Efficient simulation method for continuous laser ablation of CFRP laminated plate

Abstract

The invention discloses an efficient simulation method for continuous laser ablation of a CFRP laminated plate, and relates to the technical field of laser weapon damage high-speed aircrafts.The method comprises the steps that characteristic parameters of the CFRP laminated plate are designed based on dimensional analysis, and a three-dimensional geometric model considering material anisotropy is established; the method comprises the following steps: representing thermal-mechanical characteristics of a CFRP laminated plate in a high-temperature environment based on multi-scale thermal-mechanical analysis, and constructing a neural network model; defining a material constitutive relation related to temperature, and setting a displacement boundary and a multi-physics coupling loading condition by applying an ALE adaptive grid technology; establishing a multi-mechanism coupled laser ablation analysis model, and accurately representing an energy transfer process; high-precision tracking and evolution simulation of an ablation boundary are realized by adopting a method of combining a dynamic life-death unit and a self-adaptive grid reconstruction technology; and obtaining damage evaluation data through a restart analysis technology. The method provides important technical support for damage efficiency evaluation of laser weapons for intercepting high-speed aircrafts.

Description

Technical Field

[0001] This invention relates to the field of laser weapon damage to high-speed aircraft, and in particular to an efficient simulation method for continuous laser ablation of CFRP laminates. Background Technology

[0002] Carbon fiber reinforced plastic (CFRP) composites have become ideal materials for high-speed aircraft structural design due to their excellent specific strength, specific stiffness, and structural designability. However, with the development of high-energy laser weapon technology, the potential threat of high-power-density lasers to high-speed aircraft structures is becoming increasingly prominent, making the study of the ablation behavior of CFRP composites under continuous laser irradiation of great significance. Numerical simulation technology provides an effective way to solve this problem. Compared with traditional experimental research methods, numerical simulation can not only significantly reduce research costs, but also overcome the technical bottlenecks of experimental testing, achieving accurate characterization of complex ablation behavior and the coupling effect of multiple ablation mechanisms. However, existing numerical simulation methods still have several key limitations: First, the currently widely used ALE combined with UMESHMOTION method is only suitable for simplified simulation of single-layer composite plates, and it is difficult to accurately reflect the complex ablation behavior of multi-layer and multi-oriented layup composite structures in actual engineering; second, although the traditional temperature threshold element killing method is simple to implement, it cannot distinguish the contribution of different ablation mechanisms such as pyrolysis and oxidation, and the computational efficiency is significantly reduced due to the need to set high-density meshes. These technical limitations severely restrict the application value of numerical simulation in engineering practice.

[0003] Therefore, there is an urgent need to develop an efficient numerical simulation method that can not only optimize and improve computational efficiency, but also accurately simulate the laser ablation behavior of CFRP laminates. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention discloses an efficient simulation method for continuous laser ablation of CFRP laminates. This method not only optimizes and improves computational efficiency but also quantitatively analyzes the coupling effects of multiple ablation mechanisms, thereby accurately simulating the laser ablation behavior of CFRP laminates and obtaining multi-dimensional damage assessment data such as ablation morphology evolution, dynamic ablation rate, transient temperature field distribution, structural deformation field, and stress field.

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

[0006] An efficient simulation method for continuous laser ablation of CFRP laminates includes the following steps:

[0007] s1. Based on dimensional analysis, design key characteristic parameters such as single-layer thickness, layup sequence, total number of layups and fiber type of CFRP laminate, and establish a three-dimensional geometric model considering material anisotropy;

[0008] s2. Based on multi-scale thermo-mechanical analysis to characterize the thermo-mechanical properties of CFRP laminates under high temperature conditions, a neural network model is constructed to quickly obtain the degradation law of the thermo-mechanical properties of CFRP laminates under different temperature rise rates;

[0009] s3. Based on the calculation results of step s2, define the temperature-dependent material constitutive relation; refine the irradiated area and ablation boundary; apply ALE adaptive mesh technology to the numerical model to prevent distortion during the ablation process; and set displacement boundaries and multiphysics coupling loading conditions.

[0010] s4. Considering the interaction of multiple phases such as laser, fluid, solid and even plasma, establish a multi-mechanism coupled laser ablation analysis model to accurately characterize ablation processes such as pyrolysis, oxidation and sublimation;

[0011] s5. By combining dynamic birth and death elements with adaptive mesh technology, and in conjunction with the energy transfer process in step s4, high-precision tracking and evolution simulation of the ablation boundary are achieved;

[0012] s6. By using the restart analysis technique, the laser ablation process is solved by iterating through step s5 in sequence, and damage assessment data in multiple dimensions, including ablation amount of various ablation mechanisms, dynamic ablation rate, transient temperature field distribution, stress field, etc., are obtained.

[0013] Optionally, in step s1, the characteristic parameters of the CFRP laminate are designed based on dimensional analysis, and a three-dimensional geometric model considering the anisotropy of the material is established, as follows:

[0014] s11. To address the performance differences of CFRP laminates, a dimensionless analysis model is established, taking into account the influence of single-layer thickness, layup sequence, total number of layups, fiber type, fiber thermal and mechanical properties, and characteristic parameters.

[0015] s12. Select the following fundamental physical quantities as the geometric characteristic length of the single-layer board, single-layer thickness, layup sequence direction, fiber density, fiber specific heat, fiber thermal conductivity, fiber Young's modulus, and fiber shear modulus: N = f(h, l; θ; k) f ,c f ,ρ f E f G f ), where N is the total number of laminate layers, h is the single-layer thickness, l is the characteristic length of the geometric configuration, θ is the layup sequence direction, and ρ f For fiber density, cf For fiber specific heat, k f For the fiber thermal conductivity coefficient, E f G represents the Young's modulus of the fiber. f It is the fiber shear modulus;

[0016] s13. Through dimensionless analysis, design representative CFRP laminate types with different lamination methods;

[0017] s14. Based on the design type in step s13, establish a three-dimensional geometric model of the anisotropic CFRP composite material.

[0018] Optionally, in step s2, based on multi-scale thermo-dynamic analysis to characterize the thermo-dynamic properties of CFRP laminates under high-temperature conditions, a neural network model is constructed to quickly obtain the degradation law of the thermodynamic properties of CFRP laminates under different temperature rise rates, as follows:

[0019] s21. Considering the influence of environmental conditions, temperature rise rate and material form, the mass loss and energy dissipation of CFRP laminates with temperature change are obtained through thermogravimetric analysis and differential scanning calorimetry experiments.

[0020] s22. Based on the data results from step s21, establish a microscopic analysis model that includes pyrolysis reaction, oxidation reaction and phase change reaction;

[0021] s23. Couple the microscopic analysis model of step s22 with the mixing law theory of composite materials to establish a multi-scale thermo-mechanical analysis model of CFRP laminate, and characterize the thermophysical and mechanical properties of the composite laminate;

[0022] s24. Based on the thermo-mechanical analysis model in step s23, establish a database with a training set to validation set ratio of 5:1;

[0023] s25. Introduce a feedforward neural network model, establishing an input layer, hidden layer, and output layer. The input layer uses air environment, temperature rise rate, and temperature range as inputs, respectively, and the output layer uses thermodynamic properties. Train the model using the training set from step s24, employing R... 2 The coefficient of determination is used to evaluate the prediction error. The hidden layer weights are corrected by batch gradient descent and automatic differentiation, and the model is then trained.

[0024] s26. Use the validation set in step s24 to validate the training model in step s25. After the prediction error of the neural network model meets the accuracy requirements, stop training and save the corresponding grid structure and parameters. Input the proposed air environment, temperature rise rate and temperature range into the trained neural network model to quickly obtain the evolution law of thermodynamic performance under the condition.

[0025] Optionally, in step s4, considering the interaction of multiple phase states, a multi-mechanism coupled laser ablation analysis model is established to accurately characterize the energy transfer process, as follows:

[0026] s41. For the three-dimensional geometric model in step s1, the differential thermogravimetric method is used to decouple the ablation reaction mechanism, reaction sequence and ablation heat generated during the reaction of CFRP laminate under high temperature conditions;

[0027] s42. Based on the data results from step s41, analyze the interaction between the laser, the ambient airflow, and the CFRP composite material, and construct an ablation analysis model that includes laser, pyrolysis, oxidation, and phase transformation damage effects;

[0028] s43. Quantitative characterization of the destruction process of different ablation mechanisms inside the material, thereby enabling reliable acquisition of ablation energy, ablation quality, ablation rate and ablation depth.

[0029] Optionally, in step s5, a method combining dynamic birth and death elements with adaptive mesh reconstruction technology is adopted, combined with the energy transfer process in step s4, to achieve high-precision tracking and evolution simulation of the ablation boundary, as detailed below:

[0030] s51. Apply the laser effect, pyrolysis, oxidation, and phase transformation damage mechanisms from the ablation analysis model in step s42 as thermal loads to the finite element model;

[0031] s52. Apply the adaptive mesh method to dynamically describe the moving direction and speed of nodes in the ablation region, and set reasonable node movement times and mesh redrawing frequency to dynamically track mesh quality and boundary deformation during the ablation process;

[0032] s53. The microscopic analysis model of the element characteristic correlation step s2 of the finite element model, each element is a cell composed of fibers and matrix, and the characteristic parameters of the element include mass, volume, temperature and component content;

[0033] s54. By combining the boundary deformation dynamic tracking in step s52 and the element characteristics in step s53, the instantaneous element ablation depth is obtained;

[0034] s55. The method of birth and death of cells is used to describe the removal of ablation material. The cell killing is controlled by the cumulative amount of cell ablation depth, so as to achieve high-precision tracking and evolution simulation of ablation boundary.

[0035] The beneficial effects of this invention are that the method proposed in this invention can clearly define the damage threshold, failure mode, and ablation mechanism of CFRP composite material under laser irradiation-force failure. It can accurately obtain key parameters such as the ablation depth, temperature field, and stress field distribution of CFRP laminates, providing an effective analytical means to reveal the multi-mechanism coupled ablation process of pyrolysis, oxidation, etc. This not only adds new connotations to the cutting-edge topic of laser-matter interaction, but also provides important guidance for the effectiveness evaluation of laser weapons intercepting high-speed aircraft. Attached Figure Description

[0036] Figure 1 This is a flowchart of an efficient simulation method for continuous laser ablation of CFRP laminates according to the present invention.

[0037] Figure 2 This is a schematic diagram of a dimensional analysis model according to an embodiment of the present invention;

[0038] Figure 3 The following is a three-dimensional geometric model of different ply types shown in an embodiment of the present invention, wherein (a) is [45°, 0°, -45°, 90°] 2s (b) is [0°, 90°, 0°, 90°] 2s ;

[0039] Figure 4 This is a diagram illustrating a feedforward neural network structure according to an embodiment of the present invention;

[0040] Figure 5 This is a diagram illustrating the density degradation law of CFRP composite material according to an embodiment of the present invention;

[0041] Figure 6 This is a diagram illustrating the specific heat capacity degradation law of CFRP composite material according to an embodiment of the present invention;

[0042] Figure 7 This is a diagram illustrating the degradation of elastic modulus and shear modulus of CFRP composite material according to an embodiment of the present invention;

[0043] Figure 8 This is a diagram illustrating the degradation of the transverse and longitudinal thermal conductivity coefficients of a CFRP composite material according to an embodiment of the present invention.

[0044] Figure 9 This is a schematic diagram of grid encryption according to an embodiment of the present invention;

[0045] Figure 10 This is a schematic diagram of the ablation boundary shown in an embodiment of the present invention;

[0046] Figure 11 This is a transient temperature field distribution diagram of a T700 / BA9916 laminate under laser irradiation, as shown in an embodiment of the present invention.

[0047] Figure 12 This is a transient stress field distribution diagram of a T700 / BA9916 laminate under laser irradiation, as shown in an embodiment of the present invention.

[0048] Figure 13 This is a transient ablation depth distribution diagram of a T700 / BA9916 laminate under various ablation mechanisms under laser irradiation, as shown in an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to represent selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] An efficient simulation method for continuous laser ablation of CFRP laminates, such as Figure 1 As shown, it includes the following steps:

[0051] s1. Based on dimensional analysis, design the characteristic parameters of CFRP laminates and establish a three-dimensional geometric model considering material anisotropy; the details are as follows:

[0052] s11. Considering the influence of single-layer thickness, layup sequence, total number of layups, fiber type, fiber thermophysical and mechanical properties, a dimensionless analysis model is established with layup type as the target parameter, such as... Figure 2 As shown;

[0053] s12. Select the following fundamental physical quantities as the geometric characteristic length of the single-layer board, single-layer thickness, layup sequence direction, fiber density, fiber specific heat, fiber thermal conductivity, fiber Young's modulus, and fiber shear modulus: N = f(h, l; θ; k) f ,c f ,ρ f E f G f ), where N is the total number of laminate layers, h is the single-layer thickness, l is the characteristic length of the geometric configuration, θ is the layup sequence direction, and ρ f For fiber density, c fFor fiber specific heat, k f For the fiber thermal conductivity coefficient, E f G represents the Young's modulus of the fiber. f It is the fiber shear modulus;

[0054] s13. Through dimensionless analysis, design representative CFRP laminate types with different lamination methods;

[0055] s14. Based on the design type in step s13, establish a three-dimensional geometric model of the anisotropic CFRP composite material. An example of partial laminate layup is shown below. Figure 3 As shown, (a) the laminate ply type is [45°, 0°, -45°, 90°]. 2s (a) The laminate consists of 16 layers, and the material properties after lamination are isotropic in the transverse direction; (b) The layup type of the laminate is [0°, 90°, 0°, 90°]. 2s It consists of 16 layers, and the material properties after lamination are anisotropic.

[0056] s2. Based on multi-scale thermo-dynamic analysis to characterize the thermo-dynamic properties of CFRP laminates under high-temperature conditions, a neural network model is constructed to quickly obtain the degradation law of the thermo-dynamic properties of CFRP laminates under different temperature rise rates; the details are as follows:

[0057] s21. Considering the influence of environmental conditions, temperature rise rate and material form, the mass loss and energy dissipation of CFRP laminates with temperature change are obtained through thermogravimetric analysis and differential scanning calorimetry experiments.

[0058] s22. Based on the data results from step s21, a microscopic analysis model incorporating pyrolysis, oxidation, and phase transition reactions is established, and the analysis is as follows:

[0059]

[0060]

[0061]

[0062] In the formula, J m E represents the pre-exponential factor of epoxy resin. m The value represents the activation energy of the epoxy resin, where n represents the reaction order, and J. f E represents the prefinite factor of carbon fiber. f Represents the activation energy of carbon fiber. This represents the volume content of epoxy resin. ρ represents the volume fraction of carbon fiber. m ρ represents the density of the epoxy resin matrix. f Represents the density of carbon fiber, ρ p Represents the density of residual carbon after pyrolysis. Represents the volume content of residual carbon after pyrolysis;

[0063] s23. Couple the mesoscopic analysis model of step s22 with the mixing law theory of composite materials to establish a multi-scale thermo-mechanical analysis model for the CFRP laminate, characterizing the thermophysical and mechanical properties of the composite laminate, as shown in the following formulas:

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071] In the formula, ρ, c, k i E i and G i These represent the density, specific heat capacity, Young's modulus, and shear modulus of the CFRP monolayer, respectively. Subscript 1 indicates the direction along the fiber bundle (defined as longitudinal), subscript 2 indicates the direction perpendicular to the fiber bundle (defined as transverse), subscripts m, f, and p represent the composite material components epoxy resin, carbon fiber, and pyrolysis residue, respectively, superscript 0 represents the material properties of the corresponding components at room temperature, a is an experimental correction value, and Q... m This represents the thermal decomposition of epoxy resin;

[0072] s24. Based on the thermo-mechanical analysis model in step s23, establish a database with a training set to validation set ratio of 5:1. The input layer of the training set is an air environment with a temperature rise rate of 100–1000℃ / s and an interval of 100℃ / s, and a temperature range of 0–3000℃ with an interval of 100℃. The input layer of the validation set is an air environment with temperature rise rates of 840℃ / s and 860℃ / s, and a temperature range of 0–3000℃ with an interval of 100℃.

[0073] s25. Introduce a feedforward neural network model, and establish the model's input layer, hidden layer, and output layer, as follows: Figure 4 As shown, air environment, temperature rise rate, and temperature range are used as input layers, and thermodynamic properties (density, specific heat capacity, longitudinal and transverse thermal conductivity, elastic modulus, and shear modulus) are used as output layers. Training is performed using the training set from step s24, and R is used. 2The coefficient of determination is used to evaluate the prediction error. The hidden layer weights are corrected by batch gradient descent and automatic differentiation, and the model is then trained.

[0074] s26. Use the validation set from step s24 to validate the trained model from step s25. Once the prediction error of the neural network model meets the accuracy requirements, stop training and save the corresponding grid structure and parameters. Input the air environment, temperature rise rate of 850℃ / s, and temperature range of 0~3000℃ into the trained neural network model to quickly obtain the thermodynamic performance degradation law under this condition, such as... Figure 5-8 As shown.

[0075] Figure 5 It was found that when the temperature exceeds 600℃, the density begins to decrease rapidly with the increase of temperature. The density decreases slowly between 1000 and 1500℃. When the temperature exceeds 1500℃, the specific heat capacity decreases rapidly again, and the density approaches failure at 3000℃. Figure 6 It was found that when the temperature exceeds 600℃, the specific heat capacity begins to decrease rapidly with increasing temperature. Between 1000 and 1500℃, the decrease is slower. However, when the temperature exceeds 1500℃, the specific heat capacity decreases rapidly again, and at 3000℃, the density approaches failure. The preliminary assessment is that the phased changes in density and specific heat capacity are due to the following: the first rapid decrease is due to the pyrolysis of the resin matrix, and the second decrease is mainly due to the oxidation of the carbon fibers.

[0076] Figure 7 This diagram illustrates the degradation of mechanical properties with temperature, where blue represents the longitudinal elastic modulus E1, red represents the transverse elastic modulus E2, and green and purple represent the in-plane shear modulus G, respectively. 12 and G 13 When the temperature exceeds 600℃, the transverse elastic modulus and shear modulus of the composite material show a significant decreasing trend; when the temperature rises above 1500℃, these two modulus parameters decay sharply and tend to fail. This phenomenon mainly stems from the strong dependence of the transverse properties of the composite material on the resin matrix: under high-temperature conditions, the resin matrix undergoes a pyrolysis reaction, destroying its structural integrity, thus leading to rapid degradation of transverse mechanical properties. It is worth noting that when the temperature exceeds 1500℃, the longitudinal elastic modulus also begins to decrease sharply; when the temperature reaches 3000℃, the longitudinal modulus almost completely fails. This is because the longitudinal properties of the composite material are mainly dominated by carbon fibers; in an oxidizing environment, carbon fibers undergo an oxidation reaction, significantly reducing their load-bearing capacity, thus leading to rapid degradation of the longitudinal mechanical properties of the composite material.

[0077] Figure 8The graph shows the degradation of thermal conductivity with temperature, where blue represents the transverse direction and red represents the longitudinal direction. Analysis reveals that the transverse thermal conductivity increases within the temperature range of 35℃ to 600℃; however, it begins to decrease sharply above 600℃; and at temperatures above 1500℃, the transverse thermal conductivity essentially fails. This variation can be attributed to two competing mechanisms: in the low-temperature stage (35–600℃), the thermal expansion of the resin matrix reduces the porosity of the material, thus enhancing thermal conductivity; while in the high-temperature stage (>600℃), since the transverse properties mainly depend on the resin matrix, its thermal conductivity decreases significantly as the resin matrix undergoes pyrolysis. Furthermore, it was found that the longitudinal thermal conductivity decays rapidly above 1500℃; and at 3000℃, the longitudinal thermal conductivity is almost completely lost. This phenomenon stems from the strong dependence of longitudinal properties on carbon fibers: after the carbon fibers undergo oxidation, their inherent high thermal conductivity is destroyed, leading to a sharp degradation of the composite material's longitudinal thermal conductivity.

[0078] s3. Based on the calculation results of step s2, define the temperature-dependent material constitutive relation; refine the irradiated region and ablation boundary; apply ALE adaptive meshing technology to the numerical model to prevent distortion during the ablation process; set displacement boundaries and multiphysics coupling loading conditions; as follows:

[0079] s31. Based on the data results from step s26, input the physical property parameters and define the temperature-related material constitutive relations in the finite element model;

[0080] s32. The irradiated area and ablation boundary are densified, such as... Figure 9 As shown, ALE adaptive properties are set on the mesh to enhance the accuracy of thermal coupling response and damage evolution capture capability in this region;

[0081] s33. Based on actual working conditions, apply thermal convection and thermal radiation properties to the upper and lower surfaces of the model, and add a completely fixed constraint to the lower surface;

[0082] s34. Set multiphysics coupling loading conditions. To accurately load the laser heat source, a combination of flat-top function and Gaussian function is used to characterize the distribution characteristics of laser heat flux density, as shown in the following equation; when the distance between the node and the irradiation center is less than or equal to r s At this time, the heat flux density remains constant; when the distance between the node and the irradiation center is greater than r... s At that time, the heat flux density gradually decreases according to a Gaussian distribution law;

[0083]

[0084] In the formula, r sLet θ be the radius of the flat-top laser heat source, α be the laser absorptivity, θ be the influence factor, r be the laser emission radius, and q be the input laser power density.

[0085] s4. Considering the interaction of multiple phase states, a multi-mechanism coupled laser ablation analysis model is established to accurately characterize the energy transfer process; specifically as follows:

[0086] s41. For the three-dimensional geometric model in step s1, the differential thermogravimetric method is used to decouple the ablation reaction mechanism, reaction sequence and ablation heat generated during the reaction of CFRP laminate under high temperature conditions;

[0087] s42. Combining the data results from step s41, analyze the interaction between the laser, ambient airflow, and the CFRP composite material. Construct an ablation analysis model incorporating laser, pyrolysis, oxidation, and phase transformation damage effects to characterize boundary ablation behavior, such as... Figure 10 As shown;

[0088] s43. Quantitative characterization of the destruction process of different ablation mechanisms within the material enables reliable acquisition of ablation energy, ablation mass, ablation rate, and ablation depth. The formulas for calculating the oxidation ablation rate and sublimation ablation rate during the destruction process are as follows:

[0089]

[0090]

[0091] In the formula, v o v represents the oxidation rate of carbon fiber. s T represents the sublimation rate of carbon fiber. O A represents the oxidation temperature of carbon fiber. O E represents the pre-oxidation exponent of carbon fiber. O Represents the activation energy of carbon fiber oxidation, R represents the gas constant, and p g p represents the pressure constant term. e E represents the local pressure generated by the flow of pyrolysis gases. S M represents the activation energy for carbon fiber sublimation. C This represents the initial molar mass of a carbon molecule.

[0092] s5. A method combining dynamic birth and death elements with adaptive mesh reconstruction technology, combined with the energy transfer process in step s4, is used to achieve high-precision tracking and evolution simulation of the ablation boundary; specifically as follows:

[0093] s51. Apply the laser effect, pyrolysis, oxidation, and phase transformation damage mechanisms from the ablation analysis model in step s42 as thermal loads to the finite element model;

[0094] s52. Apply the adaptive mesh method to dynamically describe the moving direction and speed of nodes in the ablation region, and set reasonable node movement times and mesh redrawing frequency to dynamically track mesh quality and boundary deformation during the ablation process;

[0095] s53. The microscopic analysis model of the element characteristic correlation step s2 of the finite element model, each element is a cell composed of fibers and matrix, and the characteristic parameters of the element include mass, volume, temperature and component content;

[0096] s54. By combining the boundary deformation dynamic tracking in step s52 and the element characteristics in step s53, the instantaneous element ablation depth is obtained;

[0097] s55. The method of birth and death of cells is used to describe the removal of ablation material. The cell killing is controlled by the cumulative amount of cell ablation depth, so as to achieve high-precision tracking and evolution simulation of ablation boundary.

[0098] s6. Using a restart analysis technique, the laser ablation process is solved by iteratively repeating step s5 to obtain multi-dimensional damage assessment data, including ablation amounts based on various ablation mechanisms, transient temperature field distribution, and stress field; specifically as follows:

[0099] s61. Enter the solver module, perform thermo-mechanical-ablation coupled solution on the finite element model, establish table elements to extract and store element results, such as temperature, stress increment, deformation increment, ablation depth increment, oxidation ablation depth increment and sublimation ablation depth increment, etc.

[0100] s62. The restart analysis technique is adopted to solve the problem in a loop, and the incremental step count, mesh node movement, ablation depth accumulation and element ablation depth are recorded in real time;

[0101] s63. Repeat step s62 until the preset total laser irradiation time is reached, at which point the numerical calculation is paused. This achieves efficient simulation of the ablation behavior of CFRP laminates under continuous laser irradiation, acquiring multi-dimensional damage assessment data including ablation morphology evolution, dynamic ablation rate, transient temperature field distribution, structural deformation field, and stress field. Tables are then created to store the corresponding data, such as... Figure 11-13 As shown.

[0102] Figure 11 In the figure, the solid black line represents the instantaneous temperature evolution at the irradiation center. The three red markers A, B, and C, specifically marked in the figure, correspond to the temperature values ​​at three characteristic moments: 0.2s, 0.43s, and 0.7s, respectively, and are accompanied by the temperature field distribution cloud maps of the irradiated surface at the corresponding moments. Analysis reveals that the temperature exhibits a clear radial diffusion characteristic on the irradiated surface, which is due to the anisotropic thermal conductivity of carbon fibers. Figure 12In the figure, the solid black line represents the instantaneous Mises stress change at the irradiation center. The four red dots A, B, C, and D represent the stress at times 0.1s, 0.3s, 0.5s, and 0.7s, respectively, and stress distribution contour maps at the corresponding times are also provided. It was found that the stress field at the irradiation center increases exponentially with increasing irradiation time, and the stress also extends along the fiber direction. Figure 13 In the figure, the solid black line represents the instantaneous change in the total ablation depth at the irradiation center. The four red dots A, B, C, and D represent the total ablation depth at 0.1s, 0.3s, 0.5s, and 0.7s, respectively, and ablation distribution cloud maps are given at the corresponding times. The bar charts indicate the proportion of each ablation mechanism at different times. Analysis revealed that the ablation depth increases monotonically with irradiation time, and the ablated area on the surface exhibits radial expansion characteristics. Fiber sublimation is the main ablation mechanism, and its contribution rate continuously increases with irradiation time.

[0103] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A highly efficient simulation method for continuous laser ablation of CFRP laminates, characterized in that, Includes the following steps: s1. Design characteristic parameters of CFRP laminate based on dimensional analysis and establish a three-dimensional geometric model considering material anisotropy; s2. Based on multi-scale thermo-mechanical analysis to characterize the thermo-mechanical properties of CFRP laminates under high temperature conditions, a neural network model is constructed to quickly obtain the degradation law of the thermo-mechanical properties of CFRP laminates under different temperature rise rates; s3. Based on the calculation results of step s2, define the temperature-dependent material constitutive relation; refine the irradiated area and ablation boundary; apply ALE adaptive mesh technology to the numerical model to prevent distortion during the ablation process; and set displacement boundaries and multiphysics coupling loading conditions. s4. Considering the interaction of multiple phase states, establish a multi-mechanism coupled laser ablation analysis model to accurately characterize the energy transfer process; s5. By combining dynamic birth and death elements with adaptive mesh reconstruction technology, and in conjunction with the energy transfer process in step s4, high-precision tracking and evolution simulation of the ablation boundary are achieved; s6. By using the restart analysis technique, the laser ablation process is solved by iterating through step s5 in sequence, and damage assessment data including ablation amount of various ablation mechanisms, transient temperature field distribution, and stress field in multiple dimensions are obtained.

2. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 1, characterized in that, In step s1, the characteristic parameters of the CFRP laminate are designed based on dimensional analysis, and a three-dimensional geometric model considering the anisotropy of the material is established, as follows: s11. To address the performance differences of CFRP laminates, a dimensionless analysis model is established, taking into account the influence of single-layer thickness, layup sequence, total number of layups, fiber type, fiber thermal and mechanical properties, and characteristic parameters. s12. Select the following fundamental physical quantities as the geometric characteristic length of the single-layer board, single-layer thickness, layup sequence direction, fiber density, fiber specific heat, fiber thermal conductivity, fiber Young's modulus, and fiber shear modulus: N = f(h, l; θ; k) f ,c f ,ρ f E f G f ), where N is the total number of laminate layers, h is the single-layer thickness, l is the characteristic length of the geometric configuration, θ is the layup sequence direction, and ρ f For fiber density, c f For fiber specific heat, k f For the fiber thermal conductivity coefficient, E f G represents the Young's modulus of the fiber. f It is the fiber shear modulus; s13. Through dimensionless analysis, design representative CFRP laminate types with different lamination methods; s14. Based on the design type in step s13, establish a three-dimensional geometric model of the anisotropic CFRP composite material.

3. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 1, characterized in that, In step s2, the thermodynamic properties of CFRP laminates under high-temperature conditions are characterized based on multi-scale thermodynamic analysis. A neural network model is constructed to quickly obtain the degradation law of the thermodynamic properties of CFRP laminates under different temperature rise rates, as detailed below: s21. Considering the influence of environmental conditions, temperature rise rate and material form, the mass loss and energy dissipation of CFRP laminates with temperature change are obtained through thermogravimetric analysis and differential scanning calorimetry experiments. s22. Based on the data results from step s21, a microscopic analysis model incorporating pyrolysis, oxidation, and phase transition reactions is established, and the analysis is as follows: In the formula, J m E represents the pre-exponential factor of epoxy resin. m The value represents the activation energy of the epoxy resin, where n represents the reaction order, and J. f E represents the prefinite factor of carbon fiber. f Represents the activation energy of carbon fiber. This represents the volume content of epoxy resin. ρ represents the volume fraction of carbon fiber. m ρ represents the density of the epoxy resin matrix. f ρ represents the density of carbon fiber. p Represents the density of residual carbon after pyrolysis. Represents the volume content of residual carbon after pyrolysis; s23. Couple the microscopic analysis model of step s22 with the mixing law theory of composite materials to establish a multi-scale thermo-mechanical analysis model of CFRP laminate, and characterize the thermophysical and mechanical properties of the composite laminate. s24. Based on the thermo-mechanical analysis model in step s23, establish a database with a training set to validation set ratio of 5:1; s25. Introduce a feedforward neural network model, establishing an input layer, hidden layer, and output layer. The input layer uses air environment, temperature rise rate, and temperature range as inputs, respectively, and the output layer uses thermodynamic properties. Train the model using the training set from step s24, employing R... 2 The coefficient of determination is used to evaluate the prediction error. The hidden layer weights are corrected by batch gradient descent and automatic differentiation, and the model is then trained. s26. Use the validation set in step s24 to validate the training model in step s25. After the prediction error of the neural network model meets the accuracy requirements, stop training and save the corresponding grid structure and parameters. Input the proposed air environment, temperature rise rate and temperature range into the trained neural network model to obtain the evolution law of thermodynamic performance under the condition.

4. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 3, characterized in that, In step s23, the component phase content at the mesoscale is coupled with the mixing law theory of composite materials to establish a multi-scale thermo-mechanical analysis model for the CFRP laminate, characterizing the thermophysical and mechanical properties of the composite laminate, as follows: In the formula, ρ, c, k i E i and G i These represent the density, specific heat capacity, Young's modulus, and shear modulus of the CFRP monolayer, respectively. Subscript 1 indicates the direction along the fiber bundle, defined as longitudinal; subscript 2 indicates the direction perpendicular to the fiber bundle, defined as transverse; subscripts m, f, and p represent the composite material components epoxy resin, carbon fiber, and pyrolysis residue, respectively; superscript 0 represents the material properties of the corresponding components at room temperature; a is an experimental correction value; and Q... m This represents the thermal decomposition of epoxy resin.

5. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 1, characterized in that, In step s4, considering the interaction of multiple phase states, a multi-mechanism coupled laser ablation analysis model is established to accurately characterize the energy transfer process, as detailed below: s41. For the three-dimensional geometric model in step s1, the differential thermogravimetric method is used to decouple the ablation reaction mechanism, reaction sequence and ablation heat generated during the reaction of CFRP laminate under high temperature conditions; s42. Based on the data results from step s41, analyze the interaction between the laser, the ambient airflow, and the CFRP composite material, and construct an ablation analysis model that includes laser, pyrolysis, oxidation, and phase transformation damage effects; s43. Quantitatively characterize the destruction process of different ablation mechanisms inside the material, and obtain ablation energy, ablation mass, ablation rate and ablation depth.

6. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 5, characterized in that, In step s43, the destruction process of different ablation mechanisms inside the material is quantitatively characterized. The formulas for calculating the oxidation ablation rate and sublimation ablation rate during the destruction process are as follows: In the formula, v o v represents the oxidation rate of carbon fiber. s T represents the sublimation rate of carbon fiber. O A represents the oxidation temperature of carbon fiber. O E represents the pre-oxidation exponent of carbon fiber. O Represents the activation energy of carbon fiber oxidation, R represents the gas constant, and p g p represents the pressure constant term. e E represents the local pressure generated by the flow of pyrolysis gases. S M represents the activation energy for carbon fiber sublimation. C This represents the initial molar mass of a carbon molecule.

7. The efficient simulation method for continuous laser ablation of CFRP laminates as described in claim 1, characterized in that, In step s5, a method combining dynamic birth and death elements with adaptive mesh reconstruction technology is adopted, combined with the energy transfer process in step s4, to achieve high-precision tracking and evolution simulation of the ablation boundary, as detailed below: s51. Apply the laser effect, pyrolysis, oxidation, and phase transformation damage mechanisms from the ablation analysis model in step s42 as thermal loads to the finite element model; s52. Apply the adaptive mesh method to dynamically describe the moving direction and speed of nodes in the ablation region, and set reasonable node movement times and mesh redrawing frequency to dynamically track mesh quality and boundary deformation during the ablation process; s53. The microscopic analysis model of the element characteristic correlation step s2 of the finite element model, each element is a cell composed of fibers and matrix, and the characteristic parameters of the element include mass, volume, temperature and component content; s54. By combining the boundary deformation dynamic tracking in step s52 and the element characteristics in step s53, the instantaneous element ablation depth is obtained; s55. The method of birth and death of cells is used to describe the removal of ablation material. The cell killing is controlled by the cumulative amount of cell ablation depth, so as to achieve high-precision tracking and evolution simulation of ablation boundary.

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