Finite element model optimization calculation method for high-speed dynamic loading of gradient composite material

Abstract

The invention relates to the technical field of finite element simulation calculation, and provides a finite element model optimization calculation method for high-speed dynamic loading of a gradient composite material, which comprises the following steps of: establishing a two-dimensional axisymmetric structure model of a layered gradient configuration; carrying out material characteristic description on the two-dimensional axisymmetric structure model to obtain material parameters, and carrying out segmented description on the impact heat insulation line to obtain a segmented mathematical relationship; correcting the shock wave velocity and the particle velocity based on the shear modulus and the yield strength to obtain a corrected shock wave velocity and a corrected particle velocity; fitting is conducted through the segmented mathematical relationship, the corrected shock wave speed and the corrected particle speed, the corrected segmented mathematical relationship of the corrected shock wave speed and the corrected particle speed is obtained, and based on material parameters and the corrected segmented mathematical relationship, a large amount of sample data is generated through a Latin hypercube sampling method and a center composite design sampling method; evaluating data points of the sample data through a multi-target genetic algorithm to obtain optimized sample data; and performing modeling based on the optimized sample data to obtain an initial optimal finite element model, and performing repeated verification on the initial optimal finite element model to obtain an optimal finite element model. According to the method, automation of the modeling process is achieved, the final particle speed is increased, meanwhile, the calculation time cost is reduced, and the accuracy and calculation efficiency of the model are improved.

Description

Technical Field

[0001] The invention relates to the technical field of finite element simulation calculation, and in particular to a finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials. Background Art

[0002] High-speed dynamic loading of gradient composites often occurs in collision protection research in the aerospace field. For example, high-speed collisions between aircraft skin and high-speed flying objects such as birds, and ultra-high-speed collisions between space debris and satellites. Gradient composites are composed of multiple layers of different materials, each with different physical and mechanical properties, so that the material can absorb energy layer by layer when impacted, reducing the impact on the next layer. In high-speed collisions, such as collisions between aircraft and birds or between space debris and satellites, the material needs to withstand extremely high instantaneous impact forces. Gradient composites effectively disperse and absorb these impact forces through their multi-layer structure.

[0003] The existing finite element calculation model for high-speed dynamic loading of composite materials only considers the influence of the equation of state on the dynamic loading process for the mechanical description of gradient composite materials, and mainly relies on manual finite element modeling strictly according to the experimental configuration. However, for the deformation simulation calculation of gradient composite materials under high-speed dynamic loading, there are problems of repeated and cumbersome modeling, resulting in low modeling accuracy. Summary of the invention

[0004] In view of this, the present invention proposes a finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials, which solves the problem of repeated and cumbersome modeling in the prior art for deformation simulation calculation of gradient composite materials in high-speed dynamic loading.

[0005] The technical solution of the present invention is implemented as follows: The present invention provides a finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials, comprising the following steps:

[0006] S1, establish a two-dimensional axisymmetric structural model of layered gradient configuration;

[0007] S2, describing the material properties of the two-dimensional axisymmetric structure model by using the equation of state and the constitutive model to obtain material parameters of the two-dimensional axisymmetric structure model, wherein the material parameters include shear modulus and yield strength, and describing the impact adiabatic line in sections to obtain a section-wise mathematical relationship between the shock wave velocity and the particle velocity;

[0008] S3, correcting the shock wave velocity and the particle velocity based on the shear modulus and the yield strength to obtain a corrected shock wave velocity and a corrected particle velocity;

[0009] S4, fitting the piecewise mathematical relationship, the modified shock wave velocity and the modified particle velocity to obtain a modified piecewise mathematical relationship between the modified shock wave velocity and the modified particle velocity, generating a large amount of sample data by using a Latin hypercube sampling method and a central composite design sampling method based on the material parameters and the modified piecewise mathematical relationship, evaluating the data points of the sample data by using a multi-objective genetic algorithm to obtain optimized sample data;

[0010] S5, modeling is performed based on the optimized sample data to obtain an initial optimal finite element model, and the initial optimal finite element model is repeatedly verified to obtain a final optimal finite element model.

[0011] Based on the above technical solution, preferably, step S2 includes:

[0012] The calculation formula of the equation of state is:

[0013]

[0014] Where p is the pressure, p k (V) is the cold pressure, γ(V) is the coefficient of the equation of state, V is the specific volume, E is the specific internal energy, and E k (V) is the cold energy, p T is hot pressing, E T For thermal energy.

[0015] On the basis of the above technical solution, preferably, step S2 further includes:

[0016] The calculation formula of the constitutive model is:

[0017]

[0018] Where G is the shear modulus, G0 is the normal pressure shear modulus, G' p is the first derivative of shear modulus with respect to pressure, G' T is the first derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, Y is yield strength, Y0 is yield strength at normal pressure, and Y' p is the first-order derivative of yield strength with respect to pressure, Y' T is the first-order derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

[0019] On the basis of the above technical solution, preferably, step S2 further includes:

[0020] The piecewise mathematical relationship between the shock wave velocity and the particle velocity is:

[0021]

[0022] Where D is the shock wave velocity, u is the particle velocity, x is the critical velocity, and u 0,1 is the initial particle velocity before loading when the particle velocity is less than the critical velocity, C 0,1 is the first linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, λ1 is the second linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, u 0,2 is the initial particle velocity before loading when the particle velocity is not less than the critical velocity, C 0,2 is the first nonlinear fitting constant when the particle velocity is not less than the critical velocity, λ2 is the second nonlinear fitting constant when the particle velocity is not less than the critical velocity, and τ is the parabola quadratic term coefficient when the particle velocity is not less than the critical velocity.

[0023] On the basis of the above technical solution, preferably, step S3 includes:

[0024] The calculation formulas for the modified shock wave velocity and the modified particle velocity are:

[0025]

[0026] Where D' is the modified shock wave velocity, D is the shock wave velocity, G0 is the shear modulus at normal pressure, and G' p is the first derivative of shear modulus with respect to pressure, G' T is the first derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, m is the first correction parameter, a is the second correction parameter, l is the third correction parameter, k is the fourth correction parameter, b is the fifth correction parameter, u' is the corrected particle velocity, u is the particle velocity, x is the critical velocity, Y0 is the yield strength at normal pressure, Y' p is the first-order derivative of yield strength with respect to pressure, Y' T is the first-order derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

[0027] Based on the above technical solution, preferably, step S4 includes:

[0028] S41, designing multiple groups of layered gradient composite material geometric models using the Latin hypercube sampling method and the central composite design sampling method;

[0029] S42, establishing a nonlinear regression response surface model, evaluating all sample points through the multi-objective genetic algorithm, and obtaining optimized sample data.

[0030] Based on the above technical solution, preferably, step S41 includes:

[0031] The material parameters, the modified shock wave velocity and the modified particle velocity are set as design variables, the Latin hypercube sampling method and the central composite design sampling method are used for sampling design, multiple groups of layered gradient composite material geometric models are generated, and batch finite element simulation calculations are performed.

[0032] Based on the above technical solution, preferably, step S42 includes:

[0033] The nonlinear regression response surface model was fitted with data and its accuracy was verified. The peak velocity of the rear interface of the loaded sample was used as the output variable. All sample points were evaluated by a multi-objective genetic algorithm to obtain the optimized sample data.

[0034] Based on the above technical solution, preferably, step S5 includes:

[0035] S51, performing finite element simulation calculation on the optimized sample data, establishing the initial optimal finite element model in combination with boundary condition setting, mechanical description setting and meshing, and carrying out explicit dynamics calculation;

[0036] S52, repeatedly verifying and evaluating the performance of the initial optimal finite element model through final particle velocity and calculation time cost to obtain a final optimal finite element model.

[0037] On the basis of the above technical solution, preferably, step S1 includes:

[0038] S11, design a multi-layered gradient configuration according to the mechanical properties of the material under high-speed dynamic loading conditions, and determine the type, thickness and arrangement order of each layer of material;

[0039] S12, using a two-dimensional axisymmetric structure to simplify the three-dimensional model, wherein the two-dimensional axisymmetric structure model includes a gun body and a multi-layer gradient composite material.

[0040] The finite element model optimization calculation method for high-speed dynamic loading of a gradient composite material of the present invention has the following beneficial effects compared with the prior art:

[0041] (1) By combining the equation of state with the constitutive model to describe the mechanical material properties, and combining the response surface optimization method with the finite element calculation model, the constitutive model and parameter correction are introduced to achieve a comprehensive optimization of the high-speed dynamic loading finite element model of the gradient composite material, so that the comprehensive error of the particle velocity curve in each key area is controlled. The Latin hypercube sampling method is used to design multiple groups of models and evaluate a large number of sample points, realizing the automation of the modeling process. By simplifying the two-dimensional axisymmetric structure, the final particle velocity is increased, while the calculation time cost is reduced, thereby improving the accuracy and calculation efficiency of the model;

[0042] (2) By establishing a piecewise mathematical relationship between shock wave velocity and particle velocity, linear fitting and nonlinear fitting methods are used to handle different working conditions before and after the critical velocity, and multiple physical quantities such as shear modulus, yield strength, pressure, and temperature are combined to perform multi-parameter corrections on shock wave velocity and particle velocity, achieving an accurate description of the velocity variation characteristics of gradient composite materials during high-speed dynamic loading, thereby improving the accuracy of model calculations;

[0043] (3) By introducing a constitutive model based on the equation of state, the material properties of gradient composites under high-speed dynamic loading are described, especially in terms of pressure, specific volume and specific internal energy. The accuracy of material parameters is improved, and the behavioral characteristics of shear modulus and yield strength under pressure and temperature changes are described in detail, thereby enhancing the reliability of the finite element model in simulating high-speed dynamic loading and achieving an accurate description of the mechanical properties of gradient composites under different environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A flow chart of a finite element model optimization calculation method for high-speed dynamic loading of a gradient composite material according to the present invention;

[0046] Figure 2 This is a schematic diagram of the automatic optimization calculation of the gradient composite material dynamic loading process of the present invention;

[0047] Figure 3 It is a comparison curve diagram of simulation calculation results after the constitutive model of the present invention is corrected;

[0048] Figure 4 It is a curve diagram showing the effect of improving simulation accuracy during the high-speed dynamic loading process of the present invention;

[0049] Figure 5 It is a schematic diagram of the dynamic loading simulation model of the multilayer gradient composite material of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] See also Figure 1 The present invention provides a finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials, comprising the following steps:

[0052] S1, establish a two-dimensional axisymmetric structural model of layered gradient configuration;

[0053] S2, describing the material properties of the two-dimensional axisymmetric structure model by using the equation of state and the constitutive model to obtain material parameters of the two-dimensional axisymmetric structure model, wherein the material parameters include shear modulus and yield strength, and describing the impact adiabatic line in sections to obtain a section-wise mathematical relationship between the shock wave velocity and the particle velocity;

[0054] S3, correcting the shock wave velocity and the particle velocity based on the shear modulus and the yield strength to obtain a corrected shock wave velocity and a corrected particle velocity;

[0055] S4, fitting the piecewise mathematical relationship, the modified shock wave velocity and the modified particle velocity to obtain a modified piecewise mathematical relationship between the modified shock wave velocity and the modified particle velocity, generating a large amount of sample data by using a Latin hypercube sampling method and a central composite design sampling method based on the material parameters and the modified piecewise mathematical relationship, evaluating the data points of the sample data by using a multi-objective genetic algorithm to obtain optimized sample data;

[0056] S5, modeling is performed based on the optimized sample data to obtain an initial optimal finite element model, and the initial optimal finite element model is repeatedly verified to obtain a final optimal finite element model.

[0057] For details, please refer to Figure 2, is a schematic diagram of the automatic optimization calculation of the dynamic loading process of the gradient composite material of the present invention. In this embodiment, the configuration of the gradient composite material is preliminarily designed based on the existing high-speed loading layered structure by automatically calculating the high-speed dynamic loading finite element model of the gradient composite material, and the geometric configuration is established by inputting the finite element simulation calculation program. The preliminary establishment of the calculation model is completed by combining the boundary condition setting, advanced mechanical description setting and meshing, and the explicit dynamic calculation is further carried out in the finite element simulation calculation model. After post-processing, the simulation calculation results of the dynamic response behavior of the material can be obtained. For the results of the explicit dynamic simulation calculation, further expanded sample automatic calculation can be carried out, and sampling design and evaluation can be carried out. After optimization by the response surface method, the optimal gradient composite material structure can be optimized by taking the criterion of the maximum final velocity as an example. Finally, the model described by the high-precision and advanced mechanical model is repeatedly verified to ensure the correctness of the automatic optimization.

[0058] This embodiment is aimed at finite element simulation calculation of multilayer gradient composite materials under dynamic deformation loading, selects appropriate mechanical property description control equations, and combines response surface optimization method to perform structural optimization of gradient composite materials, thereby realizing high-precision, automated finite element model establishment and simulation.

[0059] In this embodiment, other types of suitable constitutive models can be selected for different materials, such as the Johnson-Cook model constitutive model, the Zerilli–Armstrong constitutive model, etc. to correct the impact adiabatic line. In addition to the response surface optimization algorithm, simulated annealing algorithm, particle swarm algorithm, etc. can also be used as alternative solutions for automated calculation.

[0060] Step S1 includes:

[0061] S11, design a multi-layered gradient configuration according to the mechanical properties of the material under high-speed dynamic loading conditions, and determine the type, thickness and arrangement order of each layer of material;

[0062] S12, using a two-dimensional axisymmetric structure to simplify the three-dimensional model, wherein the two-dimensional axisymmetric structure model includes a gun body and a multi-layer gradient composite material.

[0063] Specifically, in this embodiment, a typical 20-layer layered gradient configuration in the field of dynamic loading is established, and the finite element simulation model adopts a two-dimensional axisymmetric structure, which can save computing resources while ensuring overall accuracy. The Lagrangian algorithm calculates parameters according to the deformation of the object, and the Euler algorithm extracts the state of the material at a fixed position, which are respectively suitable for the processing of small and large deformations in high-speed dynamic loading. For the light gas gun launcher that produces high-speed dynamic deformation in the laboratory, the deformation of the gun body is small, and the deformation of the multi-layer gradient composite material is large. The simple Lagrangian algorithm and the Euler algorithm are not applicable, so the more advanced Lagrangian-Euler coupling algorithm is used in this embodiment.

[0064] When the Lagrange-Euler coupling algorithm is used to process the stress-strain relationship of the node, the appropriate time step is very important for describing the accuracy of the numerical simulation. If the time step is too large, the accuracy of the numerical simulation will be significantly reduced; if the time step is too small, the consumption of computing resources will increase, resulting in too long computing time. Therefore, a preliminary calculation is required to determine the time step range to ensure the stable operation of the simulation program and guarantee the calculation accuracy. For the model observation point for evaluating the loading effect, it is set at the rear interface of the gradient composite material loaded with the standard target material. The particle velocity profile curve measured here can well reflect the high-speed dynamic loading response characteristics of the gradient composite material.

[0065] Step S2 includes:

[0066] The calculation formula of the equation of state is:

[0067]

[0068] Where p is pressure, p k (V) is the cold pressure, γ(V) is the coefficient of the equation of state, V is the specific volume, E is the specific internal energy, and E k (V) is the cold energy, p T is hot pressing, E T For thermal energy.

[0069] The calculation formula of the constitutive model is:

[0070]

[0071] Where G is the shear modulus, G0 is the normal pressure shear modulus, G' p is the first derivative of shear modulus with respect to pressure, G' T is the first derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, Y is yield strength, Y0 is yield strength at normal pressure, and Y' p is the first-order derivative of yield strength with respect to pressure, Y' Tis the first-order derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

[0072] The piecewise mathematical relationship between the shock wave velocity and the particle velocity is:

[0073]

[0074] Where D is the shock wave velocity, u is the particle velocity, x is the critical velocity, and u 0,1 is the initial particle velocity before loading when the particle velocity is less than the critical velocity, C 0,1 is the first linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, λ1 is the second linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, u 0,2 is the initial particle velocity before loading when the particle velocity is not less than the critical velocity, C 0,2 is the first nonlinear fitting constant when the particle velocity is not less than the critical velocity, λ2 is the second nonlinear fitting constant when the particle velocity is not less than the critical velocity, and τ is the parabola quadratic term coefficient when the particle velocity is not less than the critical velocity.

[0075] Specifically, in this embodiment, since the traditional mechanical model is highly empirical, it is increasingly difficult to meet the increasing simulation calculation needs at this stage, and there are the following two problems.

[0076] First, for materials such as Al, Ni, Zn, Cu, Pt, Pb, Ce, Ta, etc. that are tried in high-speed dynamic loading of gradient composite materials, there is a situation where the material becomes easier to compress or more difficult to compress as the impact pressure increases. At this time, the traditional linear relationship cannot describe the mechanical behavior well. Secondly, when the impact pressure is small and the particle speed is low, the solid has a certain shape. To deform solid materials such as metals, a large external force must be applied, especially when the impact pressure is small. The mechanical description of the system of equations of state only reflects the response of the solid under the action of the hydrostatic load of the fluid. The low-pressure applicability of the "fluid approximation" model of the material has been questioned. Therefore, when the shock wave is very weak, the strength of the solid material in the shock adiabatic line cannot be ignored, and the empirical relationship obtained from the medium and high pressure shock compression experiments may not be extrapolated to the low-pressure shock compression zone. Therefore, in this embodiment, a segmented description is used for the shock adiabatic relationship of the material. When the speed is less than the critical speed, the traditional linear form is still used to describe the Du relationship of the impact adiabatic line; when the speed is greater than the critical speed, the parabolic equation form is used to describe the Du relationship of the impact adiabatic line, which can provide a good mechanical description of the changes in the high-pressure physical properties of the material under the high impact pressure range.

[0077] Step S3 includes:

[0078] The calculation formulas for the modified shock wave velocity and the modified particle velocity are:

[0079]

[0080] Where D' is the modified shock wave velocity, D is the shock wave velocity, G0 is the shear modulus at normal pressure, and G' p is the first derivative of shear modulus with respect to pressure, G' T is the first derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, m is the first correction parameter, a is the second correction parameter, l is the third correction parameter, k is the fourth correction parameter, b is the fifth correction parameter, u' is the corrected particle velocity, u is the particle velocity, x is the critical velocity, Y0 is the yield strength at normal pressure, Y p ' is the first-order derivative of yield strength to pressure, Y T ' is the first derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

[0081] Specifically, in this embodiment, although the low pressure area of ​​the impact loading experiment is in the range of less than 10GPa, it is still far beyond the pressure range under civil working conditions, so the SCG constitutive model as a high pressure constitutive model is still very suitable for the correction of shock wave velocity and particle velocity. The high pressure yield effect of the material in high-speed dynamic loading will significantly change the high-pressure physical properties of the material, and has a great influence on the shock wave velocity and particle velocity during the high-speed dynamic loading of the material, while the shear modulus mainly affects the measurement of the particle velocity profile at the observation point. For the convenience of establishing the mechanical model, the above corrections are mainly made to the shock wave velocity and particle velocity of the material, and the corrected shock wave velocity and corrected particle velocity are obtained. m is the first correction parameter, a is the second correction parameter, l is the third correction parameter, k is the fourth correction parameter, and b is the fifth correction parameter, and its value is mainly determined by the material type and the impact pressure.

[0082] Step S4 includes:

[0083] S41, designing multiple groups of layered gradient composite material geometric models using the Latin hypercube sampling method and the central composite design sampling method;

[0084] The material parameters, the modified shock wave velocity and the modified particle velocity are set as design variables, the Latin hypercube sampling method and the central composite design sampling method are used for sampling design, multiple groups of layered gradient composite material geometric models are generated, and batch finite element simulation calculations are performed.

[0085] S42, establishing a nonlinear regression response surface model, evaluating all sample points by the multi-objective genetic algorithm, and obtaining optimized sample data;

[0086] The nonlinear regression response surface model was fitted with data and its accuracy was verified. The peak velocity of the rear interface of the loaded sample was used as the output variable. All sample points were evaluated by a multi-objective genetic algorithm to obtain the optimized sample data.

[0087] Specifically, this embodiment introduces an automated optimization calculation module and combines it with the dynamic loading model on the basis of the high-speed dynamic loading finite element model simulation calculation. In this embodiment, the ANSYS optimization design module is selected. After the finite element simulation results are imported into the ANSYS optimization design module, the structural characteristic parameters of the multilayer gradient composite material are exported as design variables, and the peak interface velocity after the sample is loaded is used as the output variable. Latin hypercube sampling and central composite design sampling are used to design 780 groups of layered gradient composite material geometric models and perform batch automated finite element calculations. Subsequently, the nonlinear regression response surface model is fitted with data and the accuracy is verified, so that any structural geometric model and the corresponding high-speed dynamic loading model simulation calculation results can be obtained quickly and efficiently. The best result was obtained after evaluating 33,600 sample points through a multi-objective genetic algorithm. Manual modeling was performed for the best optimization result and the result verification was performed with full assurance of the calculation accuracy. The experimental results are as follows: Figure 3-Figure 5 As shown;

[0088] See also Figure 3 , is a comparison of simulation results after the constitutive model is modified under lower and higher speed loading, such as Figure 3 As shown in the figure, no matter it is a low speed or a high speed loading condition, under the high speed dynamic loading condition of gradient composite materials, the simulation calculation results without constitutive model correction are quite different from the published experimental results. The calculation model with SCG constitutive correction has a comprehensive error of less than 5% in the first jump of particle velocity curve, elastic-plastic transition zone, plastic rise zone and two platform velocity zones, but the simulation calculation accuracy of the second particle velocity rise stage still needs to be improved, and this phenomenon will be improved with the increase of loading speed.

[0089] Step S5 includes:

[0090] S51, performing finite element simulation calculation on the optimized sample data, establishing the initial optimal finite element model in combination with boundary condition setting, mechanical description setting and meshing, and carrying out explicit dynamics calculation;

[0091] S52, repeatedly verifying and evaluating the performance of the initial optimal finite element model through final particle velocity and calculation time cost to obtain a final optimal finite element model.

[0092] For details, please refer to Figure 4 , is a curve diagram showing the effect of improving simulation accuracy during high-speed dynamic loading by combining the equation of state with the constitutive model to describe the mechanics of the two-dimensional axisymmetric structure model. Figure 4 As shown in the figure, the results of automated simulation calculations based on high-precision models show that the final particle velocity of the optimized gradient composite material structure under high-speed dynamic loading conditions is increased from 7.54km / s to 7.69km / s. This shows that it is difficult to significantly increase the final particle velocity by only performing collective optimization on the basis of the original structure, but the calculation time cost can be reduced by 52.75%. The response surface optimization method is combined with the finite element calculation model to realize the automated modeling and calculation of the high-speed dynamic loading finite element model, which simplifies the modeling process and improves the calculation efficiency. The results show that this method is correct and effective, and has strong operability. At the same time, the loaded sample structure can be manually designed to directly obtain the launch velocity of the loaded sample from the response surface, which improves the calculation efficiency and saves time cost. It is also important for studying the propagation of shock waves in gradient flyers and realizing the high-speed dynamic response mechanism of gradient composite materials. Please refer to Figure 5 , is a schematic diagram of a dynamic loading simulation model of a gradient composite material of this embodiment.

[0093] 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 spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials, characterized in that: The following steps are involved: S1, establish a two-dimensional axisymmetric structural model of layered gradient configuration; S2, describing the material properties of the two-dimensional axisymmetric structure model by using the equation of state and the constitutive model to obtain material parameters of the two-dimensional axisymmetric structure model, wherein the material parameters include shear modulus and yield strength, and describing the impact adiabatic line in sections to obtain a section-wise mathematical relationship between the shock wave velocity and the particle velocity; S3, correcting the shock wave velocity and the particle velocity based on the shear modulus and the yield strength to obtain a corrected shock wave velocity and a corrected particle velocity; S4, fitting the piecewise mathematical relationship, the modified shock wave velocity and the modified particle velocity to obtain a modified piecewise mathematical relationship between the modified shock wave velocity and the modified particle velocity, generating a large amount of sample data by using a Latin hypercube sampling method and a central composite design sampling method based on the material parameters and the modified piecewise mathematical relationship, evaluating the data points of the sample data by using a multi-objective genetic algorithm to obtain optimized sample data; S5, modeling is performed based on the optimized sample data to obtain an initial optimal finite element model, and the initial optimal finite element model is repeatedly verified to obtain a final optimal finite element model.

2. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 1, characterized in that: Step S2 includes: The calculation formula of the equation of state is: Where p is pressure, p k (V) is the cold pressure, γ(V) is the coefficient of the equation of state, V is the specific volume, E is the specific internal energy, and E k (V) is the cold energy, p T is hot pressing, E T For thermal energy.

3. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 2, characterized in that: Step S2 also includes: The calculation formula of the constitutive model is: Where G is the shear modulus, G0 is the normal pressure shear modulus, G' p is the first derivative of shear modulus with respect to pressure, G' T is the first-order derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, Y is yield strength, Y0 is yield strength at normal pressure, and Y′ p is the first-order derivative of yield strength with respect to pressure, Y′ T is the first-order derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

4. The finite element model optimization calculation method for high-speed dynamic loading of a gradient composite material as claimed in claim 3, characterized in that: Step S2 also includes: The piecewise mathematical relationship between the shock wave velocity and the particle velocity is: Where D is the shock wave velocity, u is the particle velocity, x is the critical velocity, and u 0,1 is the initial particle velocity before loading when the particle velocity is less than the critical velocity, C 0,1 is the first linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, λ1 is the second linear fitting constant of the measured shock wave velocity and particle velocity when the particle velocity is less than the critical velocity, u 0,2 is the initial particle velocity before loading when the particle velocity is not less than the critical velocity, C 0,2 is the first nonlinear fitting constant when the particle velocity is not less than the critical velocity, λ2 is the second nonlinear fitting constant when the particle velocity is not less than the critical velocity, and τ is the parabola quadratic term coefficient when the particle velocity is not less than the critical velocity.

5. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 4, characterized in that: Step S3 includes: The calculation formulas for the modified shock wave velocity and the modified particle velocity are: Where D' is the modified shock wave velocity, D is the shock wave velocity, G0 is the shear modulus at normal pressure, and G' p is the first derivative of shear modulus with respect to pressure, G' T is the first derivative of shear modulus with respect to temperature, p is pressure, η is material compression, T is temperature, m is the first correction parameter, a is the second correction parameter, l is the third correction parameter, k is the fourth correction parameter, b is the fifth correction parameter, u' is the corrected particle velocity, u is the particle velocity, x is the critical velocity, Y0 is the yield strength at normal pressure, Y' p is the first-order derivative of yield strength with respect to pressure, Y′ T is the first-order derivative of yield strength with respect to temperature, β is the first correction parameter of work hardening effect, n is the second correction parameter of work hardening effect, and ε is the third correction parameter of work hardening effect.

6. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 1, characterized in that: Step S4 includes: S41, designing multiple groups of layered gradient composite material geometric models using the Latin hypercube sampling method and the central composite design sampling method; S42, establishing a nonlinear regression response surface model, evaluating all sample points through the multi-objective genetic algorithm, and obtaining optimized sample data.

7. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 6, characterized in that: Step S41 includes: The material parameters, the modified shock wave velocity and the modified particle velocity are set as design variables, the Latin hypercube sampling method and the central composite design sampling method are used for sampling design, multiple groups of layered gradient composite material geometric models are generated, and batch finite element simulation calculations are performed.

8. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 7, characterized in that: Step S42 includes: The nonlinear regression response surface model was fitted with data and its accuracy was verified. The peak velocity of the rear interface of the loaded sample was used as the output variable. All sample points were evaluated by a multi-objective genetic algorithm to obtain the optimized sample data.

9. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 1, characterized in that: Step S5 includes: S51, performing finite element simulation calculation on the optimized sample data, establishing the initial optimal finite element model in combination with boundary condition setting, mechanical description setting and meshing, and carrying out explicit dynamics calculation; S52, repeatedly verifying and evaluating the performance of the initial optimal finite element model through final particle velocity and calculation time cost to obtain a final optimal finite element model.

10. The finite element model optimization calculation method for high-speed dynamic loading of gradient composite materials according to claim 1, characterized in that: Step S1 includes: S11, design a multi-layered gradient configuration according to the mechanical properties of the material under high-speed dynamic loading conditions, and determine the type, thickness and arrangement order of each layer of material; S12, using a two-dimensional axisymmetric structure to simplify the three-dimensional model, wherein the two-dimensional axisymmetric structure model includes a gun body and a multi-layer gradient composite material.

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