A method for diagnosing buckling mechanism of thin-walled composite structures

Abstract

The present application relates to the technical field of material structure equilibrium state diagnosis, and particularly relates to a composite material thin-walled structure buckling mechanism diagnosis method, which comprises the following steps: obtaining finite element calculation results or test post-processing data of a composite material thin-walled structure to be analyzed, wherein the data comprises axial compression response data and optional damage data; judging whether the finite element calculation results or test post-processing data are valid according to the axial compression response data; determining an axial compression path state according to a pre-peak membrane-bending path index and a local radial non-uniform deformation index; determining a damage participation state according to a damage participation index; and combining and matching the axial compression path state and the damage participation state to obtain a buckling mechanism category. The present application is directed to existing finite element calculation results or test post-processing data, and is used for identifying an initial defect input state, an axial compression path state and a damage participation state of a composite material thin-walled structure under axial compression loading, and outputting a joint mechanism diagnosis result.

Description

Technical Field

[0001] This invention relates to the field of material structure equilibrium state diagnosis technology, specifically to a method for diagnosing the buckling mechanism of thin-walled composite material structures. Background Technology

[0002] Fiber-reinforced composite thin-walled structures are characterized by their light weight, high specific strength, and high specific stiffness, and are widely used in aerospace, launch vehicle shells, engine connecting tubes, support tubes, and lightweight load-bearing structures. These structures are prone to buckling under axial compressive loads, and their peak loads are highly sensitive to initial geometric imperfections, ply stiffness distribution, end constraints, loading eccentricity, and local bending deformation.

[0003] Currently, buckling reduction coefficients, empirical lower limit curves, or nonlinear finite element analysis are commonly used in engineering design to assess the load-bearing capacity of thin-walled shells. While these methods can provide the structural load-bearing capacity or design lower limit, further mechanistic interpretation still relies on engineers' comprehensive judgment of load curves, deformation contour maps, damage variables, and local strain fields. For composite thin-walled structures, peak load formation may be simultaneously related to factors such as initial geometric imperfections, laminated stiffness distribution, local bending development before the peak load, loading eccentricity, and material damage. Relying solely on peak load or the final deformation contour map is insufficient to distinguish the roles of these factors in the peak load formation process.

[0004] Existing analytical methods have the following main shortcomings: First, defect descriptions are mostly based on geometric amplitudes. Commonly used maximum defect amplitude, root mean square defect amplitude, or buckling mode amplitude can describe the geometric size of a defect, but they are still difficult to reflect the severity of mechanical input corresponding to the same geometric defect under different ply stiffness, different thickness distribution, or different variable stiffness designs.

[0005] Second, peak loads primarily provide load-bearing results and do not adequately explain the path before the peak. Two structures may have similar peak loads, with one structure already exhibiting localized bending development before the peak, while the other primarily maintains intramembrane load-bearing and experiences sudden buckling near the peak. Comparing peak loads alone cannot distinguish between these two types of peak formation paths.

[0006] Third, there is a lack of correspondence between the initial defect input and the axial compression response. The initial defect may have a high geometric amplitude or a high stiffness-weighted energy. Whether this input truly transforms into a pre-peak localized path needs to be determined in conjunction with the axial compression response process. Existing methods typically lack a diagnostic process that maps the defect input state to the pre-peak response path.

[0007] Fourth, there is a lack of a unified discrimination process between buckling and damage. In thin-walled composite structures, material damage may occur before the peak value or may be induced by local indentation and stress concentration after geometric buckling. If only the presence of damage variables is checked, it is easy to misjudge the situation of "damage risk triggered but peak value still controlled by geometric buckling" as damage-driven failure.

[0008] Fifth, batch parametric design relies on manual review of curves and contour maps. When there are many parameters such as layup angle, defect amplitude, defect shape, loading eccentricity, and damage model parameters, manual judgment is inefficient and easily influenced by subjective experience.

[0009] Therefore, it is necessary to establish a diagnostic method for buckling mechanisms of composite thin-walled structures that can be implemented by a program, unifying the initial defect input state, axial compression response path state, and damage participation state into the same diagnostic framework, thereby achieving quantifiable, traceable, and batch identification of peak formation mechanisms. Summary of the Invention

[0010] To address the shortcomings in the aforementioned background technology, this invention provides a method for diagnosing the buckling mechanism of thin-walled composite structures. This method utilizes existing finite element calculation results or post-experimental data to identify the initial defect input state, axial compression path state, and damage participation state of thin-walled composite structures under axial compression loading, and outputs a combined mechanism diagnosis result.

[0011] This invention divides buckling mechanism diagnosis into two interrelated parts: the first part is the defect input severity evaluation, which is used to determine the geometric amplitude state, stiffness-weighted input level and input type of the initial geometric defect under the current laminated stiffness system; the second part is the axial compression response mechanism evaluation, which is used to determine whether the defect input transforms into pre-peak localization development, early damage participation or post-peak buckling development during axial compression loading.

[0012] This invention establishes a complete computational chain from input data to mechanism classification results by setting data validity thresholds, defect input indicators, peak pre-film-bend path indicators, local radial non-uniform deformation indicators, and damage participation indicators. The final diagnostic result is composed of defect input status, axial compression path status, damage participation status, and main mechanism category, and can be used for defect sensitivity assessment, model verification, ply layup design improvement, and damage risk assessment.

[0013] The first objective of this invention is to provide a method for diagnosing the buckling mechanism of thin-walled composite structures, comprising: Obtain the finite element calculation results or post-test data of the thin-walled composite material structure to be analyzed, including axial compression response data and optional damage data; The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature variations; the optional damage data includes failure indices, damage variables, stiffness degradation indicators, and equivalent damage indices. The validity of the finite element calculation results or post-test data can be determined based on the axial compression response data. Based on the axial compression response data, the pre-peak membrane-bending path index is obtained to distinguish the timing of buckling, and the local radial non-uniform deformation index is obtained to quantify the degree of local buckling deformation. The axial compression path state is determined based on the peak pre-film-bend path index and the local radial non-uniform deformation index. Damage participation indicators are obtained from optional damage data to distinguish the degree of impact of damage on the peak value. Determine the damage participation status based on damage participation indicators; The buckling mechanism category is obtained by combining and matching the axial compression path state and the damage participation state.

[0014] In one embodiment, determining the validity of finite element calculation results or post-test processing data based on axial compression response data includes: When the input data is finite element calculation result data, the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak value are calculated based on the axial compression response data. Define a preset numerical quality threshold; When the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak are both less than or equal to the preset numerical mass threshold, the finite element calculation results are considered valid. When the input data is post-test data, the validity is judged by the integrity of the load-displacement curve, the identifiability of the peak point, the effective measurement area of ​​the displacement field, and the data noise level. If the test data covers the path near the peak point, the peak point is effectively identified, the effective measurement area of ​​the displacement field is sufficient, and the noise level does not exceed the preset threshold, then the post-processed test data is considered valid.

[0015] In one embodiment, the pre-peak membrane-bend path index includes the pre-peak bending channel participation ratio increment; the local radial non-uniform deformation index includes the pre-peak local radial non-uniform deformation increment and the post-peak localization amplification factor.

[0016] In one embodiment, the axial compression path state is determined according to the following formula:

[0017] In the formula, The percentage increase of the bending channel participation before the peak; This represents the increment of local radial non-uniform deformation before the peak value; This is the localization amplification factor after the peak value; The threshold value for the pre-peak bending channel increment; This is the threshold for the local radial non-uniform deformation increment before the peak value; This is the threshold for localized amplification after the peak. This is the axial compression path state.

[0018] In one embodiment, the damage participation index includes damage or degradation triggering flags, damage triggering path points, and the percentage reduction in peak value caused by damage degradation.

[0019] In one embodiment, the damage participation state is determined according to the following formula:

[0020] In the formula, This serves as a marker for damage or degradation. This is the damage triggering path point; The percentage decrease in peak value due to damage and degradation; The threshold for determining whether damage or degradation has caused a decrease in peak value; For peak neighborhood tolerance; This indicates a state of damage involvement.

[0021] In one embodiment, the finite element calculation results or post-experiment processing data further include: basic model data and initial defect data; the basic model data includes geometric parameters, free segment range, lamination information, single-layer material parameters, and shell element region information; the initial defect data includes an initial geometric defect field.

[0022] In one embodiment, it further includes: Based on the basic model data and initial defect data, traditional geometric amplitude indices of composite thin-walled structures are obtained, as well as the defect input energy and the proportion of defect input bending channels related to lamination stiffness; the traditional geometric amplitude indices include the maximum absolute radial deviation and the root mean square defect amplitude. Determine the geometric amplitude state based on traditional geometric amplitude indices; The stiffness-weighted defect input level is determined based on the defect input energy related to the layer stiffness. Determine the defect input type based on the proportion of curved channels in the defect input; The defect input status is obtained based on the geometric amplitude status, stiffness-weighted defect input level, and defect input type.

[0023] In one embodiment, the buckling mechanism diagnosis result is obtained based on the defect input state, axial compression path state, damage participation state, and buckling mechanism category.

[0024] A second objective of this invention is to provide a system for diagnosing the buckling mechanism of thin-walled composite structures, comprising: The data acquisition module is used to acquire finite element calculation results or post-test processing data of the thin-walled composite material structure to be analyzed. The data includes axial compression response data and optional damage data. The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature changes. The optional damage data includes failure index, damage variables, stiffness degradation indicators, and equivalent damage indices. The data judgment module is used to determine whether the finite element calculation results or post-test processing data are valid based on the axial compression response data. The axial compression response module is used to obtain the pre-peak membrane-bending path index based on the axial compression response data to distinguish the timing of buckling, and to obtain the local radial non-uniform deformation index to quantify the degree of local buckling deformation; and to determine the axial compression path state based on the pre-peak membrane-bending path index and the local radial non-uniform deformation index. The damage participation module is used to obtain damage participation indicators based on optional damage data, which are used to distinguish the degree of impact of damage on the peak value; and to determine the damage participation status based on the damage participation indicators. The main mechanism module is used to combine and match the axial compression path state and the damage participation state to obtain the buckling mechanism category.

[0025] The present invention has at least the following beneficial effects: This invention provides a method for diagnosing the buckling mechanism of thin-walled composite structures, which introduces a peak pre-membrane-bend path index. and This can determine whether the curved channel participates before the peak value, thus supplementing the problem that a single peak load cannot explain the peak formation path. Simultaneously, a local radial non-uniform deformation index is introduced. Increment before peak and peak localization amplification factor By linking the development of local deformation with the paths before and after the peak, it is possible to quantify whether localization mainly occurs before or after the peak.

[0026] This invention establishes a correspondence between defect input states and axial compression response path states, through comparison. and It can determine whether the initial defect has been transformed into a pre-peak localization path, and thus distinguish between different situations such as "the defect input is high but the structure still has the capacity to accommodate" and "the defect input has driven the development of pre-peak local buckling".

[0027] This invention sets damage assessment as a conditional branch. When the model or experimental data provides damage variables, failure indices, or damage degradation results, it can further determine whether damage has been triggered, whether it occurs before or near the peak value, and whether it significantly reduces the peak load. When damage data is incomplete, it can output the impact of the damage peak value on the state to be reviewed, avoiding the forced provision of unreliable judgments.

[0028] This invention employs a hierarchical judgment method for mechanism classification. First, it determines the usability of the results through a data validity threshold. Then, it uses defect input indicators, axial compression path indicators, and damage participation indicators to form a joint diagnostic result. This method can cover situations such as geometric buckling dominance, pre-peak local buckling development, early damage participation, buckling-damage coupling, post-buckling damage, damage risk triggering but peak insensitivity, and mechanisms requiring further verification.

[0029] This invention combines traditional geometric defect amplitude evaluation with laminated stiffness-related defect energy evaluation, using traditional geometric amplitude indices. and Used to retain amplitude judgments at the manufacturing and inspection levels, lamination stiffness-related defect input energy. This is used to evaluate the severity of the mechanical input of the defect under the current ply, thickness, and stiffness system, thereby improving the pertinence of defect sensitivity evaluation.

[0030] This invention is suitable for batch finite element post-processing. It can automatically read multiple sets of layup, defect amplitude, defect shape or damage model results, and output a mechanism diagnosis report in a unified format, reducing the subjectivity caused by manually viewing curves and contour maps. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the method for diagnosing buckling mechanisms of thin-walled composite structures provided by the present invention; Figure 2 This invention provides a flowchart of the diagnostic method for buckling mechanisms of thin-walled composite structures. Figure 3 This is a schematic diagram of the approximately perfect reference structure and the defective structure on which the calculation of nodal displacement difference in this invention is based; Figure 4 This is a schematic diagram illustrating the hierarchical joint classification of defect input states and peak formation mechanisms in this invention; Figure 5 A comparison curve of peak axial compression identification and load-displacement recalculation for the QI / RTS benchmark example; Figure 6 The peak pre-membrane-bend channel participation path curve for the QI / RTS benchmark calculation; Figure 7 The curve of local radial non-uniform deformation in the QI / RTS benchmark example; Figure 8This is a diagram showing the results of damage participation status assessment using a damage degradation model. Detailed Implementation

[0032] In order to illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description is provided in conjunction with the embodiments.

[0033] This invention targets thin-walled composite material structures with initial geometric defects. It integrates geometric parameters, laminated stiffness information, initial defect field, axial compression load-displacement response, pre-peak membrane-bending path, local radial non-uniform deformation, and damage participation index to determine the input state of the initial defect under the current laminated stiffness system, and whether the input is transformed into pre-peak localization, damage participation, or post-peak buckling development during axial compression. Finally, it outputs a joint diagnostic result of buckling mechanism.

[0034] This invention provides a method for diagnosing the buckling mechanism of thin-walled composite structures, applicable to the buckling response analysis of thin-walled composite cylindrical shells, thin-walled tubes, thin-walled cylindrical sections, and other structures under axial compression or axial compression-dominant loading conditions.

[0035] To achieve the above objectives, see Figure 1 As shown, a method for diagnosing the buckling mechanism of a composite thin-walled structure includes: S1. Obtain the finite element calculation results or post-test processing data of the thin-walled composite material structure to be analyzed. This data includes axial compression response data and optional damage data. The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature variations; the optional damage data includes failure indices, damage variables, stiffness degradation indicators, and equivalent damage indices. The finite element calculation results or post-experiment data also include: basic model data and initial defect data; the basic model data includes geometric parameters, free segment range, lamination information, single-layer material parameters and shell element region information; the initial defect data includes the initial geometric defect field.

[0036] S2. Determine the validity of the finite element calculation results or post-test data based on the axial compression response data; Specifically, the validity of finite element calculation results or post-experiment data can be determined based on axial compression response data, including: When the input data is finite element calculation result data, the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak value are calculated based on the axial compression response data. Define a preset numerical quality threshold; When the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak are both less than or equal to the preset numerical mass threshold, the finite element calculation results are considered valid. When the input data is post-test data, the validity is judged by the integrity of the load-displacement curve, the identifiability of the peak point, the effective measurement area of ​​the displacement field, and the data noise level. If the test data covers the path near the peak point, the peak point is effectively identified, the effective measurement area of ​​the displacement field is sufficient, and the noise level does not exceed the preset threshold, then the post-processed test data is considered valid.

[0037] S3. Based on the axial compression response data, obtain the pre-peak membrane-bending path index to distinguish the timing of buckling, and obtain the local radial non-uniform deformation index to quantify the degree of local buckling deformation; determine the axial compression path state based on the pre-peak membrane-bending path index and the local radial non-uniform deformation index. The pre-peak membrane-bending path index includes the incremental proportion of the bending channel participation before the peak; the local radial non-uniform deformation index includes the incremental local radial non-uniform deformation before the peak and the localization amplification factor after the peak.

[0038] The axial compression path state is determined according to the following formula:

[0039] In the formula, The percentage increase of the bending channel participation before the peak; This represents the increment of local radial non-uniform deformation before the peak value; This is the localization amplification factor after the peak value; The threshold value for the pre-peak bending channel increment; This is the threshold for the local radial non-uniform deformation increment before the peak value; This is the threshold for localized amplification after the peak. This is the axial compression path state.

[0040] S4. Obtain damage participation indicators based on optional damage data to distinguish the degree of damage impact on the peak value; determine the damage participation status based on the damage participation indicators. The damage participation indicators include damage or degradation triggering markers, damage triggering path points, and the percentage reduction in peak value caused by damage and degradation.

[0041] The damage participation status is determined according to the following formula:

[0042] In the formula, This serves as a marker for damage or degradation. This is the damage triggering path point; The percentage decrease in peak value due to damage and degradation; The threshold for determining whether damage or degradation has caused a decrease in peak value; For peak neighborhood tolerance; This indicates a state of damage involvement.

[0043] S5. Combine and match the axial compression path state and damage participation state to obtain the buckling mechanism category.

[0044] The present invention also includes: Based on the basic model data and initial defect data, traditional geometric amplitude indices of composite thin-walled structures are obtained, as well as the defect input energy and the proportion of defect input bending channels related to lamination stiffness; the traditional geometric amplitude indices include the maximum absolute radial deviation and the root mean square defect amplitude. Determine the geometric amplitude state based on traditional geometric amplitude indices; The stiffness-weighted defect input level is determined based on the defect input energy related to the layer stiffness. Determine the defect input type based on the proportion of curved channels in the defect input; The defect input status is obtained based on the geometric amplitude status, stiffness-weighted defect input level, and defect input type.

[0045] Finally, the buckling mechanism diagnosis results are obtained based on the defect input status, axial compression path status, damage participation status, and buckling mechanism category.

[0046] To illustrate the buckling mechanism diagnosis method for thin-walled composite material structures provided by this invention, the following description is provided in conjunction with the accompanying drawings.

[0047] See Figure 2 As shown, a method for diagnosing the buckling mechanism of a composite thin-walled structure includes the following steps: Step S1, Basic Data Acquisition and Data Mapping: Obtain basic model data, initial defect data, axial compression response data, and optional damage data for the thin-walled composite material structure to be analyzed.

[0048] The basic model data includes geometric parameters, free segment range, lamination information, single-layer material parameters, and shell element region information. The geometric parameters include radius... ,length Wall thickness and the surface area of ​​the free segment The lamination information includes ply angle, ply sequence, single-layer thickness, and material elastic constants.

[0049] The initial defect data includes the initial geometric defect field. ,in For axial coordinates, The coordinates are circumferential. The initial geometric defect field can be derived from CMM measurement, DIC reconstruction, laser scanning, finite element initial mesh, linear buckling modes, or artificially constructed defects.

[0050] The axial compression response data includes load-displacement curves. The data includes energy history, nodal displacement field, shell element section forces, shell element section bending moments, mid-surface strain, and curvature variation. The energy history includes kinetic energy. Stabilizing dissipated energy and elastic strain energy The mid-surface strain and curvature changes can be obtained directly from the shell element output, or they can be obtained by fitting the shell section strain along the thickness direction.

[0051] The optional damage data includes failure index, damage variable, stiffness degradation indicator, or equivalent damage index. When no damage-related output exists, the damage branch output is "Not Applicable".

[0052] To clarify the correspondence between input data, calculated indicators, and diagnostic applications, this invention performs data mapping as shown in Table 1.

[0053] Table 1. Correspondence between input data, calculation indicators, and applications.

[0054] Through the above data mapping, the variables required for each subsequent step are obtained directly or indirectly from the input data in step S1.

[0055] Step S2, Initial defect input severity characterization: This step is used to evaluate the severity of the initial geometric defects in the current composite laminate stiffness system. This step does not depend on the axial compression loading response and belongs to the defect input branch.

[0056] First, the initial geometric defect field of the free segment. Calculate the average area:

[0057] In the formula, This represents the average area of ​​the initial defect field in the free segment; Let be the area of ​​the surface region in the free segment.

[0058] Further calculations were performed on the maximum absolute radial deviation and the root mean square defect amplitude:

[0059]

[0060] In the formula, The maximum absolute radial deviation of the initial geometric defect field of the free segment; denoted as the root mean square magnitude of the initial geometric defect field of the free segment.

[0061] Normalizing the above defect amplitudes according to the wall thickness yields the traditional defect amplitude index:

[0062]

[0063] In the formula, This is the normalized value of the maximum defect amplitude thickness; This represents the root mean square defect amplitude and thickness normalized value. The nominal wall thickness of the structure.

[0064] Depend on and Obtain the traditional geometric amplitude state The aforementioned Used to record the low, medium, or high amplitude state of initial defects at the geometric amplitude scale. The geometric amplitude threshold can be determined based on the manufacturing tolerances, inspection standards, design-allowed defects, or parametric samples of the same structural series.

[0065] To further characterize the mechanical severity of the same geometric defect in structures with different ply stiffness, thickness distribution, or variable stiffness, this invention defines the lamination stiffness-related defect input energy. According to the theory of laminated plates and shells, the input energy of defects related to laminated stiffness can be expressed as:

[0066] In the formula, , , These are the membrane stiffness matrix, membrane-bending coupling stiffness matrix, and bending stiffness matrix, respectively, determined by the layup angle, layup sequence, single-layer thickness, and material elastic constants. The equivalent mid-surface strain induced by the initial defect displacement field; This represents the equivalent curvature change induced by the initial defect displacement field.

[0067] In finite element implementation, see Figure 3 As shown, an approximately perfect reference structure can be established, the displacement difference between the node coordinates of the defective structure and the node coordinates of the perfect reference structure can be calculated, and this displacement difference can be applied to the perfect reference structure as a specified node displacement. Elastic strain energy can then be extracted at the end of the auxiliary linear static step.

[0068] In the formula, The total elastic strain energy at the end of the auxiliary defect input calculation step is used.

[0069] Furthermore, based on the contributions of intramembrane channels and tortuous channels in the auxiliary defect input calculation, the proportion of tortuous channels in the defect input is defined as follows:

[0070] In the formula, To assist in the proportion of curved channels in linear defect input; Contributes to intramembrane channels in the auxiliary defect input; It contributes to the curved channel in the auxiliary defect input.

[0071] This yields the defect input index set:

[0072] The defect input index group is used to determine the defect input status. .in, Record the state of traditional geometric amplitude; As the main index of defect severity after weighting by lamination stiffness; Used to characterize the proportion of curved channels in defect input.

[0073] The The threshold is set for the structure to be analyzed or the same design series. For specific structural designs or comparisons of defect sensitivity within the same structural series, a unified structural model, material parameters, layup system, and boundary settings are used to determine the threshold, and the defect input level is judged accordingly.

[0074] Step S3, Axial compression response identification and data validity judgment: This step is used to identify the peak value of the axial compression response and determine whether the finite element or post-test data meets the requirements for subsequent mechanism diagnosis. This step is a quality threshold for the axial compression response branch.

[0075] According to the load-displacement curve Calculate the peak load:

[0076] The loading displacement corresponding to the peak load is:

[0077] Define normalized path variables:

[0078] In the formula, Peak load; This represents the loading displacement corresponding to the peak load. For normalized path variables; when At that time, the corresponding peak load state.

[0079] When the input data is the result of finite element analysis, in order to determine whether the axial compression response can be used for quasi-static mechanism diagnosis, the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio within the effective loading segment before the peak are calculated:

[0080]

[0081] In the formula, This represents the maximum kinetic energy ratio within the effective loading segment before the peak value. The maximum stabilized energy dissipation ratio within the effective loading period before the peak value; Path variables The kinetic energy below; Path variables Stabilization dissipation energy under the following conditions; Path variables elastic strain energy under the condition; This is the effective loading segment start threshold, used to exclude the initial loading phase. The numerical amplification of the energy ratio when it approaches zero; The starting point of the load-displacement curve entering the stable loading stage is determined; if no separate calibration is performed, it can be taken as... That is, from The path segment is used to start the statistics. For the same batch of comparative samples, Maintain consistency.

[0082] If the following conditions are met:

[0083] The finite element axial compression response data is then used for the calculation of mechanism indices in steps S4 to S6. Where, The numerical quality threshold is determined based on the principle that kinetic energy and stabilization dissipation energy should be kept at a low level relative to elastic strain energy, and is further defined by considering the stability of peak load and path indices when mesh size, loading increment, and stabilization parameters change. This embodiment uses the energy ratio range from the publicly available benchmark and controlled examples. The same threshold is used for the same batch of comparison samples. If equation (15) is not satisfied, the output "numerical quality needs to be reviewed" will be displayed, and the diagnostic report will state that the result will not be directly included in the mechanism classification.

[0084] When the input data is post-test processing data, validity is judged based on the integrity of the load-displacement curve, the identifiability of peak points, the effective measurement area of ​​the displacement field, and the data noise level. The data noise threshold is determined based on the nominal accuracy of the measurement system, the root mean square noise of the unloaded baseline segment, and the dispersion of repeated test results; the effective measurement area of ​​the displacement field is required to be determined based on the effective coverage of the target free segment. A unified judgment standard is used for the same measurement system and the same batch of tests. The post-test processing data is considered valid when the test data covers the path near the peak point, the peak point can be effectively identified, the effective measurement area of ​​the displacement field is sufficient, and the noise level does not exceed the preset threshold; if any condition is not met, "Test data quality needs review" is output, and the specific deficiencies are explained in the diagnostic report.

[0085] Step S4, Calculation of peak pre-film-bend path index: This step uses the shell element section force, section bending moment, mid-surface strain, and curvature change from step S1 to calculate the membrane-bending energy path during axial compression loading.

[0086] For the Each shell unit, in path variables Under these conditions, the contribution of intramembrane channels is defined as:

[0087] The contribution of the curved channel is defined as:

[0088] In the formula, For the first Each shell unit in path variables The contribution of intramembrane channels; For the first Each shell unit in path variables The contribution of the curved channel below; For the first The mid-surface area of ​​each shell unit; The force vector of the shell section; The bending moment vector of the shell section; The mid-surface strain vector; The curvature variation vector; superscript This indicates transpose.

[0089] To avoid the impact of local coordinate direction and sign cancellation on path determination, the participation ratio of curved channels is defined using absolute channel contribution:

[0090] In the formula, Path variables The proportion of participation in the curved channel below; The number of free segment shell units participating in post-processing; This indicates taking the absolute value.

[0091] Further define the incremental participation ratio of the pre-peak bending channel:

[0092] In the formula, To start from the reference path point to peak point The percentage increase of the curved channel participation; This is a reference path point before the preset peak value.

[0093] in, Maintain consistency within the same batch of comparison samples; if there are discrepancies in the post-processed data... If the path point is found, the corresponding indicator is read directly; if the path point does not exist in the post-processed data, the corresponding indicator is obtained by interpolation using adjacent path points; if interpolation is not possible, the indicator that satisfies the condition is selected. The nearest path point, where This is a preset reference point tolerance. If no pathpoint meets this tolerance, then... It is marked as unavailable, and the diagnostic report indicates insufficient path data.

[0094] Step S5, Calculation of local radial non-uniform deformation index: This step uses the nodal radial displacement field or DIC displacement field from step S1 to calculate the local radial non-uniform deformation index.

[0095] In path variables Below, the average radial displacement area of ​​the free segment is defined as:

[0096] In the formula, This represents the average radial displacement area of ​​the free segment.

[0097] The local radial non-uniform deformation is defined as:

[0098] In the formula, Path variables The local radial non-uniform deformation amount.

[0099] For post-processed data of discrete nodes or cells, the area average can be calculated in an area-weighted form:

[0100] In the formula, For the first The radial displacement value of a unit or a point represented by a unit.

[0101] Further define the local radial non-uniform deformation increment before the peak:

[0102] To quantify the degree of post-peak localization amplification, a post-peak localization amplification factor is defined:

[0103] In the formula, For preset peak-representing path points, calculation termination path points, or specified post-buckling path points; To prevent small positive numbers with a denominator of zero.

[0104] in, Maintain consistency within the same batch of comparison samples; if there are discrepancies in the post-processed data... If the path point is not specified, then directly read the corresponding path point. If the path point does not exist in the post-processed data, the corresponding value is obtained by interpolation using adjacent path points; if interpolation is not possible, a value that satisfies the condition is selected. The nearest post-peak path point, among which A preset post-peak pathpoint tolerance is set. If no post-peak pathpoint meets this tolerance, the calculated termination frame can be used as the default pathpoint. The report should indicate the actual path points used; if the calculation results do not lead to the post-peak path, then... Mark it as unavailable and output "Insufficient post-peak path".

[0105] For comparisons between structures of different thicknesses, the thickness normalized form can also be output simultaneously:

[0106] In the formula, This is the thickness-normalized value of the local radial non-uniform deformation increment before the peak value. When using this normalized index to compare structures of different thicknesses, the local deformation criterion in equation (40) is rewritten accordingly. or ,in, This represents the threshold for the increment of local radial non-uniform deformation before the dimensionless peak value. When using the unnormalized form, it is still based on... With a threshold having the dimension of length Compare the two criteria. The two criteria should not be used interchangeably. For a single structure or the same design series with consistent thickness, the criteria can be directly applied. Make a judgment.

[0107] Step S6, Calculation of damage participation index: This step is executed when the finite element model or post-test processing data contains failure index, damage variable, stiffness degradation indicator, or equivalent damage index; otherwise, this step outputs "Damage not applicable".

[0108] Let the first Unit 1, the 1st The integration point, the first One layer, the first Each failure mode in path variables The following failure indicators are:

[0109] Among them, failure modes It may include fiber tension, fiber compression, matrix tension, matrix compression, or other composite material failure modes.

[0110] The comprehensive maximum failure index is defined as:

[0111] Define damage or degradation trigger flags:

[0112] If the following conditions are met across the entire range of the investigation paths:

[0113] If at least one path point satisfies the condition, then the damage is determined not to have been triggered; Then define the damage trigger path point:

[0114] In the formula, This is the damage triggering path point.

[0115] To address the peak neighborhood determination problem caused by discrete output frames or interpolation errors, a peak neighborhood tolerance is defined. When the following relationship is satisfied:

[0116] Damage triggering is determined to occur near the peak value; When the following relationship is satisfied:

[0117] Damage triggering is determined to be pre-peak triggering; When the following relationship is satisfied:

[0118] Damage triggering is determined to be post-peak triggering.

[0119] in, To ensure consistent path tolerance within the same batch of comparison samples, for discrete output frame data, The output interval can be determined based on the path variable, for example, by taking half of the maximum interval between adjacent output path points; for interpolated continuous path data, A preset small amount can be used to characterize the tolerance for judging the peak value.

[0120] When both baseline calculations without material degradation and calculations with damage degradation exist, the peak loads of the two sets of responses are calculated separately:

[0121] In the formula, Calculate peak loads based on a material-degrade-free baseline; Calculate the peak load for damage and degradation.

[0122] Define the percentage decrease in peak value caused by damage and degradation:

[0123] In the formula, The percentage decrease in peak value due to damage and degradation.

[0124] When only single damage calculation or experimental damage observation data exists, the output is... , and As a state of damage risk, and Marked as inapplicable. In this case, the primary mechanism category is determined by the axial compression path status, and a "Damage peak impact to be verified" note is added to the diagnostic report.

[0125] Step S7, Joint classification of defect input state and peak formation mechanism: See Figure 4 As shown, this step jointly determines the defect input index obtained in step S2, the axial compression response index obtained in steps S4 to S6, and the damage participation index, and outputs the defect input status, axial compression path status, damage participation status, and main mechanism category.

[0126] First, determine the geometric amplitude state based on traditional geometric amplitude indices. The Depend on and Together, they are used to identify the low, medium, or high amplitude state of the initial defect under the traditional geometric amplitude scale.

[0127] Secondly, the stiffness-weighted defect input level is determined based on the defect input energy related to the layer stiffness:

[0128] Determine the defect input type based on the proportion of curved channels in the defect input:

[0129] In the formula, , , , These are preset thresholds. The above thresholds are set for the structure to be analyzed or the same design series, and can be determined by manufacturing tolerances, design allowable defects, a database of similar structures, or parametric samples.

[0130] This yields the defect input status:

[0131] In the formula, Used to retain the results of traditional geometric magnitude determination; Used to provide the layer stiffness-weighted defect input level; Used to indicate the defect input type. When the geometric amplitude state and stiffness-weighted input level are inconsistent, the diagnostic report retains both, and uses the stiffness-weighted input level as the primary basis for ranking the defect input risk.

[0132] Next, the axial compression path state is determined based on the pre-peak membrane-bending path and local radial non-uniform deformation. A set of axial compression path indices is defined:

[0133] The axial compression path state is determined based on the pre-peak bending channel increment, the pre-peak local radial non-uniform deformation increment, and the post-peak localization amplification factor:

[0134] In the formula, The threshold value for the pre-peak bending channel increment; This is the threshold for the local radial non-uniform deformation increment before the peak value; This is the threshold for post-peak localization amplification. The threshold is determined based on the index distribution of calibration samples of similar structures, the allowable deformation range in engineering, and the measurement or calculation resolution. Based on the stable samples of the path before the peak The upper envelope or high quantile value is determined; It can be determined based on the allowable local radial non-uniform deformation increment before the peak or the upper envelope of the stable sample; This threshold is used to specify the minimum amplification factor of post-peak localization relative to the peak state. After the threshold is determined, the stability of the classification results should be checked by perturbation with neighboring values, and consistency should be maintained within the same batch of comparison samples. This embodiment is for illustrating the judgment process, taking... , , If thickness normalization is adopted... Then Replace with dimensionless threshold .

[0135] Then, the damage participation status is determined based on the damage triggering path point and the percentage reduction in damage degradation peak. When there is no damage output, it is determined that the damage is not applicable; when there is damage output but it is within the entire scope of the investigation path... When, it is determined that the damage has not been triggered; when If not applicable, retain the damage trigger path point and output the damage peak value affecting the status to be reviewed.

[0136] exist When calculable, the damage involvement state is determined by the following formula:

[0137] In the formula, The threshold for determining peak value reduction due to damage degradation should be higher than the numerical fluctuations caused by meshing, increments, and peak extraction between the non-damage baseline calculation and the damage-included calculation, and should be determined in conjunction with the peak load variation amplitude considered to have practical impact in engineering. In this embodiment, the threshold is... . The peak neighborhood tolerance is determined based on the discrete resolution of the path data; for discrete output frames, it can be half of the maximum value of the output interval between adjacent path variables; for interpolated continuous path data, it can be a uniform small positive number; in this embodiment, it is... The same batch of comparative samples used a uniform method and .

[0138] Finally, according to and Determine the main mechanism category and will The status serves as the input for the combined diagnostic results. The classification process employs the following priority: First, if the data validity check in step S3 fails, the output "Data quality needs to be reviewed" will be displayed, and the data will not be classified in the main mechanism.

[0139] Second, if If the condition is "Localization not fully activated / Loading range to be verified", then the output will be "Mechanism to be verified", and the report will explain that the post-peak path is insufficient, localization is not fully activated, or the path indicator is unavailable.

[0140] Third, if the data is valid and the path indicators are available, determine the main mechanism category as shown in Table 2.

[0141] Table 2. Main Mechanism Categories Obtained by Combining Axial Compression Path State and Damage Participation State

[0142] The final combined diagnostic results are expressed as follows:

[0143] In the formula, This is a joint diagnostic result; the joint diagnostic result simultaneously includes the defect input status, axial compression path status, damage involvement status, and main mechanism category. The natural language output can be expressed as "high stiffness weighted defect input - geometric buckling dominant but with damage risk type", "medium defect input - pre-peak local buckling development type", or "bending type defect input - buckling-damage coupling type".

[0144] Step S8, output the diagnostic report: Output a structured diagnostic report, which includes at least the following: (1) Results of data validity assessment, including , , , And whether it meets the threshold requirements; for test data, output the completeness of the load-displacement curve, the identifiability of the peak point, the effective measurement area of ​​the displacement field, and the noise level judgment results. (2) Defect input severity results, including , , , , , , and ; (3) Axial compression path status results, including , , , , and ; (4) Results of damage involvement status, including , , , , , and ;when If not applicable, the report should indicate "Damage peak impact to be verified"; (5) Main mechanism category and combined diagnostic results ; (6) Design concerns, including defect control, ply stiffness adjustment, boundary and loading verification, local stability control, post-peak path supplementary calculation or damage risk verification recommendations.

[0145] Through the above steps, the present invention can link the severity of the initial defect input with the axial compression response path, further determine whether the initial defect has been transformed into a dangerous path before the peak, and output a complete buckling mechanism diagnosis result in combination with the damage participation state.

[0146] To further illustrate the buckling mechanism diagnosis method for thin-walled composite structures provided by this invention, specific examples are given.

[0147] The following embodiments use a unified path reference point. This facilitates the explanation of the stratification process. The finite element quality control threshold is taken as... The threshold for the peak-bend channel increment is taken as follows: The threshold for the local radial non-uniform deformation increment before the peak value is taken as mm, post-peak localization amplification threshold is taken The threshold for reducing the peak value of damage and degradation is taken. Peak neighborhood tolerance The thresholds mentioned above are only used for process description in this embodiment and should be kept consistent across the same batch of comparison samples.

[0148] Example 1 This embodiment implements a buckling mechanism diagnosis method based on the axial compression benchmark example of a QI / RTS composite cylindrical shell, including: This embodiment employs two types of composite cylindrical shell axial compression benchmark examples from publicly available literature and datasets. Here, QI stands for quasi-isotropic, representing a straight-fiber quasi-isotropic composite cylindrical shell; RTS stands for Rapid-Tow-Sheared, representing a variable-stiffness, variable-thickness composite cylindrical shell manufactured using a rapid fiber layup shearing process. The specimen designations QI and RTS from the publicly available studies will continue to be used thereafter. The publicly available data includes axial compression test load-displacement curves, CMM measured geometric defects, DIC deformation data, LVDT loading eccentricity data, strain gauge data, and finite element input files. This publicly available benchmark is used to illustrate the diagnostic process of this invention for geometric buckling-dominant responses.

[0149] (1) Judgment of the validity of basic data and axial compression response: First, a complex model of the cylindrical shell with QI and RTS is established, the load-displacement curve is calculated, and the results are compared with those of the public test and the public finite element method. The peak load is extracted from the load-displacement curve by equation (10), the peak displacement is determined by equation (11), and the path variable is normalized by equation (12). Figure 5Figure (a) shows the comparison results for the QI cylindrical shell. The recalculated curve in this paper can reproduce the overall stiffness before the peak and the load reduction process after the peak. The peak load is 168.70 kN, while the published experimental peak and the published finite element peak are 154.3 kN and 160.7 kN, respectively. Figure 5 Figure (b) presents the comparative results for the RTS cylindrical shell. The peak value calculated in this paper is 176.36 kN, which is close to the publicly available experimental peak value of 172.4 kN and the publicly available finite element peak value of 177.5 kN. Both sets of calculations can reproduce the pre-peak loading path and near-peak response of the publicly available benchmark, and can be used for subsequent path index extraction. The specific global response and numerical quality index are shown in Table 3.

[0150] Table 3 Global Response and Data Validity Assessment of Public QI / RTS Benchmark Examples

[0151] As shown in Table 3, both the QI and RTS recalculation models can reproduce the initial stiffness and peak load levels of the publicly disclosed finite element model. The kinetic energy ratio and stabilized dissipation energy ratio within the effective loading segment are both lower than the mass control threshold set in this embodiment. Therefore, it proceeds to the calculation of subsequent mechanism indicators.

[0152] (2) Defect input status calculate: Based on the initial defect node coordinates in the publicly available CMM measured defects and recalculated models, the traditional geometric magnitude indices of QI and RTS are calculated. Further, an auxiliary linear defect input calculation is constructed. Using the approximately perfect cylinder of the corresponding example as a reference, the measured defect node displacement difference is applied to the free segment node, and the elastic strain energy at the end of the auxiliary step is extracted. And calculate the proportion of the defect input bending channel. The specific defect input status indicators are shown in Table 4.

[0153] Table 4 Defect Input Status Indicators for Public QI / RTS Benchmark Cases

[0154] As shown in Table 4, the conventional geometric amplitude and laminated stiffness-related defect input energy of RTS are both higher than those of QI. The proportion of bending channels in the defect input for both is similar, both falling within the low bending proportion range. Based on the relative comparison results of this embodiment, QI can be denoted as a lower stiffness-weighted defect input, and RTS as a higher stiffness-weighted defect input; both can be denoted as mixed-film-type defect input.

[0155] The results indicate that RTS has a higher input defect severity, and further analysis of the axial compression path is needed to determine whether the input has been converted into a dangerous path before the peak.

[0156] (3) Axial compression path status calculate: The axial compression recalculation results of QI and RTS are post-processed for membrane-bending path. The participation ratio of the bending channel is calculated using equation (18). The formula (19) is used to calculate the value from... to peak point Incremental participation of curved channels . Figure 6 The dashed line in the middle represents the reference path point before the peak. its right side to The region represents the evaluation window before the peak value. QI's... Within this window, the value increased from 0.0973 to 0.1818, an increment of 0.0845; the RTS increased from 0.0393 to 0.0701, an increment of 0.0308. QI exhibited a high proportion of curved channel participation throughout the pre-peak evaluation window, but the increments in both sets of calculations did not exceed the limits set in this embodiment. The specific values ​​are listed separately in Table 5.

[0157] Table 5 discloses the peak front membrane-bend path index of the QI / RTS benchmark calculation.

[0158] As shown in Table 5, QI exhibits a higher bending channel participation ratio and a larger bending channel increment before the peak; RTS maintains a lower bending channel participation ratio before the peak. According to the threshold values ​​in this embodiment... Both None of them exceeded the threshold for local buckling development before the peak.

[0159] Further calculation of local radial non-uniform deformation based on nodal radial displacement field Local radial non-uniform deformation increment before peak value and peak localization amplification factor . Figure 7 The main graph shows the complete path of QI and RTS from the initial loading stage to the post-peak state. Figure 7 The enlarged view on the left further demonstrates Changes before the peak within the range. QI and RTS in to within the interval Both increased slowly, with pre-peak increments of 0.1027 mm and 0.0855 mm, respectively; after the peak... The peak localization amplification factors increased rapidly to 14.95 and 16.53, respectively. This indicates that the local non-uniform deformation in both benchmark examples is mainly amplified after the peak value, consistent with the "smooth path before peak value – localized after peak value" criterion. Specific values ​​are listed separately in Table 6.

[0160] Table 6. Local radial non-uniform deformation path indices of the publicly disclosed QI / RTS benchmark calculation.

[0161] As shown in Table 6, the local radial non-uniform deformation increments before the peak values ​​of both QI and RTS are lower than the threshold values ​​in this embodiment. mm, while the post-peak localization amplification factor is much higher than Therefore, the axial compression path states of both QI and RTS are determined to be "stable path before peak - localized after peak".

[0162] (4) Damage involvement status judge: The publicly available QI / RTS benchmark calculations are primarily used for geometric buckling response verification. Since the publicly available experimental and recalculation results do not show evidence of material damage prematurely participating in peak formation, this embodiment denotes the damage participation state as "damage not participating in peak formation." This state is consistent with the results in Tables 5 and 6 showing a smooth pre-peak path and post-peak localization amplification.

[0163] (5) Combined diagnostic results: Following step S7, the defect input status, axial compression path status, and damage participation status are combined to obtain the joint diagnostic results shown in Table 7.

[0164] Table 7. Public QI / RTS benchmark case combined diagnostic results

[0165] This embodiment illustrates that the present invention can separately identify "defect input severity" and "axial compression peak formation path". The defect input energy of RTS is higher than that of QI, and the axial compression path still exhibits a smooth path before the peak and localized amplification after the peak, indicating that the structure has a certain capacity to accommodate this type of measured defect. The defect input energy of QI is lower, but the proportion of the bending channel participating before the peak is higher than that of RTS, indicating that the pre-peak path index can further supplement the shortcomings of the defect input index in explaining the mechanism. Both sets of published benchmarks are ultimately classified as geometric buckling-dominated.

[0166] Example 2 This embodiment includes damage participation boundary determination in the damage degradation model; This embodiment illustrates how the present invention determines whether damage participates in the formation of peak load when the finite element model of a composite thin-walled structure includes damage variables, failure indices, or stiffness degradation models, and incorporates the damage state, defect input state, and axial compression path state into the joint diagnostic result.

[0167] The examples selected three sets of numerical calculations on axial compression of thin-walled cylindrical shells made of composite materials. Each set of calculations included two corresponding calculations: one set was a baseline calculation without material degradation, and the other set was a damage calculation with USDFLD stiffness degradation. The two sets of calculations used the same geometry, layup, initial defect shape, defect amplitude, and boundary conditions. The main difference was whether damage degradation was introduced into the material response.

[0168] The three representative working conditions are as follows: D-1 is an ORTHO layer. Defect shape, ; D-2 is a T30 layup. Defect shape, ; D-3 is a T60 layup. Defect shape, .

[0169] In damage calculations, the user subroutine updates state variables based on composite material failure indices. State variables include damage trigger flags, historical maximum indices for each failure mode, combined maximum failure index, and dominant failure mode number. Figure 8 Figure (a) shows three sets of damage triggering path points representing the working conditions. D-1 in Time-triggered, belonging to the earlier pre-peak triggering; D-2 ​​in Time-triggered, belonging to the pre-peak triggering near the peak value; D-3 in It is triggered at any time and is located in the neighborhood of the peak. Figure 8 Figure (b) shows the percentage reduction in peak values ​​for damage-included degradation calculations compared to non-damage baseline calculations. D-1, D-2, and D-3 are 0.3118%, 0.0032%, and 0.0002%, respectively, all below the judgment threshold. Therefore, all three working conditions have the risk of damage triggering, but the damage degradation has not significantly changed the peak load. The damage participation status is determined as "damage risk before or near the peak but not sensitive to the peak".

[0170] (1) Basic data and validity assessment: Peak load, peak displacement, kinetic energy ratio, and stabilization dissipation energy ratio were extracted for the baseline response without material degradation and the response with damage degradation for D-1, D-2, and D-3, respectively. The results are shown in Table 8.

[0171] Table 8 Global Response and Data Validity Judgment for Representative Working Conditions Including Damage Degradation Model

[0172] As shown in Table 8, the kinetic energy ratio of all three operating conditions is 0, and the stabilized dissipation energy ratio is lower than the quality control threshold set in this embodiment. Therefore, subsequent mechanism index calculations were performed. The peak value reduction percentages of all three groups of calculations including damage degradation compared to the baseline calculation without material degradation were lower than... .

[0173] (2) Defect input status calculate: For three representative working conditions, the input energy of defects related to lamination stiffness was extracted, and the contribution of intramembrane channels, bending channels, and the proportion of bending channels in the defect input were obtained based on auxiliary defect input post-processing. For D-3, the membrane-bending decomposition was performed by free segment diagnostic decomposition based on the specified defect displacement field and lamination ABD stiffness relationship in the input file; its total input severity was still calculated using the output of the auxiliary calculation. The specific defect input status indicators are shown in Table 9.

[0174] Table 9 Defect Input State Indicators for Representative Working Conditions with Damage Degradation Model

[0175] As shown in Table 9, D-1 has the highest defect amplitude and the highest lamination stiffness-related defect input energy, but its defect input bending channel ratio is relatively low, indicating it is an intramembrane type defect input. D-2 has a lower geometric amplitude and a higher defect input bending channel ratio, indicating that this defect has a higher bending component under the current layup stiffness system. D-3 has a lower stiffness-weighted defect input energy, and its defect input bending channel ratio is between that of D-1 and D-2, which can be considered a mixed-type defect input.

[0176] The results show that the defect amplitude, stiffness-weighted energy and bending channel ratio can describe the input state from different levels. Further analysis is needed to determine whether it has been transformed into pre-peak localization by combining the axial compression path.

[0177] (3) Axial compression path status calculate: For the three working conditions, the membrane-bending path and the local radial non-uniform deformation path were extracted from the baseline response without material degradation and the response with damage degradation. The path state was mainly determined based on the baseline response without material degradation, while the response with damage degradation was used to check whether the path parameters changed significantly after the introduction of damage. The specific axial compression path state parameters are shown in Table 10.

[0178] Table 10. Axial compression path status indicators for representative working conditions including damage degradation model

[0179] As shown in Table 10, the local radial non-uniform deformation increment before the peak value in all three working conditions exceeds the threshold value of this embodiment. mm, indicating that local deformation has developed before the peak value. The proportion of bending channel participation in D-1 is... The level was already high at that time, and then remained relatively stable until the peak; D-2 ​​and D-3 from The proportion of the bending channel involved in the peak point further increases. According to Equation (40), the axial compression path state of all three working conditions is determined to be "local buckling development type before peak".

[0180] The path indices of the baseline response without material degradation and the response with damage degradation are similar, indicating that damage degradation has little impact on the geometric path before the peak; the localized path before the peak remains the main geometric feature in the peak formation process.

[0181] (4) Damage involvement status judge: In the damage calculation, the combined maximum failure index and damage triggering path point are obtained from equations (26) to (29). The peak neighborhood tolerance is set according to this embodiment. ,when Damage is considered to be triggered before or near the peak value. This is based on the peak value reduction caused by damage degradation. To determine whether the damage significantly alters the peak load, the specific damage participation status is shown in Table 11.

[0182] Table 11 Damage Participation Status of Representative Working Conditions Including Damage Degradation Model

[0183] As shown in Table 11, failure indicators were triggered in all three operating conditions. Specifically, D-1 was triggered in the earlier path phase, D-2 was triggered before the peak value but close to it, and D-3 was triggered near the peak value. The three operating conditions... All are below the threshold of this embodiment. This indicates that the peak load was not significantly reduced after the damage risk occurred. According to Equation (41), all three working conditions are classified as "damage risk before or near the peak value but not sensitive to the peak value".

[0184] (5) Combined diagnostic results: Following step S7, the defect input status, axial compression path status, and damage participation status are combined to obtain the joint diagnostic results shown in Table 12.

[0185] Table 12. Combined diagnostic results for representative working conditions including damage and degradation models.

[0186] This embodiment illustrates that the damage branch of the present invention can distinguish between two types of situations: "damage risk triggering" and "damage significantly changing the peak load". Failure index triggering is present in D-1, D-2, and D-3, and the triggering location is before or near the peak value; the peak value reduction ratio in all three cases is less than... Peak load is not sensitive to damage degradation. Combined with the axial compression path index, all three working conditions show a pre-peak local buckling development type, and their combined diagnostic result is "pre-peak local buckling development with damage risk type".

[0187] This result indicates that when damage variables appear, the program first determines... and , and then combine The primary mechanism category is given. In this embodiment, the damage state provides additional risk descriptions, and the peak formation primary path is still controlled by geometric localization. This determination avoids classifying the structure as damage-driven failure solely based on failure index triggering.

[0188] In the implementation of this invention, it also includes: (1) The initial geometric defect field can come from CMM, DIC, laser scanning, finite element initial mesh, linear buckling mode or artificially constructed defects.

[0189] (2) The input energy of defects related to laminated stiffness can be calculated using auxiliary linear elasticity or geometric nonlinearity. For defects with large measured values ​​or unstable auxiliary paths, auxiliary linear elasticity can be used to improve the repeatability of the index.

[0190] (3) The membrane-bending energy path can be calculated from the cross-sectional force and bending moment of the shell element, or it can be obtained by fitting the stress and strain at the point of the shell cross-section along the thickness direction.

[0191] (4) Local radial non-uniform deformation can be measured by the free segment RMS index, the maximum absolute radial displacement, the local area RMS, or the equivalent index within the DIC observation area.

[0192] (5) Damage indicators can be Hathin, Puck, maximum stress, maximum strain, stiffness degradation variable, failure index or damage dissipation energy.

[0193] (6) The classification threshold can be adjusted according to the structure type, material system, test noise level, numerical stability requirements and engineering design requirements. A uniform threshold caliber is used in the same batch of comparative samples.

[0194] (7) This invention is applicable to thin-walled cylindrical shells made of composite materials, and also to other thin-walled load-bearing structures made of composite materials that are mainly subjected to axial compression or axial compression, including thin-walled tubes, cylindrical sections, connecting cylinders, reinforcing cylindrical sections and locally variable stiffness shell sections.

[0195] This invention provides a system for diagnosing the buckling mechanism of thin-walled composite structures, comprising: The data acquisition module is used to acquire finite element calculation results or post-test processing data of the thin-walled composite material structure to be analyzed. The data includes axial compression response data and optional damage data. The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature changes. The optional damage data includes failure index, damage variables, stiffness degradation indicators, and equivalent damage indices. The data judgment module is used to determine whether the finite element calculation results or post-test processing data are valid based on the axial compression response data. The axial compression response module is used to obtain the pre-peak membrane-bending path index based on the axial compression response data to distinguish the timing of buckling, and to obtain the local radial non-uniform deformation index to quantify the degree of local buckling deformation; and to determine the axial compression path state based on the pre-peak membrane-bending path index and the local radial non-uniform deformation index. The damage participation module is used to obtain damage participation indicators based on optional damage data, which are used to distinguish the degree of impact of damage on the peak value; and to determine the damage participation status based on the damage participation indicators. The main mechanism module is used to combine and match the axial compression path state and the damage participation state to obtain the buckling mechanism category.

[0196] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of diagnosing buckling mechanisms in thin-walled composite structures, characterized by, include: Obtain the finite element calculation results or post-test data of the thin-walled composite material structure to be analyzed, including axial compression response data and optional damage data; The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature variations; the optional damage data includes failure indices, damage variables, stiffness degradation indicators, and equivalent damage indices. The validity of the finite element calculation results or post-test data can be determined based on the axial compression response data. Based on the axial compression response data, the pre-peak membrane-bending path index is obtained to distinguish the timing of buckling, and the local radial non-uniform deformation index is obtained to quantify the degree of local buckling deformation. The axial compression path state is determined based on the peak pre-film-bend path index and the local radial non-uniform deformation index. Damage participation indicators are obtained from optional damage data to distinguish the degree of impact of damage on the peak value. Determine the damage participation status based on damage participation indicators; The buckling mechanism category is obtained by combining and matching the axial compression path state and the damage participation state. The pre-peak membrane-bending path index includes the pre-peak bending channel participation ratio increment; the local radial non-uniform deformation index includes the pre-peak local radial non-uniform deformation increment and the post-peak localization amplification factor. The finite element calculation results or post-experiment data also include: basic model data and initial defect data; the basic model data includes geometric parameters, free segment range, lamination information, single-layer material parameters, and shell element region information; the initial defect data includes the initial geometric defect field; Based on the basic model data and initial defect data, traditional geometric amplitude indices of composite thin-walled structures are obtained, as well as the defect input energy and the proportion of defect input bending channels related to lamination stiffness; the traditional geometric amplitude indices include the maximum absolute radial deviation and the root mean square defect amplitude. Determine the geometric amplitude state based on traditional geometric amplitude indices; The stiffness-weighted defect input level is determined based on the defect input energy related to the layer stiffness. Determine the defect input type based on the proportion of curved channels in the defect input; The defect input status is obtained based on the geometric amplitude status, stiffness-weighted defect input level, and defect input type. The buckling mechanism diagnosis results are obtained based on the defect input status, axial compression path status, damage participation status, and buckling mechanism category.

2. The composite thin-walled structure buckling mechanism diagnostic method of claim 1, wherein, Determining the validity of finite element calculation results or post-experiment data based on axial compression response data includes: When the input data is finite element calculation result data, the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak value are calculated based on the axial compression response data. Define a preset numerical quality threshold; When the maximum kinetic energy ratio and the maximum stabilization dissipation energy ratio in the effective loading segment before the peak are both less than or equal to the preset numerical mass threshold, the finite element calculation results are considered valid. When the input data is post-test data, the validity is judged by the integrity of the load-displacement curve, the identifiability of the peak point, the effective measurement area of ​​the displacement field, and the data noise level. If the test data covers the path near the peak point, the peak point is effectively identified, the effective measurement area of ​​the displacement field is sufficient, and the noise level does not exceed the preset threshold, then the post-processed test data is considered valid.

3. The method for diagnosing the buckling mechanism of thin-walled composite structures according to claim 1, characterized in that, The axial compression path state is determined according to the following formula: In the formula, The percentage increase of the bending channel participation before the peak; This represents the increment of local radial non-uniform deformation before the peak value; This is the localization amplification factor after the peak value; The threshold value for the pre-peak bending channel increment; This is the threshold for the local radial non-uniform deformation increment before the peak value; This is the threshold for localized amplification after the peak. This is the axial compression path state.

4. The method for diagnosing the buckling mechanism of thin-walled composite structures according to claim 1, characterized in that, The damage participation indicators include damage or degradation triggering markers, damage triggering path points, and the percentage reduction in peak value caused by damage and degradation.

5. The method for diagnosing buckling mechanisms of thin-walled composite structures according to claim 4, characterized in that, The damage participation status is determined according to the following formula: In the formula, This serves as a marker for damage or degradation. This is the damage triggering path point; The percentage decrease in peak value due to damage and degradation; The threshold for determining whether damage or degradation has caused a decrease in peak value; For peak neighborhood tolerance; This indicates a state of damage involvement.

6. A system for diagnosing the buckling mechanism of a composite thin-walled structure as described in claim 1, characterized in that, include: The data acquisition module is used to acquire finite element calculation results or post-test processing data of the thin-walled composite material structure to be analyzed. The data includes axial compression response data and optional damage data. The axial compression response data includes load-displacement curves, energy history, nodal displacement fields, shell element section forces, shell element section bending moments, mid-surface strain, and curvature changes. The optional damage data includes failure index, damage variables, stiffness degradation indicators, and equivalent damage indices. The data judgment module is used to determine whether the finite element calculation results or post-test processing data are valid based on the axial compression response data. The axial compression response module is used to obtain the pre-peak membrane-bending path index based on the axial compression response data to distinguish the timing of buckling, and to obtain the local radial non-uniform deformation index to quantify the degree of local buckling deformation; and to determine the axial compression path state based on the pre-peak membrane-bending path index and the local radial non-uniform deformation index. The damage participation module is used to obtain damage participation indicators based on optional damage data, which are used to distinguish the degree of impact of damage on the peak value; and to determine the damage participation status based on the damage participation indicators. The main mechanism module is used to combine and match the axial compression path state and the damage participation state to obtain the buckling mechanism category; The pre-peak membrane-bending path index includes the pre-peak bending channel participation ratio increment; the local radial non-uniform deformation index includes the pre-peak local radial non-uniform deformation increment and the post-peak localization amplification factor. The finite element calculation results or post-experiment data also include: basic model data and initial defect data; the basic model data includes geometric parameters, free segment range, lamination information, single-layer material parameters, and shell element region information; the initial defect data includes the initial geometric defect field; Based on the basic model data and initial defect data, traditional geometric amplitude indices of composite thin-walled structures are obtained, as well as the defect input energy and the proportion of defect input bending channels related to lamination stiffness; the traditional geometric amplitude indices include the maximum absolute radial deviation and the root mean square defect amplitude. Determine the geometric amplitude state based on traditional geometric amplitude indices; The stiffness-weighted defect input level is determined based on the defect input energy related to the layer stiffness. Determine the defect input type based on the proportion of curved channels in the defect input; The defect input status is obtained based on the geometric amplitude status, stiffness-weighted defect input level, and defect input type. The buckling mechanism diagnosis results are obtained based on the defect input status, axial compression path status, damage participation status, and buckling mechanism category.

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