A blade stratification post-processing method based on ABAQUS

Abstract

This invention provides a blade layering post-processing method based on ABAQUS. The method defines post-processing parameters according to preset conditions, extracts initial data from the model in ABAQUS software, further calculates the failure index, and simplifies the extracted data significantly based on classical laminate theory without losing accuracy. Finally, it classifies and outputs failure index reports based on the relationships between layers, materials, elements, strain, and nodal coordinates, and allows for the free selection of three levels: global, component, and layer, to plot failure index cloud maps. This method significantly reduces the time for post-processing extraction, calculation, and output, lowers the difficulty of classification management and iterative adjustments, shortens the development cycle, and provides more room for cost reduction.

Description

Technical Field

[0001] This invention relates to the field of wind turbine blade structure simulation technology, specifically to a blade layering post-processing method based on ABAQUS. Background Technology

[0002] The new energy industry is developing rapidly, and the requirements for cost reduction and capacity expansion are becoming increasingly stringent. Blade length is increasing rapidly, and blades exceeding 100m in length have become a thing of the past. With the accelerated iteration of blades, blade simulation technology is also developing rapidly, and automation and precision have become basic requirements for blade simulation verification.

[0003] The post-processing methods for finite element verification of blades in the industry have to be simplified due to issues such as large data volume and complex layup. Although batch processing tools are available, problems such as extraction speed, classification difficulties, and computational efficiency still result in long processing times. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention proposes a method to solve the technical problems of the loss of intermediate layers due to oversimplification in the post-processing process, and the long time consumption.

[0005] A blade layered post-processing method based on ABAQUS includes: reading initial data, which includes single-layer material characteristics, element and strain information in the result file, and element, cross-section, node, and model material library information in the model file; defining post-processing parameters according to preset conditions, which include industry standards and layered output requirements, and the post-processing parameters include layer name prefixes; calculating failure indices based on the initial data and the post-processing parameters, which include fiber failure index, inter-fiber failure index, and fatigue failure index; selecting initial data and its corresponding failure index based on the layer name prefix for layered output according to the preset conditions; and establishing a cloud map containing three levels: layer, component, and global, based on the layered output.

[0006] In one embodiment, the step of reading initial data, which includes single-layer material characteristics, elements and their strain information in the result file, and elements, sections, nodes, and model material library information in the model file, includes: obtaining the top strain and bottom strain of the elements in the result file; and expanding the intermediate layer strain according to the strain compatibility assumption of classical laminates to obtain the strain information of the elements in the result file.

[0007] In one embodiment, the monolayer material characteristics include the positive axial strength, modulus, and Poisson's ratio of the monolayer material.

[0008] In one embodiment, the step of calculating the failure index based on the initial data and the post-processing parameters includes: calculating the positive axial stress based on the initial data; determining fiber failure based on the single-layer material characteristics and the positive axial stress, and calculating the fiber failure index; determining inter-fiber failure based on the single-layer material characteristics and the positive axial stress, and calculating the inter-fiber failure index; and determining fatigue failure based on the single-layer material characteristics and the positive axial stress, and calculating the fatigue failure index.

[0009] In one embodiment, after defining the post-processing parameters according to preset conditions, the method further includes: obtaining and determining the positive axis and off-axis based on the name of the single-layer material and the angle of the single-layer material in the post-processing parameters; if it is an off-axis, then performing strain angle conversion and stress-strain conversion in sequence to obtain the positive axis stress; if it is a positive axis, then obtaining the positive axis stress through stress-strain conversion.

[0010] In one embodiment, the strain angle conversion formula is:

[0011]

[0012] Where: m = cosθ, n = sinθ, and θ is the strain angle. For the strain along the off-axis, e 11 / e 22 / e 12 The strain is the strain on the positive axis after strain angle conversion.

[0013] In one embodiment, the stress-strain conversion formula is:

[0014]

[0015] Where E1 is the modulus of a single-layer material in one direction, E2 is the modulus of a single-layer material in two directions, v1 is the Poisson's ratio in the 1 / 2 direction, v2 is the Poisson's ratio in the 2 / 1 direction, and G... 12 e is the in-plane shear modulus; 11 / e 22 / e 12 For strain along the positive axis, s 11 / s 22 / s 12 The stress is on the positive axis.

[0016] In one embodiment, the formula for calculating the fiber failure index is:

[0017]

[0018] Among them, f ff The fiber failure index. To introduce the characteristic tensile or compressive stress intensity value after introducing the reduction factor, The stress values ​​in the 11 directions are obtained from the stress-strain conversion formula, with positive values ​​representing tension and negative values ​​representing compression.

[0019] In one embodiment, the step of determining inter-fiber failure based on positive axial stress and calculating the inter-fiber failure index includes: determining the type of inter-fiber failure based on positive axial stress, positive axial strength, and the Puck criterion, wherein the inter-fiber failure type includes inter-fiber type A failure, inter-fiber type B failure, and inter-fiber type C failure; and calculating the inter-fiber failure index based on the corresponding failure index formula according to the type of inter-fiber failure.

[0020] In one embodiment, the step of determining fatigue failure based on positive axial stress and calculating the fatigue failure index includes: calculating cumulative damage based on the number of cycles, and calculating the fatigue failure index based on the cumulative damage; the fatigue failure index calculation formula is:

[0021]

[0022]

[0023]

[0024] Where N is the allowed number of cycles, and D is the damage accumulation. e γ is the fatigue failure index. Ma Table of material limit reduction factor, γ Mb C represents the fatigue reduction factor of the material. 1b express S k,M S represents the mean stress cycle value. k,A R represents the stress cycle amplitude. k,t R represents the characteristic value of tensile strength. k,c This represents the characteristic value of compressive strength, and m represents the slope parameter, which varies depending on the material.

[0025] As can be seen from the above technical solution, the beneficial technical effects of the present invention are as follows:

[0026] This invention defines post-processing parameters based on preset conditions and extracts initial data from the model in ABAQUS software. It then calculates the failure index and significantly simplifies the extracted data volume based on classical laminate theory without sacrificing accuracy. Finally, it categorizes and outputs failure index reports based on the relationships between layers, materials, elements, strain, and nodal coordinates. Furthermore, it allows for the free selection of failure index cloud maps at three levels: global, component, and layer. This method greatly reduces the time spent on post-processing extraction, calculation, and output, lowers the difficulty of classification management and iterative adjustments, shortens the development cycle, and provides more room for cost reduction. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0028] Figure 1 This is a flowchart illustrating a blade stratification post-processing method based on ABAQUS in one embodiment.

[0029] Figure 2 A cross-sectional stacking diagram in one embodiment;

[0030] Figure 3 This is a schematic diagram of strain coordination in one embodiment;

[0031] Figure 4 This is a flowchart illustrating step S3 in one embodiment;

[0032] Figure 5 This is a schematic diagram of step S3 in another embodiment;

[0033] Figure 6 This is a diagram showing the relationship between cross-sectional objects in one embodiment;

[0034] Figure 7 This is a global failure index cloud map in one embodiment;

[0035] Figure 8 This is a component failure index cloud diagram using the P-face main beam component as an example in one embodiment;

[0036] Figure 9 This is a layer failure index cloud map of the 8th layer of the P-face main beam in one embodiment. Detailed Implementation

[0037] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0038] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by those skilled in the art to which this invention pertains.

[0039] First, ABAQUS is a powerful finite element software for engineering simulation, capable of solving problems ranging from relatively simple linear analyses to many complex nonlinear problems. ABAQUS includes a rich library of elements capable of simulating arbitrary geometries and possesses a library of various types of material models that can simulate the properties of typical engineering materials. Therefore, this section presents a blade layering post-processing method based on ABAQUS.

[0040] In one embodiment, an ABAQUS-based blade stratification post-processing method is provided, comprising the following steps:

[0041] S1 reads the initial data, which includes single-layer material characteristics, element and strain information in the result file, and element, section, node and model material library information in the model file.

[0042] Specifically, the element, layup, node, and strain information of the model are obtained from the ABAQUS odb and inp files. odb and inp are file extensions; the odb file is the result file, and the inp file is the model file. To simplify the result file data size, only the top and bottom strains (E11 / E22 / E12) of the elements in the odb file are needed, and the reading process is accelerated using multi-processing. Then, the element section definitions are read from the inp file, and the section stacking diagram is shown below. Figure 2 As shown.

[0043] In one embodiment, the monolayer material characteristics include the positive axial strength, modulus, and Poisson's ratio of the monolayer material.

[0044] In one embodiment, step S1 includes: obtaining the top strain and bottom strain of the element in the result file; expanding the intermediate layer strain according to the strain compatibility assumption of classical laminates to obtain the strain information of the element in the result file.

[0045] Specifically, in practice, existing reading methods tend to oversimplify the post-processing, leading to the loss of intermediate layer strain. To address this issue, this embodiment only reads the top and bottom strains E11 / E22 / E12 of the elements in the ABAQUS output odb file. The reading process is accelerated through multi-processing. Furthermore, the strain compatibility assumption of shell elements in classical laminates is used to establish a correlation with known element cross-sectional information. A strain compatibility diagram is shown below. Figure 3 As shown, linear interpolation supplements all intermediate layer strain data, thus restoring the final data. This solves the problem of other reading methods losing intermediate layers.

[0046] S2 defines post-processing parameters based on preset conditions, including industry standards and layered output requirements. Post-processing parameters include layer name prefixes.

[0047] Specifically, this involves defining all safety factors, material strengths, operating conditions, and output intervals according to design specifications. First, based on wind power industry standards, the partial factors and reduction factors for fiber failure, inter-fiber failure, fiber fatigue failure, ultimate bond failure, and fatigue bond failure are defined for subsequent calculations. Second, based on the model material library retrieved in step S1, the material names and angle compositions of each layer are defined. Then, the categorized output intervals and categorized output component prefixes are defined, representing a layered output requirement. Finally, the verification operating condition names are defined. The layered output in subsequent step S4 is based on the layer name prefixes, allowing for corresponding output selection.

[0048] In one embodiment, after step S2, the method further includes: obtaining and determining the positive axis and off-axis based on the name of the single-layer material and the angle of the single-layer material in the post-processing parameters; if it is an off-axis, then performing strain angle conversion and stress-strain conversion in sequence to obtain the positive axis stress; if it is a positive axis, then obtaining the positive axis stress through stress-strain conversion.

[0049] Specifically, such as Figure 4 As shown, where, Figure 4 Circle 1 in the diagram represents the strain angle conversion formula, and Circle 2 represents the stress-strain conversion formula. It's necessary to first determine if the axis is positive. If not, strain angle conversion must be performed before stress-strain conversion. If it is positive, stress-strain conversion can be performed directly.

[0050] In one embodiment, the strain angle conversion formula is:

[0051]

[0052] Where: m = cosθ, n = sinθ, θ is the strain angle. For the strain along the off-axis, e 11 / e 22 / e 12 The strain is the strain on the positive axis after strain angle conversion.

[0053] In one embodiment, the stress-strain conversion formula is:

[0054]

[0055] Where E1 is the uniaxial modulus in direction 1, E2 is the uniaxial modulus in direction 2, v1 is the Poisson's ratio in direction 1 / 2, v2 is the Poisson's ratio in direction 2 / 1, and G... 12 This refers to the in-plane shear modulus. The modulus in direction 1 and the modulus in direction 2 represent two types of moduli in multiple directions within a single-layer material.

[0056] S3 calculates the failure index based on the initial data and post-processing parameters. The failure index includes the fiber failure index, the inter-fiber failure index, and the fatigue failure index.

[0057] Specifically, the failure index is calculated for all layers and all angles of all units under each working condition. Taking the Puck criterion recommended by the design code as an example, the process for calculating the failure index is as follows: Figure 4 As shown, where, Figure 4 Circle 1 is the strain angle conversion formula, circle 2 is the stress-strain conversion formula, circle 3 is the fiber failure index calculation formula, circle 4 is the inter-fiber type A failure index formula, circle 5 is the inter-fiber type B failure index formula, circle 6 is the inter-fiber type C failure index formula, and circle 7 is the fatigue failure index formula. Figure 4 In this context, ff_effort is the fiber failure index, iff_effort is the inter-fiber failure index, and fatigue_effort is the fatigue failure index.

[0058] In one embodiment, such as Figure 5 As shown, step S3 includes: S31 calculating the positive axial stress based on the initial data; S32 determining fiber failure based on the characteristics of the single-layer material and the positive axial stress, and calculating the fiber failure index; S33 determining inter-fiber failure based on the characteristics of the single-layer material and the positive axial stress, and calculating the inter-fiber failure index; S34 determining fatigue failure based on the characteristics of the single-layer material and the positive axial stress, and calculating the fatigue failure index.

[0059] Specifically, all failure indices are calculated based on all available information. The main failures include three categories: fiber failure, inter-fiber failure, and fatigue failure. Therefore, the three types of failure indices for each piece of information are determined separately. Steps S32-S34 are not sequential; the step numbers are merely for ease of description in subsequent embodiments. These three steps can be performed synchronously in separate threads, thereby effectively improving the efficiency of failure index determination.

[0060] In one embodiment, the formula for calculating the fiber failure index in step S32 is:

[0061]

[0062] Among them, f ff The fiber failure index. This refers to the characteristic tensile or compressive stress intensity value after introducing a reduction factor. The stress value in the 11 direction (i.e., the direction where the uniaxial fabric fibers are located) is obtained according to the stress-strain conversion formula in the previous embodiment. Positive values ​​represent tension, and negative values ​​represent compression.

[0063] In one embodiment, step S33 includes: determining the inter-fiber failure type based on the positive axis stress, positive axis strength, and the Puck criterion, where the inter-fiber types include inter-fiber type A failure, inter-fiber type B failure, and inter-fiber type C failure; and calculating the inter-fiber failure index based on the corresponding failure index formula selected according to the inter-fiber failure type.

[0064] Specifically, the determination of the type is based on positive axis stress, positive axis strength, and the Puck criterion, which considers stress perpendicular to the fiber, in-plane shear stress, tensile and compressive strength of the fiber perpendicular to the fiber, in-plane shear strength, and some Puck parameters. This determination process is quite complex. For example... Figure 4 As shown, the formula for the Class A failure index between fibers is:

[0065] When the normal stress σ is perpendicular to the fiber direction t >0 indicates a Type A failure.

[0066]

[0067] Among them, f A τ is the inter-fiber Type A failure index. pt For in-plane shear stress, R is the tensile strength perpendicular to the fiber direction. s In-plane shear strength, Tensile parameters according to Puck criterion

[0068] Formula for inter-fiber type B failure index:

[0069] Judgment formula:

[0070]

[0071]

[0072] When the normal stress σ is perpendicular to the fiber direction t <0, and It is a Class B failure. This indicates that compressive stress perpendicular to the fiber direction and in-plane shear stress work together, but shear stress is dominant. τ 21 All are intermediate variables.

[0073]

[0074] Among them, f B This is the Class B failure index between fibers. For Puck criterion compression parameters, This represents the compressive strength perpendicular to the fiber direction.

[0075] Formula for Class C failure index between fibers:

[0076] When the normal stress σ is perpendicular to the fiber direction t <0, and It is a Class C failure. This indicates that compressive stress perpendicular to the fiber direction and in-plane shear stress work together, but compressive stress is dominant.

[0077]

[0078] Among them, f C This represents the Class C failure index between fibers; the meanings of other values ​​are described above.

[0079] In one embodiment, step S34 includes: calculating cumulative damage based on the number of cycles, and calculating a fatigue failure index based on the cumulative damage.

[0080] Specifically, the fatigue failure index formula first calculates the allowable number of cycles for a certain load level.

[0081]

[0082] Then, we obtain the damage accumulation expression, damage accumulation. Fatigue failure index

[0083] Where, γ Ma Table of material limit reduction factor, γ Mb C represents the fatigue reduction factor of the material. 1b express S k,M S represents the mean stress cycle value. k,A R represents the stress cycle amplitude. k,r R represents the characteristic value of tensile strength. k,c This represents the characteristic value of compressive strength, and m represents the slope parameter, which varies depending on the material.

[0084] S4 selects initial data and its corresponding failure index based on the layer name prefix according to preset conditions and outputs the data in layers.

[0085] Specifically, such as Figure 6 As shown, the core concept of layered output lies in using cross-sectional objects to establish relationships. In, for example... Figure 6 Under this relationship, output can be categorized according to any requirements, so the preset conditions are the pre-set output requirements.

[0086] For example, consider a set of layers containing a certain prefix as a component. By filtering the cross-section to identify all contained elements, and using the material, uniaxial direction, thickness, and total thickness of the cross-section corresponding to these layer names, calculate the failure index under strain for all elements. The results can include the nodal coordinates, safety factor, and layer name for each element. Then, by calculating the maximum failure index for the component in each spanwise direction, the report output for the component is complete.

[0087] S5 generates a cloud map containing three levels: layer, component, and global, based on the layered output.

[0088] Specifically, the plotting process involves outputting a failure index report accurate to a single-axis angle in the fourth step. The output format must include at least: element number - material - single-axis angle - layer name - failure index. A dedicated plugin is used to manipulate the ABAQUS odb field output object, adding data to it to complete the contour plotting.

[0089] The plugin needs to define the odb path, analysis step name, instance name, result file path, and level options.

[0090] The cloud map level options are divided into three levels: ALL (Global Failure Index), PARTS (Component Failure Index), and PLYS (Layered Failure Index).

[0091] ALL: Filter by cell number, taking the maximum value of all calculated failure indices within each cell as the failure index for that cell. Specifically, as follows... Figure 7 The image shown is a cloud map of the global failure index.

[0092] PARTS: This filter uses the component name as a prefix to select layer names. Based on ALL, it selects each unit containing the prefix layer and takes the maximum failure index as the failure index for that component and unit. Specifically... Figure 8 The figure shows a component failure index cloud map, taking the P-face main beam component as an example.

[0093] PLYS: Using layer name as the filtering condition, it finds failure indices for the same layer name, element number, and location but different single-axis angles, and takes the largest failure index as the failure index for that layer and element. Specifically, as shown below... Figure 9 The figure shown is a cloud map of the layer failure index, taking the 8th layer of the main beam on the P-side as an example.

[0094] The three levels are progressively higher and contain each other, as shown in Table 1 below:

[0095] Table 1 Cloud Map Levels

[0096]

[0097] The above embodiment, based on ABAQUS and utilizing the reasonable definition of layer names, establishes a connection between the element numbers (labels) and layers (plys) of the blade model. Based on classical laminated plate theory, it significantly simplifies the extracted data volume without sacrificing accuracy. Finally, it classifies and outputs failure index effort reports based on the relationships between layers, materials, elements, strain, and nodal coordinates. Furthermore, it allows for the free selection of three levels: global ALL, component PARTS, and layer PLYS to plot failure index effort contour maps. This method greatly reduces the time spent on post-processing extraction, calculation, and output, lowers the difficulty of classification management and iterative adjustments, shortens the development cycle, and provides more room for cost reduction.

[0098] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a computer storage medium (ROM / RAM, magnetic disk, optical disk) for execution by the computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Therefore, the present invention is not limited to any particular hardware and software combination.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A blade stratification post-processing method based on ABAQUS, characterized in that, include: Read the initial data, which includes single-layer material characteristics, element and strain information in the result file, and element, cross-section, node and model material library information in the model file; Post-processing parameters are defined according to preset conditions, which include industry standards and layered output requirements. The post-processing parameters include layer name prefixes. Based on the initial data and the post-processing parameters, a failure index is calculated, which includes a fiber failure index, an inter-fiber failure index, and a fatigue failure index. Based on the pre-set hierarchical output requirements, the initial data and its corresponding failure index are selected for hierarchical output based on the layer name prefix; Based on the layered output, a cloud map is constructed that includes three levels: layer, component, and global. The step of calculating the failure index based on the initial data and the post-processing parameters includes: Calculate the positive axial stress based on the initial data; Fiber failure is determined based on the characteristics of single-layer materials and positive axial stress, and the fiber failure index is calculated. Based on the characteristics of single-layer materials and positive axial stress, inter-fiber failure is judged, and the inter-fiber failure index is calculated. Fatigue failure is determined based on the characteristics of single-layer materials and positive axial stress, and the fatigue failure index is calculated. The step of reading initial data, which includes single-layer material characteristics, element and strain information in the result file, and element, section, node, and model material library information in the model file, includes: Obtain the top and bottom strains of the elements in the results file; Based on the strain compatibility assumption of classical laminates, the strain of the intermediate layer is expanded to obtain the strain information of the elements in the result file; The step of determining inter-fiber failure based on the characteristics of the single-layer material and the positive axial stress, and calculating the inter-fiber failure index, includes: Based on positive axis stress, positive axis strength, and the Puck criterion, the inter-fiber failure type is determined, which includes inter-fiber type A failure, inter-fiber type B failure, and inter-fiber type C failure. Based on the type of inter-fiber failure, the corresponding failure index formula is selected to calculate the inter-fiber failure index.

2. The method according to claim 1, characterized in that, The characteristics of the monolayer material include its positive axial strength, modulus, and Poisson's ratio.

3. The method according to claim 1, characterized in that, After defining the post-processing parameters according to the preset conditions, the following steps are also included: Obtain and determine the positive axis and off-axis based on the single-layer material name and angle in the post-processing parameters; If it is off-axis, then the strain angle conversion and stress-strain conversion are performed sequentially to obtain the positive axis stress; If it is the positive axis, then the positive axis stress can be obtained through stress-strain conversion.

4. The method according to claim 3, characterized in that, The strain angle conversion formula is: in: , , For the angle of strain, / / For strain off-axis, / / This represents the strain along the positive axis after strain angle conversion.

5. The method according to claim 3, characterized in that, The stress-strain conversion formula is: in, The modulus in one direction of a single-layer material. The modulus in the two directions of a single-layer material. Poisson's ratio in 12 directions The Poisson's ratio is in the 21st direction. It is the in-plane shear modulus; / / Strain is the positive axis. / / The stress is on the positive axis.

6. The method according to claim 5, characterized in that, The formula for calculating the fiber failure index is as follows: in, The fiber failure index. To introduce the characteristic tensile or compressive stress intensity value after introducing the reduction factor, The stress values ​​in the 11 directions are obtained from the stress-strain conversion formula, with positive values ​​representing tension and negative values ​​representing compression.

7. The method according to claim 3, characterized in that, The steps for determining fatigue failure based on positive axis stress and calculating the fatigue failure index include: The cumulative damage is calculated based on the allowable number of cycles, and the fatigue failure index is calculated based on the cumulative damage. The formula for calculating the fatigue failure index is as follows: Where N is the allowed number of cycles, and the damage accumulation is... , The fatigue failure index. Table of material limit reduction factor This represents the fatigue reduction factor of the material. express , This represents the mean value of stress cycles. Indicates the stress cycle amplitude. Indicates the characteristic value of tensile strength. Indicates the characteristic value of compressive strength. This represents the slope parameter, and its value varies depending on the material.

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