the calculation time is significantly shortened. Compared with the problems faced by traditional random corrosion modeling methods such as Boolean cutting, such as long calculation time and non-convergence of the solution process, this invention effectively optimizes the calculation process, reduces the consumption of computing resources, and reduces the time cost of simulation calculation, which is conducive to more efficient related analysis work in engineering practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the process of the finite element modeling method of the random corrosion component in the example of the present invention;

[0055] Figure 2It is a comparison diagram before and after the random corrosion is introduced into the finite element modeling method of the random corrosion component in the example of the present invention;

[0056] Figure 3 It is a comparison diagram before and after random corrosion is introduced into a cross section of a random corrosion component finite element modeling method example in the example of the present invention. DETAILED DESCRIPTION

[0057] In general, the present invention discloses a finite element modeling method for randomly corroded components. According to the random distribution characteristics of the corrosion depth and the power spectrum density of the randomly corroded components, the random field of the corrosion depth is characterized by the second-class random harmonic function, so as to obtain the specific corrosion depth corresponding to each position of the component. After the solid unit finite element model of the uncorroded component is established by the commercial finite element software ABAQUS, the effect of simulating random corrosion is achieved by offsetting the nodes. While ensuring the accuracy of the finite element modeling, the present invention overcomes the problems of difficulty in modeling the irregular randomly corroded component model, complex mesh division, non-convergence of the calculation results, and excessively long calculation time. The present invention reduces the difficulty of finite element modeling of randomly corroded components and saves calculation time.

[0058] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. Component models, material names, connection structures, control methods, algorithms and other features not clearly described in this technical solution are all considered to be common technical features disclosed in the prior art.

[0059] Example 1

[0060] The specific dimensions used in this embodiment are only for illustrating the technical solution and do not limit the protection scope of the present invention.

[0061] Figure 1 The finite element modeling method for random corrosion components in the present invention is a flow chart of the method. Figure 2 The finite element model of the uncorroded component shown in the figure mainly includes: establishing a geometric model, defining materials, assigning materials, dividing the mesh, setting analysis steps, setting loads and boundary conditions. The modeling uses solid elements.

[0062] Determine the average corrosion depth t_e and the standard deviation of the corrosion depth t sd After that, the corrosion depth random field is established. In order to reduce the bias effect, the data used to establish the corrosion depth random field is data with a mean of 0.

[0063] ξ(x, y) = z(x, y) - t_e

[0064] Where ξ(x, y) is the deviation from the average corrosion depth, z(x, y) is the actual corrosion depth, and t_e is the average corrosion depth.

[0065] According to the results of the component corrosion test, the parameters a and b related to the degree of corrosion are fitted, where a is related to the peak value of the power spectrum density and b is related to the upper limit of the harmonic component wave number. The values ​​of a and b are calculated according to the following formula:

[0066] a=2.33*(1-exp(-0.07656*t_e 0.64 ))

[0067] b=0.62*a

[0068] Where te is the average depth of component corrosion, and a and b are dimensionless parameters related to the degree of corrosion.

[0069] Determine the upper cutoff wave number ω of the random field in the x and y directions 1u ,ω 2u , determined by the following criteria:

[0070]

[0071] Where S(ω1, ω2) is the power spectral density of corrosion depth, ∈<<1, for example 0.001.

[0072] In programming, it is simplified to let ω 1u After ∞, determine ω 2u , we can obtain ω in the same way 1u The value of .

[0073] The corrosion depth random field function ξ(x, y) can be calculated by the following formula based on the above obtained data:

[0074]

[0075] ω 1p =pΔω1, Δω1=2π / L x , M c =ω 1u / △ω1

[0076] ω 2q =qΔω2,Δω2=2π / L y , N c =ω 2u / △ω2

[0077] Where ξ(x, y) is the deviation from the average corrosion depth, ω 1u ,ω 2u is the upper cutoff wave number of the random field in the x and y directions, θ 1pq ,θ 2pq is a random phase angle uniformly distributed between [0, 2π], L x , L yM is the plane size of the component in the x and y directions, c 、N c is the number of harmonic components in the x and y directions.

[0078] To find the true corrosion depth corresponding to each point, add the average corrosion depth after calculating the data corresponding to each node.

[0079] ξ(x, y) = z(x, y) - t_e

[0080] Where ξ(x, y) is the deviation from the average corrosion depth, z(x, y) is the actual corrosion depth, and t_e is the average corrosion depth.

[0081] Export the inp file corresponding to the finite element model of the uncorroded component generated by the traditional modeling method. Read the node information through Python, which includes the node number and its position coordinates. According to the geometric relationship of the component and the read node coordinate position, Python can be used to determine the nodes on the corroded surface of the corroded component, the nodes inside the component, the nodes on the uncorroded surface, the vectors perpendicular to the corroded surface and facing the inside of the component, and other information.

[0082] Modify the node coordinates in the inp file through python to simulate the effect of random corrosion. According to the corrosion depth corresponding to each node, the nodes of the corrosion surface are offset in the direction perpendicular to the corrosion surface and toward the inside of the component by the corresponding corrosion depth. If it is a node located inside the component, the node offset is also required to prevent unit singularity. Due to the mesh division, the component may be divided into multiple layers in the thickness direction. Determine which layer the internal node of the component is located in the thickness direction. Here, the corrosion surface is defined as the 0th layer, and it increases layer by layer along the thickness direction, such as Figure 3 As shown. Then the node located inside the component corresponds to the offset distance z c (x, y) is found by the following formula:

[0083] z c (x, y) = (dc) * z (x, y) / d

[0084] In the formula, z c (x, y) is the distance to be offset for the c-th layer node, c is the layer number where the node is located, d is the total number of layers divided in the thickness direction (starting from the corrosion surface as layer 0), and z(x, y) is the actual corrosion depth.

[0085] The offset direction of the internal node of the component is the same as the offset direction of the corrosion surface, that is, it is offset in the direction perpendicular to the surface of the layer where the node is located toward the inside of the component.

[0086] Import the modified inp file into the finite element software to obtain the finite element model of the corroded component.

[0087] Example 2

[0088] This embodiment also includes a storage medium of computer executable instructions, which, when executed by a computer processor, is used to perform the finite element modeling method for the random corrosion component as described above.

[0089] First, the computer processor will start the commercial finite element software ABAQUS according to the instructions in the storage medium, and strictly follow the established steps to establish the finite element model of the uncorroded component, including accurately establishing the geometric model, reasonably defining the material, accurately assigning the material, carefully dividing the grid, scientifically setting the analysis steps, appropriately setting the load and boundary conditions, and ensuring the use of solid elements for modeling, laying a solid foundation for subsequent corrosion simulation.

[0090] Then, according to the instructions of the storage medium, the computer processor will obtain the average depth and standard deviation data of the corrosion of the random corrosion component, and use this as a basis to accurately calculate the parameters a and b related to the degree of corrosion, where a is closely related to the peak value of the power spectrum density, and b is closely related to the upper limit of the harmonic component wave number; at the same time, the upper limit cutoff wave number of the random field in the x and y directions will also be calculated. Then, based on the size of the random corrosion component and the size information of the divided grid, the number of nodes M in the x and y directions that need to determine the corrosion depth is calculated. t 、N t .

[0091] Then, the second type of random harmonic function is used, combined with the various parameters calculated previously, to characterize the corrosion depth random field, and then calculate the corrosion depth of each node. In this process, in order to reduce the deviation effect, the corrosion depth random field data with a mean of 0 will be established first. After calculating the corresponding data of each node, the average corrosion depth is added to obtain the final accurate corrosion depth value.

[0092] Finally, the computer processor again offsets the nodes corresponding to the finite element model of the uncorroded component to the corresponding depth inside the component along the thickness direction according to the storage medium instructions, completing the modeling of the random corrosion model. For the internal nodes of the component, the appropriate offset distance will be determined based on the information such as the number of layers it is in to prevent the occurrence of unit singularity and other problems, thereby successfully constructing a finite element model that can accurately simulate the random corrosion component, providing a high-quality model foundation for subsequent related applications such as mechanical properties analysis, greatly improving the efficiency, accuracy and repeatability of the finite element modeling of random corrosion components, and has extremely broad application prospects in engineering design and analysis and other fields.

[0093] The above description of the embodiments is to facilitate the understanding and use of the invention by those skilled in the art. It is obvious that those skilled in the art can easily make various modifications to these embodiments and apply the general principles described herein to other embodiments without creative work. Therefore, the present invention is not limited to the above embodiments, and improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the present invention should be within the scope of protection of the present invention.

Claims

1. A finite element modeling method for a random corrosion component, characterized in that: The following steps are involved: S1: Establish a finite element model of the uncorroded component using finite element software; S2: Calculate the parameters a and b related to the degree of corrosion based on the average depth and standard deviation of the randomly corroded components, where a is related to the peak value of the power spectrum density and b is related to the upper limit of the harmonic component wave number; S3: According to the average depth and standard deviation of the corrosion of the random corrosion component, the upper cutoff wave number ω of the random field in the x and y directions is calculated. 1u ,ω 2u ; S4: According to the size of the randomly corroded component and the size of the grid, calculate the number of nodes M in the x and y directions to determine the corrosion depth t 、N t ; S5: Based on the corrosion depth random field function and the number of nodes M obtained in S4 t 、N t , calculate the corrosion depth of each node; S6: Based on the corrosion depth of each node obtained in S5, the nodes of the finite element model of the uncorroded component are offset to a corresponding depth in the component along the thickness direction to complete the random corrosion modeling.

2. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: In S1, the process of establishing the finite element model of the uncorroded component includes: establishing the geometric model, defining materials, assigning materials, dividing the mesh, setting the analysis steps, setting the loads and boundary conditions; In S1, the finite element model of the uncorroded component was established using the commercial finite element software ABAQUS; In S1, solid elements were used for modeling when establishing the finite element model of the uncorroded structure.

3. The finite element modeling method for a random corrosion component according to claim 1 is characterized in that: In S2, when there are test data, the parameters a and b related to the corrosion degree are fitted according to the results of the component corrosion test, where a is related to the peak value of the power spectrum density and b is related to the upper limit of the harmonic component wave number; The intervals of scanning corrosion depth in x and y directions are Δx and Δy respectively. The two-dimensional discrete Fourier transform F(ω 1p ,ω 2q ) is obtained by the following formula: Where M and N are the number of points in the x and y directions where the corrosion depth needs to be measured, respectively. m and n are summation variables used to traverse all measurement points. p = 0, 1, ..., M-1; q = 0, 1, ..., N-1, ω 1p ,ω 2q is the pth and qth harmonic component wave number in the x and y directions, in rad / mm; the discrete bilateral spectral density S(ω 1P ,ω 2q ) is calculated by the following formula: Assuming that the distribution characteristics of the corrosion surface in all directions are the same, the power spectrum density S(ω1, ω2) of the corrosion depth is fitted using the following formula to obtain the values ​​of parameters a and b: Where, t sd is the standard deviation of the corrosion depth of the component, and a and b are the parameters fitted according to the test results.

4. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: In S2, when there is no corresponding test data for fitting, the values ​​of a and b are calculated according to the following formula: a=2.33*(1-exp(-0.07656*t_e 0.64 )) b=0.62*a Where t_e is the average depth of component corrosion, and a and b are dimensionless parameters related to the degree of corrosion.

5. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: In S3, determine the upper cutoff wave number ω of the random field in the x and y directions 1u ,ω 2u , determined by the following criteria: In the formula, ∈<<1.

6. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: In S4, the specific steps include: measuring the actual size of the random corroded component in the x and y directions, and obtaining the specific size information of the grid divided in the x and y directions of the component during finite element modeling, and then determining the number of nodes M in the x direction to determine the corrosion depth by dividing the component size by the grid size according to the corresponding relationship between the component size and the grid size. t And the number of nodes N in the y direction t .

7. The finite element modeling method for a random corrosion component according to claim 3 is characterized in that: In S5, the corrosion depth random field function is as follows: oh 1p =pΔω1,Δω1=2π / L x ,M c =ω 1u / Give1 oh 2q =qΔω2,Δω2=2π / L y ,N c =ω 2u / D2 Where ξ(x,y) is the deviation from the average corrosion depth, ω 1u ,ω 2u is the upper cutoff wave number of the random field in the x and y directions, θ 1pq ,θ 2pq is a random phase angle uniformly distributed between [0,2π], L x , L y M is the plane size of the component in the x and y directions, c 、N c is the number of harmonic components in the x and y directions.

8. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: In S5, the actual corrosion depth corresponding to each point is calculated by the following formula: ξ(x,y)=z(x,y)-t_e Where ξ(x,y) is the deviation from the average corrosion depth, z(x,y) is the actual corrosion depth, and t_e is the average corrosion depth.

9. The finite element modeling method for a random corrosion component according to claim 1, characterized in that: S6 specifically includes the following steps: The corrosion depth data of each node calculated in S5 is obtained, and then the position information of each node in the finite element model of the uncorroded component is identified. Then, according to the corrosion depth value of the corresponding node, the node located on the corrosion surface is accurately offset by the corresponding depth in the direction perpendicular to the corrosion surface and toward the inside of the component. For the internal nodes of the component, the offset distance is determined according to the number of layers and the number of layers divided in the thickness direction, and the offset is made in the same direction. By performing such offset operations on all nodes, the modeling of the random corrosion model is finally completed.

10. A storage medium containing computer executable instructions, characterized in that: When the storage medium of the computer executable instructions is executed by a computer processor, it is used to perform the finite element modeling method of the random corrosion component as described in any one of claims 1 to 9.

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