Method and apparatus for low velocity impact simulation of laminated panels based on near field dynamics

Abstract

The application discloses a low-speed impact simulation method and device of a laminated plate based on near-field dynamics, and belongs to the technical field of materials. The method comprises the following steps: acquiring a near-field dynamic impact model; controlling an impact object simulation model to perform low-speed impact on a laminated plate simulation model; determining the contact stiffness of each particle in a contact area at a time step according to the material properties and deformation ratio of each particle in the contact area of the impact object simulation model at the time step; determining the contact force of each particle in the contact area at the time step according to the contact stiffness and deformation ratio of each particle in the contact area at the time step; determining the contact force between the impact object simulation model and the laminated plate simulation model at the time step according to the contact force of each particle in the contact area at the time step; and generating a simulation curve of the contact force and time according to the contact force between the impact object simulation model and the laminated plate simulation model at each time step. The application can simplify the low-speed impact simulation of the laminated plate and improve the damage prediction accuracy.

Description

Technical Field

[0001] This application belongs to the field of materials technology, and in particular relates to a method and apparatus for simulating low-speed impacts on laminates based on near-field dynamics. Background Technology

[0002] Composite laminates are widely used in aerospace, automotive, and marine industries due to their excellent mechanical properties, especially their high energy absorption capacity when subjected to low-speed impacts.

[0003] Low-velocity impacts can cause various complex damages within composite laminates, such as matrix cracking, fiber breakage, and interface damage. These damages can severely reduce the strength and stiffness of the structure, and may even lead to structural failure. To optimize design, low-velocity impact simulations can be used to predict the damage evolution of composite laminates.

[0004] However, existing simulation methods typically employ multi-scale modeling, which requires handling a large number of models and complex calculations, resulting in excessive computational costs and time overhead. Furthermore, these methods fail to capture the long-range interactions of composite materials, leading to low accuracy in damage prediction. Summary of the Invention

[0005] This application provides a method and apparatus for simulating low-velocity impacts on laminates based on near-field dynamics, which simplifies the simulation of low-velocity impacts on laminates and improves the accuracy of damage prediction.

[0006] In a first aspect, embodiments of this application provide a method for simulating low-velocity impact on laminates based on near-field dynamics. The method includes: acquiring a near-field dynamics impact model, wherein the near-field dynamics impact model includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using near-field dynamics; controlling the impactor simulation model to perform low-velocity impact on the laminate simulation model; when the impactor simulation model contacts the laminate simulation model in response to the low-velocity impact, for each time step, determining the contact stiffness of each particle in the contact area at each time step based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at each time step; determining the contact force of each particle in the contact area at each time step based on the contact stiffness and deformation ratio at each time step; determining the contact force between the impactor simulation model and the laminate simulation model at each time step based on the contact force between the impactor simulation model and the laminate simulation model at each time step; and generating a simulation curve of the contact force versus time of the laminate corresponding to the low-velocity impact based on the contact force between the impactor simulation model and the laminate simulation model at each time step.

[0007] Secondly, embodiments of this application provide a low-velocity impact simulation device for laminates based on peri-field dynamics. The device includes: an acquisition module for acquiring a peri-field dynamics impact model, wherein the peri-field dynamics impact model includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using peri-field dynamics; an impact module for controlling the impactor simulation model to perform low-velocity impacts on the laminate simulation model; and a determination module for determining, at each time step, when the impactor simulation model responds to the low-velocity impact and contacts the laminate simulation model, based on... The material properties and deformation ratios of each particle in the contact region of the impactor simulation model at each time step are used to determine the contact stiffness of each particle in the contact region at each time step. Based on the contact stiffness and deformation ratio of each particle in the contact region at each time step, the contact force of each particle in the contact region at each time step is determined. Based on the contact force of each particle in the contact region at each time step, the contact force between the impactor simulation model and the laminate simulation model at each time step is determined. The output module is used to generate the simulation curve of contact force versus time for the laminate corresponding to low-velocity impact, based on the contact force of the impactor simulation model and the laminate simulation model at each time step.

[0008] Thirdly, embodiments of this application provide a low-speed impact simulation device for laminates based on peri-field dynamics. The device includes a processor and a memory storing computer program instructions. When the processor executes the computer program instructions, it implements the low-speed impact simulation method for laminates based on peri-field dynamics as described in the first aspect.

[0009] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the low-speed impact simulation method for laminates based on near-field dynamics as described in the first aspect.

[0010] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform the low-speed impact simulation method for laminates based on near-field dynamics as described in the first aspect.

[0011] In this embodiment, the laminate and the impactor are modeled using a particle-level structural characterization method and a near-field dynamics approach, resulting in a near-field dynamics impact model that includes both a laminate simulation model and an impactor simulation model. This particle model constructed using near-field dynamics avoids modeling complexity, simplifying the simulation process, and accurately captures long-range interactions between particles, thereby improving the accuracy of damage prediction.

[0012] Furthermore, in this embodiment, when the impactor simulation model responds to a low-velocity impact and contacts the laminate simulation model, a simulated curve of the contact force versus time corresponding to the low-velocity impact can be generated based on the contact force between the impactor simulation model and the laminate simulation model at each time step, thus demonstrating the low-velocity impact simulation response of the laminate. Specifically, when determining the contact force between the impactor simulation model and the laminate simulation model at each time step, the contact stiffness of each particle at each time step can be determined based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at each time step. In this way, the contact stiffness of the particles can be adaptively adjusted based on the impact energy and material properties, thereby enhancing the stability of the contact force calculation, improving the accuracy of the impact simulation, and increasing the precision of damage prediction. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart illustrating the low-velocity impact simulation method for laminates based on near-field dynamics provided in this application embodiment.

[0015] Figure 2 This is a schematic diagram of a low-velocity impact example of a composite laminate provided in this application embodiment;

[0016] Figure 3 This is a schematic diagram of the near-field dynamic impact model provided in the embodiments of this application;

[0017] Figure 4 This is the contact force-time curve of the verification example provided in the embodiments of this application;

[0018] Figure 5 This is the overall damage evolution cloud map of the verification example provided in the embodiments of this application;

[0019] Figure 6 This is a cloud map of interlaminar shear damage distribution in a verification example provided in this application embodiment;

[0020] Figure 7 This is a schematic diagram of the computing framework provided in an embodiment of this application;

[0021] Figure 8 This is a schematic diagram of the low-speed impact simulation device for laminates based on near-field dynamics provided in the embodiments of this application;

[0022] Figure 9This is a schematic diagram of the low-speed impact simulation device for laminates based on near-field dynamics provided in the embodiments of this application. Detailed Implementation

[0023] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0025] In related technologies, the simulation of low-velocity impact response of composite laminates has the following problems:

[0026] 1. Multi-scale modeling is complex and computationally intensive: Existing multi-scale modeling methods, such as representative volume element (RVE) models and finite element analysis (FEA), often require handling a large number of models and complex calculation processes. In practical applications, especially for the simulation of large laminates, these methods result in excessive computational costs and time consumption.

[0027] 2. Inability to accurately simulate nonlocal interactions between particles: Existing methods mostly use local stress-strain relationships to simulate damage behavior within composite materials. However, long-range nonlocal interactions exist between particles in composite materials, especially under low-velocity impact loading, where inter-particle interactions play a crucial role. Existing methods cannot effectively capture these long-range interactions, leading to reduced damage prediction accuracy.

[0028] 3. Insufficient simulation of interface damage and debonding: The interfaces between fibers and matrix, and between layers in composite laminates, are the key components leading to impact damage. Existing methods have relatively simple simulations of interface damage (such as debonding and slippage), which are difficult to reflect the actual damage process and affect the accuracy of damage evolution.

[0029] 4. Accuracy and efficiency of composite material damage prediction: Although existing simulation methods can predict the damage mode of composite materials, it is still difficult to accurately predict the damage evolution under the complex conditions of low-velocity impact. Moreover, existing methods are often computationally cumbersome and difficult to apply in engineering practice.

[0030] Therefore, how to simplify the model, improve computational efficiency, and accurately simulate the damage behavior of composite materials under low-speed impact while ensuring high accuracy has become an urgent technical problem to be solved.

[0031] Based on this, embodiments of this application provide a low-velocity impact simulation method for laminates based on near-field dynamics, which can simplify the low-velocity impact simulation of laminates and improve the accuracy of damage prediction.

[0032] The low-speed impact simulation method for laminates based on near-field dynamics provided in this application can be applied to electronic devices. Specifically, this method can be executed by the electronic device itself, or by components of the electronic device, such as its processor, chip, or chip system. It can also be implemented by logic modules or software that implement all or part of the functions of the electronic device. In practical applications, the electronic device can be a terminal, server, service platform, cloud, distributed system, Internet of Things (IoT), or vehicle network system. Furthermore, the terminal can be a smartphone, tablet computer, laptop computer, or desktop computer.

[0033] The low-velocity impact simulation method for laminates based on near-field dynamics provided in this application will be described in detail below with reference to the accompanying drawings and through some embodiments and application scenarios.

[0034] See Figure 1 , Figure 1 This is a schematic flowchart of a low-velocity impact simulation method for laminates based on near-field dynamics, provided in an embodiment of this application. Figure 1 As shown, the low-velocity impact simulation method for laminates based on near-field dynamics may include the following steps:

[0035] Step 101: Obtain the near-field dynamic impact model, which includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using near-field dynamics.

[0036] In this embodiment, the laminate and the impactor can be modeled using a particle-level structural characterization method and a near-field dynamics approach. This yields a particle simulation model of the laminate (which can be simply referred to as the laminate simulation model or the near-field dynamics laminate model) and a particle simulation model of the impactor (which can be simply referred to as the impactor simulation model or the near-field dynamics impactor model). A near-field dynamics impact model is then constructed using these two models. This particle model, built using near-field dynamics, avoids modeling complexity, simplifying the simulation process. Furthermore, by applying near-field dynamics and considering the non-local interactions between particles, it accurately captures long-range interactions, thereby improving the accuracy of damage prediction.

[0037] In some embodiments, the laminate can be represented as a composite material laminate. When constructing a laminate simulation model, each particle of the composite material can be defined as a different material composition, such as matrix particles, fiber particles, etc., through particle-level structural characterization, and its spatial distribution can be optimized to realize the reconstruction of real heterogeneous characteristics, so as to improve the fit between the laminate simulation model and the laminate, thereby improving the accuracy of low-speed impact simulation response.

[0038] In the particle model, corresponding bonds can be established between particles to characterize various physical phenomena such as mechanical connections, energy transfer, and structural stability between particles. Thus, damage evolution can be simulated through bond breakage propagation. For example, within the same layup (also called intralayer) of a laminate simulation model, the bond between matrix particles can be called a matrix bond, the bond between fiber particles can be called a fiber bond, and the bond between matrix particles and fiber particles can be called a fiber-matrix interface bond. Between adjacent layups (also called interlayer), if the bond between particles is parallel to the z-axis, it can be called an interlayer normal bond; otherwise, it can be called an interlayer shear bond. In some embodiments, the bonds between particles can further form interfaces. For example, the bonds between fiber particles and matrix particles within each layup can form one type of interface, which can be called an intralayer interface or a first interface; the bonds between particles in adjacent layups can form another type of interface, which can be called an interlayer interface or a second interface.

[0039] For easier understanding, please refer to Figure 2 and Figure 3 ,in, Figure 2 This is a schematic diagram illustrating an example of a low-velocity impact on a composite laminate. Figure 3 This is a schematic diagram of the corresponding near-field dynamic impact model. It should be noted that... Figure 2 and Figure 3For illustrative purposes only, the embodiments of this application do not limit the structure and size of the laminate, nor do they limit the shape and size of the impactor.

[0040] exist Figure 2 In this design, the laminate can be 150mm × 100mm in size, 4mm thick, with each layer being 0.5mm thick, and includes a 125mm × 75mm impact frame opening. The impactor (also called the impactor head) can be a 16mm diameter hemispherical steel impact head. In other embodiments, the impactor can also be conical, flat-headed, spherical, or irregularly shaped, etc. It is understood that different shapes of impactors will induce different stress distributions and damage modes during the impact process. Therefore, in specific applications, the shape of the impactor can be flexibly determined according to the simulation objective. The impactor acts on the central region of the laminate. The boundary conditions of the laminate are rigidly fixed to ensure that the movement of the laminate is restricted during the impact process, resulting only in deformation and damage.

[0041] exist Figure 3 In the simulation model, the laminate includes n layers, namely layer 1, layer 2, ... layer n. The laminate simulation model includes two particle types: matrix particles (…). Figure 3 The middle part is blue particles) and fiber particles ( Figure 3 (The middle part is an orange particle).

[0042] Furthermore, for composite laminates, this application does not limit the type of composite material. In some embodiments, the composite material can be carbon fiber reinforced composite, glass fiber composite, metal matrix composite, or ceramic matrix composite, etc., which can be determined based on actual needs. In other words, this application can be applied to the low-velocity impact simulation of various composite laminates, thus giving it strong versatility and broad application potential. In aerospace, automotive, and shipbuilding fields, this application can provide reliable numerical prediction tools for the design and optimization of composite material structures, helping engineers to more accurately evaluate the low-velocity impact performance of materials and optimize the design of composite laminates.

[0043] Step 102: Control the impactor simulation model to subject the laminate simulation model to low-speed impact.

[0044] After obtaining the near-field dynamic impact model, the laminate simulation model can be subjected to low-speed impact by controlling the impactor simulation model, so as to realize the low-speed impact simulation of the laminate through the near-field dynamic impact model.

[0045] In practice, to enable the impactor simulation model to impact the laminate simulation model at low speed, a low-speed impact load (also known as a low-speed impact load or impact load) can be applied to the impactor simulation model. For example, a concentrated impact or uniform loading method can be used to simulate the low-speed impact load.

[0046] This application does not limit the value of the low-speed impact loading. In some embodiments, the impact energy range of the low-speed impact loading can be 0J to 40J, and the impact velocity can be 0m / s to 6m / s, but it is not limited to these. In one example, such as Figure 2 and Figure 3 As shown, the impact loading can be performed using a displacement control method, with the initial impact velocity set at 6 m / s and the impact process gradually advanced in increments of 0.01 mm.

[0047] Step 103: When the impactor simulation model responds to a low-velocity impact and comes into contact with the laminate simulation model, for each time step, determine the contact stiffness of each particle in the contact area at each time step based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at each time step; determine the contact force of each particle in the contact area at each time step based on the contact stiffness and deformation ratio at each time step; determine the contact force between the impactor simulation model and the laminate simulation model at each time step based on the contact force of each particle in the contact area at each time step.

[0048] After applying a low-speed impact load to the impactor simulation model, the distance between the impactor simulation model and the laminate simulation model can be dynamically detected at each time step to determine whether they are in contact, i.e., the contact state between them can be dynamically acquired.

[0049] If the distance between the two particles is greater than the distance threshold, it can be determined that they are not in contact, and detection can continue. If the distance between the two particles is less than or equal to the distance threshold, it can be determined that they are in contact, as shown in the impact simulation model (low-speed impact laminate simulation model). The distance threshold can be set based on actual needs; in one example, the distance threshold can be 0.9 times the particle spacing, but it is not limited to this.

[0050] During the impact, step 103 can be executed to obtain the contact force between the impactor simulation model and the laminate simulation model at each time step. This simulates the contact behavior between the impacted laminate particles and the impactor particles, ensuring the correct transmission of contact force between particles during the simulation, especially the contact nonlinearity under impact loading. It can be understood that during the impact, the contact force dynamically updates with the displacement of the impactor and gradually decays with the rebound of the impactor.

[0051] In this embodiment, the contact force can be calculated using a power-law nonlinear elastic contact force model. This model can adjust the contact stiffness in real time based on material properties and impact energy (which can be, but is not limited to, characterization through deformation ratio), thereby ensuring that the contact stiffness is consistent with the material properties within the contact area. In other words, the contact stiffness matches the actual local stiffness of the material, enhancing the stability of the contact force calculation and thus improving the accuracy of impact contact simulation. For example, the contact stiffness between two high-modulus regions should be higher than that of the matrix-matrix contact region. Adaptive adjustment of the contact stiffness can make the contact stiffness more realistic. In low-velocity impacts, materials with large stiffness differences (such as carbon fiber vs. epoxy resin) can cause numerical oscillations or even non-convergence under traditional fixed stiffness models. Adaptive adjustment of the contact stiffness can suppress this instability.

[0052] In practice, for each time step, the contact force between the impactor simulation model and the laminate simulation model at that time step can be determined through the following steps:

[0053] Based on the material properties of each particle in the contact area of ​​the impact simulation model and the deformation ratio at the time step, the contact stiffness of each particle in the contact area at the time step is determined.

[0054] Based on the contact stiffness and deformation ratio of each particle in the contact region at each time step, the contact force of each particle in the contact region at each time step is determined.

[0055] Based on the contact force of each particle in the contact area at the time step, the contact force between the impactor simulation model and the laminate simulation model at the time step is determined.

[0056] The contact stiffness of a particle can be expressed as k(x), where x can be understood as a material fit factor, which characterizes the particle's material properties and deformation ratio. The particle's material properties can include, but are not limited to, its material type and elastic modulus. The particle's deformation ratio λ can be calculated using formula (1):

[0057]

[0058] in, The initial particle spacing, The current particle spacing, where a and b represent different particles.

[0059] This application does not limit the method of obtaining contact stiffness based on x. In some embodiments, a model that has learned the correspondence between x and contact stiffness can be pre-trained. In specific implementation, the contact stiffness can be obtained by inputting x into the model. In other embodiments, the correspondence between x and contact stiffness can be pre-obtained, and then the contact stiffness corresponding to x can be obtained through this mapping relationship.

[0060] By using the material adaptation factor x, the contact stiffness of particles in the contact area during the impact process can be adaptively adjusted, which can avoid the errors caused by the fixed contact stiffness in traditional contact models and improve the accuracy of impact simulation.

[0061] After obtaining the contact stiffness, the contact force of the particle can be determined based on the particle's contact stiffness and deformation ratio.

[0062] In some embodiments, determining the contact force of each particle in the contact region at a time step based on the contact stiffness and deformation ratio of each particle in the contact region at a time step includes:

[0063] For each particle in the contact area, the first difference between the particle's deformation ratio at time step q1 raised to the power of q2 raised to the power of q2 is obtained, where q1 and q2 are adjustable power exponents, and q1 and q2 are determined based on the material and shape of the impactor simulation model and the laminate simulation model, and q1 is greater than q2.

[0064] The contact force of the particle at the time step is determined based on the contact stiffness of the particle at the time step and the first difference.

[0065] In these embodiments, the power-law nonlinear elastic contact force model is further expressed as an adjustable power-law nonlinear elastic contact force model. Specifically, when calculating the contact force based on contact stiffness and deformation ratio, the power exponent (also known as the power law) of the deformation ratio is an adjustable power exponent. Of course, it is understood that in other embodiments, a fixed exponent model can also be used to calculate the contact force, specifically, the power exponent of the deformation ratio is fixed and cannot be adjusted.

[0066] In these embodiments, the contact force F contact It can be calculated using formula (2):

[0067]

[0068] in, It is the unit direction vector between particles, defined as:

[0069] The embodiments of this application do not limit the specific values ​​of q1 and q2, which can be adaptively adjusted, but are not limited to, by at least one of the following: the material of the laminate, and the material and shape of the impactor; contact stiffness; impact energy. In some embodiments, q1 and q2 can take the 4-2 power law or the 1-0 power law, that is, q1 is 4 and q2 is 2; or q1 is 1 and q2 is 0. When q1 and q2 take the 1-0 power law, the power-law nonlinear elastic contact force model can degenerate into a power-law linear elastic contact force model.

[0070] In these embodiments, q1 and q2 can be adaptively adjusted according to the impact energy and material properties, which can further enhance the computational stability, make the evolution of contact force in the contact occurrence, slippage and recovery stages conform to the actual material behavior, avoid non-physical oscillation phenomena, and thus improve the accuracy of impact simulation.

[0071] After obtaining the contact forces of each particle in the contact area, the resultant force of the contact forces of each particle in the contact area can be used as the contact force between the impactor simulation model and the laminate simulation model.

[0072] Step 104: Based on the contact force of the impactor simulation model and the laminate simulation model at each time step, generate the simulation curve of the contact force versus time of the laminate corresponding to the low-speed impact.

[0073] After obtaining the contact forces of the impactor simulation model and the laminate simulation model at each time step during the impact process, the corresponding relationship between contact force and time step can be plotted to obtain the simulation curve of contact force versus time for the laminate corresponding to low-speed impact, so as to show the evolution of contact force in the contact occurrence, slippage and recovery stages.

[0074] In one example, the simulated curve of contact force versus time can be found here. Figure 4 . Figure 4 The contact force-time curves shown are compared with experimental data. The results indicate that the error between the simulated peak contact force and the experimental measurement is less than 5%, demonstrating that the embodiments of this application can accurately predict the contact force change trend of the laminate during impact. The curves show that the contact force rises rapidly in the initial stage of impact, reaches its peak, gradually decreases, and eventually approaches zero, which is consistent with experimental results. Comparison of different contact algorithms shows that the contact model of the embodiments of this application can accurately simulate the interaction between the impactor and the laminate, ensuring the reliability of the calculation results.

[0075] This embodiment of the low-velocity impact simulation method for laminates based on peri-field dynamics uses a particle-level structural characterization approach and peri-field dynamics to model the laminate and the impactor, resulting in a peri-field dynamic impact model that includes both a laminate simulation model and an impactor simulation model. By employing a particle model constructed using peri-field dynamics, modeling complexity is avoided, simplifying the simulation process. Furthermore, it accurately captures long-range interactions between particles, thereby improving the accuracy of damage prediction. Additionally, when the impactor simulation model responds to low-velocity impact contact with the laminate simulation model, the contact force versus time curves of the laminate corresponding to the low-velocity impact can be generated based on the contact forces at each time step between the impactor and laminate simulation models, thus demonstrating the low-velocity impact simulation response of the laminate. Specifically, when determining the contact force between the impactor simulation model and the laminate simulation model at each time step, the contact stiffness of each particle at each time step can be determined based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at each time step. In this way, the contact stiffness of the particles can be adaptively adjusted based on the impact energy and material properties, thereby enhancing the stability of the contact force calculation, improving the accuracy of impact simulation, and increasing the precision of damage prediction.

[0076] The near-field dynamic impact model of the embodiments of this application will be described in detail below.

[0077] In some embodiments, obtaining a near-field dynamic impact model includes:

[0078] Establish a three-dimensional spatial model of the laminate;

[0079] The layers of the three-dimensional spatial model are discretized into a particle matrix consisting of multiple rows and columns. Based on the material properties of the laminate, the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix are set to obtain the laminate simulation model.

[0080] In this system, the column direction of the particle matrix corresponding to each layup is the same as the fiber direction of the layup. Each column of particles is divided into a fiber phase particle column or a matrix phase particle column according to the preset fiber content. The fiber phase particle column and the matrix phase particle column are staggered along the row direction of the particle matrix.

[0081] In these embodiments, to establish a laminate simulation model corresponding to the laminate, the geometric structure of the laminate can be defined first, that is, a three-dimensional spatial model of the laminate can be established.

[0082] Subsequently, each layer of the three-dimensional spatial model can be discretized into a particle matrix, resulting in a discretized model of the three-dimensional laminate. Each particle matrix includes multiple particles representing different material compositions, and a near-field dynamic interaction network within and between layers is constructed through inter-particle bond connections.

[0083] Each layup consists of several rows and columns of particles, with the column orientation (i.e., column direction) aligned with the fiber direction. Different columns can be defined as either the fiber phase or the matrix phase according to a specified fiber content (e.g., 60%, with fiber volume fraction error controlled within 3%). A column defined as the fiber phase can be called a fiber phase particle column, containing only fiber particles; a column defined as the matrix phase can be called a matrix phase particle column, containing only matrix particles.

[0084] In the three-dimensional spatial model, the layup orientation (i.e., fiber orientation) of different layers can be defined according to the simulation requirements. In some embodiments, the fiber orientation of each layer can be determined by material design. In one example, the layup orientation of the three-dimensional spatial model can be [0°, 45°, 90°, -45°], but it is not limited to this. In this example, a particle orientation control strategy can be used to precisely control the fiber orientation (0°, 45°, 90°, -45°) to achieve anisotropic response and ensure the actual layup characteristics of the composite laminate.

[0085] The distribution of particles in a single layer of a 3D spatial model can be set based on actual needs, such as a square arrangement or a hexagonal distribution. In practical applications, particles in the same layer can indeed adopt multiple distribution methods, such as a square arrangement or a hexagonal close packing, depending on the target accuracy of the simulation and the actual material structure. A square arrangement is easier to program and post-process, while a hexagonal distribution is closer to the actual fiber-filled structure and can more uniformly simulate isotropic or quasi-anisotropic properties. Particles in different layers can also adopt different distribution methods because the layup direction of each layer is different (such as 0°, ±45°, 90°, etc.), and the corresponding particle arrangement direction should be consistent with the main fiber direction. Therefore, it is possible to define the particle arrangement structure separately according to the layup angle.

[0086] Furthermore, the spatial distribution of particles can be optimized by employing optimization algorithms to adjust the spatial distribution of particles, making the fiber rows and matrix rows as uniformly staggered as possible, thereby reconstructing true heterogeneous features. In some embodiments, the particle size (i.e., particle size) can be spatially optimized based on the fiber diameter (e.g., 7 μm) and the proportion of the matrix region (e.g., 60% volume fraction) to ensure the anisotropy and numerical stability of mechanical properties.

[0087] Then, mechanical property parameters and peri-field dynamic bond parameters can be defined for each material to obtain a laminate simulation model. The mechanical property parameters may include at least one of the following: mass density, elastic modulus, critical fracture strain, etc.; the peri-field dynamic bond parameters may include at least one of the following: critical bond elongation, bond stiffness coefficient, etc.

[0088] Furthermore, the reconstruction of true heterogeneous features can be achieved through differentiated assignment of material properties; that is, the defined mechanical property parameters and near-field dynamic bond parameters can differ for different types of material particles. Furthermore, for the defined particle parameters, parameter verification can be performed using, but is not limited to, the T700 / M21 material data provided by Hongkarnjanakul et al., to ensure the physical accuracy of the computational model.

[0089] Taking T700 / M21 carbon fiber reinforced epoxy resin composite material as an example, the parameters of the material particles can include: density ρ = 1600 kg / m³ 3 Elastic modulus E 11 =130GPa, E 22 =E 33 = 7.7 GPa, where, E 11 Indicates the fiber laying direction, E 22 E represents the direction perpendicular to the fiber within the board. 33 Indicates the thickness direction of the laminate; shear modulus G between the fiber direction and the transverse direction. 12 =G 13 = 4.8 GPa; Poisson's ratio, representing the Poisson effect ν between principal-transverse and transverse sides, respectively. 12 =0.33, ν 23 =0.48; Fiber-direction tensile strength is X 11 =2080MPa, transverse tensile strength X 22 =60MPa, and interlaminar type I fracture toughness (fracture energy absorbed per unit area) G IC =0.5mJ / mm 2 .

[0090] The laminate simulation model obtained by the above method is a heterogeneous composite material particle model. It distinguishes the matrix and fiber materials at the microscopic level, and realizes the reconstruction of real heterogeneous features through material parameter differentiation and spatial optimization distribution. In this way, the modeling accuracy of the laminate can be improved, thereby improving the accuracy of low-speed impact simulation.

[0091] This application does not limit the method for determining the stiffness coefficient of interparticle bonds. In some embodiments, the stiffness coefficients of interparticle bonds can be the same to simplify the determination of bond stiffness coefficients. In other embodiments, a new rule for modeling the transition zone of the laminated interface can be used, employing a progressive bond stiffness attenuation function (also known as a stiffness reduction factor) to simulate the gradient changes in the mechanical properties of intralayer and interlayer interfaces. This avoids the problem of abrupt changes in interface stiffness in traditional discrete models, making the interlayer load transfer more consistent with physical reality.

[0092] The progressive bond stiffness decay function can be used to describe the response behavior and mechanical parameter modulation of different types of particle bonding relationships within a near-field dynamics framework. In some embodiments, different types of bonds between particles, such as... Figure 3 Different colored bonds (purple represents fiber-matrix interface bonds, green represents interlaminar normal bonds, and red represents interlaminar shear bonds) can have their own independent mechanical characteristics, as detailed below.

[0093] In some embodiments, the mechanical property parameters include the elastic modulus of the particle, and the near-field dynamic bond parameters include the stiffness coefficient of the interlayer bond of the particle, wherein the interlayer bond can be the aforementioned interlayer normal bond or interlayer shear bond.

[0094] Based on the material properties of the laminate, the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix can be set, which may include:

[0095] Based on the material properties of the laminate, set the elastic modulus of each particle in the particle matrix;

[0096] For each particle in the particle matrix, the first basic stiffness coefficient of the target interlayer bond is determined based on the elastic modulus of the particle and the elastic modulus of the connecting particles of the target interlayer bond of the particle. The target interlayer bond of the particle can be any interlayer bond of the particle.

[0097] Based on the normal height of the particle in the laminate simulation model, the interlayer bond attenuation factor of the particle is determined, where the interlayer bond attenuation factor is positively correlated with the normal height;

[0098] The product of the first basic stiffness coefficient and the interlayer bond attenuation factor is determined as the actual stiffness coefficient (also known as the final stiffness coefficient) of the target interlayer bond.

[0099] In these embodiments, the stiffness coefficient of the interlayer bond can be obtained, on the one hand, by determining the basic stiffness coefficient of the interlayer bond based on the elastic modulus. On the other hand, to simulate the "layer-by-layer weakening" transition behavior from the complete structural layer to the intermediate interface region, the interlayer bond attenuation factor α(z) can be defined based on the normal height z of the particle (also known as the interlayer center distance: the normal distance between the particle and the center position of the first ply); then... Multiplying by α(z) yields the actual stiffness coefficient c of the interlayer bond. ab ,Right now In this way, the stiffness coefficient of the interlayer bond of the particles can achieve the gradual change characteristics of the interlayer mechanical properties, avoiding the problem of sudden change in interface stiffness in traditional discrete models, and making the interlayer load transfer more in line with physical reality.

[0100] In practical implementation, the basic stiffness coefficient of a single interlayer bond It can be calculated, but is not limited to, using formula (3):

[0101]

[0102] Among them, E mf The equivalent modulus derived from the elastic modulus of the two particles connected by this interlayer bond can be calculated using harmonic averaging; |ξ ab | represents the initial length of the interlayer bond; m is the normalization factor to ensure energy conservation; δ is the near-field range of the particle, representing the maximum radius range within which a particle can interact. Each particle only interacts with other particles within its near-field range. If the relative position between particles is greater than δ, the interaction force is zero.

[0103] The interlayer bond attenuation factor α(z) of a particle is positively correlated with its normal height z; that is, the larger the normal height z, the larger the interlayer bond attenuation factor α(z), and vice versa. It can be understood that the interlayer bond attenuation factor α(z) of particles in different layers of the laminate simulation model is different, meaning the attenuation factor of the interlayer bonds at different second interfaces in the laminate simulation model is different. Therefore, the interlayer bond attenuation factor α(z) can also be called the progressive attenuation factor. The interlayer bond attenuation factor determined in this way can simulate the "layer-by-layer weakening" transition behavior from the complete structural layer to the intermediate interface region, making the interlayer load transfer more consistent with physical reality.

[0104] This application does not limit the method of determining α(z). In some embodiments, the interlayer bond attenuation factor of the particle is determined based on the normal height of the particle in the laminate simulation model, including:

[0105] The ratio of the second difference to the ply thickness (Δz, i.e. the thickness of one ply of the laminate, also known as the transition zone thickness) of the laminate simulation model is determined as the weighting coefficient of the interlaminar bond stiffness reduction factor of the particle. The second difference is the difference between the normal height z and the normal coordinate value of the center position (z0, also known as the interface center position) of the first ply of the laminate simulation model.

[0106] Obtain the maximum stiffness reduction factor (α) of the interlaminar bonds in the laminate simulation model. max That is, the reduction factor of the strongest interlayer bond (e.g., 0.2) and the reduction factor of the minimum stiffness of the interlayer bond (α). min That is, the reduction factor of the weakest interlayer bond (e.g., 0.8);

[0107] The difference between the maximum stiffness reduction factor of the interlayer bond and the minimum stiffness reduction factor of the interlayer bond is determined as the basic adjustment step size of the interlayer bond stiffness reduction factor in the laminate simulation model.

[0108] The product of the weighting coefficient and the basic adjustment step size is determined as the actual adjustment step size of the interlayer bond stiffness reduction coefficient of the particle.

[0109] The sum of the minimum stiffness reduction factor of the interlayer bond and the actual adjustment step size is determined as the interlayer bond attenuation factor of the particle.

[0110] In these embodiments, the interlayer bond attenuation factor of the particles can be calculated using formula (4):

[0111]

[0112] Through the above embodiments, the interlayer bond attenuation factor of the particles can be adaptively adjusted based on the normal height of the particles. In this way, the "layer-by-layer weakening" transition behavior from the complete structural layer to the intermediate interface region can be simulated, making the interlayer load transfer more in line with physical reality.

[0113] In some embodiments, the mechanical property parameters include the elastic modulus of the particle, and the near-field dynamic bond parameters include the stiffness coefficient of the interfacial bond of the particle, wherein the interfacial bond can be the aforementioned fiber-matrix interfacial bond.

[0114] Based on the material properties of the laminate, the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix are set, including:

[0115] Based on the material properties of the laminate, set the elastic modulus of each particle in the particle matrix;

[0116] For each particle in the particle matrix, the second basic stiffness coefficient of the target interface bond is determined based on the elastic modulus of the particle and the elastic modulus of the connected particles of the target interface bond of the particle. The target interface bond of the particle can be any interface bond of the particle.

[0117] Obtain the interface adjustment coefficient of the interface where the particle is located;

[0118] The product of the second basic stiffness coefficient and the interface adjustment coefficient is determined as the actual stiffness coefficient of the target interface key.

[0119] In these embodiments, the stiffness coefficient of the interface bond can be obtained in two ways: firstly, the basic stiffness coefficient of the interface bond can be determined based on the elastic moduli of the two particles connected by the interface bond; secondly, the interface adjustment coefficient γ of the interface where the particles are located can be obtained. The product of these two values ​​can then be used to determine the actual stiffness coefficient c of the interface bond. fb .

[0120] In practice, the actual stiffness coefficient of the interface key can be calculated using, but is not limited to, formula (5):

[0121]

[0122] Among them, E m E represents the elastic modulus of matrix particles bonded by interface bonds. f This represents the elastic modulus of the fiber particles connected by interface bonds.

[0123] The interface adjustment coefficient of each interface can be determined based on the material properties of the particles at that interface. It is understood that the interface adjustment coefficients of different interfaces may be the same or different.

[0124] The actual stiffness coefficient of the interface key determined by the above embodiments can simulate the gradient change of the mechanical properties of the interface within the layer, which can avoid the problem of sudden change in interface stiffness in traditional discrete models, making the interlayer load transfer more in line with physical reality, thereby improving the accuracy of low-speed impact simulation.

[0125] In the embodiments of this application, in addition to simulating the contact force between the laminate and the impactor through a near-field dynamic impact model, the damage evolution of the laminate can also be simulated through a near-field dynamic impact model, as detailed below.

[0126] In some embodiments, after determining the contact force between the impactor simulation model and the laminate simulation model at a time step, the method may further include:

[0127] For each particle in the laminate simulation model, the displacement of the particle in the time step is determined by the peri-field dynamics equation based on the external force acting on the particle in the time step; where the external force includes the contact force between the impactor simulation model and the laminate simulation model in the time step.

[0128] Based on the particle's displacement at the time step, the damage factor of each bond of the particle at the time step is determined, where the damage factor of each bond characterizes whether the bond is damaged.

[0129] The total number of damaged bonds in a particle at a time step is determined based on the damage factor of each bond at the time step.

[0130] The ratio of the total number of damaged bonds to the total number of bonds in the particle is determined as the first damage variable of the particle at the time step, where the first damage variable of each particle characterizes the degree of damage to the particle.

[0131] Based on the first damage variable of each particle at each time step in the laminate simulation model, a damage distribution simulation diagram of the laminate corresponding to low-velocity impact is generated.

[0132] In these embodiments, the laminate simulation model can be iterated based on near-field dynamics (PD) theory to solve for the particle displacement at each time step.

[0133] In practice, the particle's acceleration can be calculated first based on the integral form of the near-field dynamics equations, and then the particle's displacement can be calculated based on the particle's acceleration.

[0134] The peri-field dynamics equation of particle a can be expressed as formula (6):

[0135]

[0136] Where, ρ a It is the density of particle a; It is the acceleration of particle a; Within the near-field range of particle a; f(ξ) ab ,η ab V is the bonding force density between particle a and particle b; b Let b be the volume of any particle within the near-field range of particle a; a The external force acting on particle a includes at least the contact force.

[0137] Formula (6) describes the motion of particle a and takes into account the interaction forces between it and its neighboring particles and external loads. This improves the accuracy of particle displacement calculation and thus improves the accuracy of damage evolution.

[0138] In PD calculations, each particle interacts only with other particles within its near-field range (horizon), when |ξ ab When |>δ, the interaction force is zero. This application proposes an adaptive bond strength allocation strategy based on heterogeneous composite materials, namely the aforementioned new rule for modeling the transition zone of the laminated interface. It employs a progressive bond stiffness decay function to simulate the gradient changes in the mechanical properties of the intralayer and interlayer interfaces, overcoming the limitations of the PD model for homogeneous materials. Specifically: the mechanical parameters of the fibers and matrix particles are different, and the bonding force density f(ξ) ab ,η ab It can be controlled by material properties and can be characterized by formula (7):

[0139]

[0140] Where c is the proportionality coefficient, i.e., the aforementioned bond stiffness coefficient, such as the actual stiffness coefficient of interlayer bonds and the actual stiffness coefficient of interface bonds; ξ ab =x b -x a η represents the relative position between particle a and particle b; ab =u b -u a It is the displacement vector in the deformable configuration, where u a and u b d(ξ) represents the displacements of particles a and b, respectively; ab ,η ab The value ) indicates whether the bond is damaged, taking the form of 0 or 1, where 1 represents a broken bond and 0 represents an unbroken bond; a unit vector is defined. y ab =ξ ab +η ab ,y ab =|y ab |=λ ab |ξ ab Here, λ ab The deformation coefficient (elongation) determines the magnitude of elastic deformation between particles.

[0141] In this way, each particle in the model interacts with other particles through the bonding force density, and can accurately capture the mechanical behavior of composite materials under complex loading conditions such as low-speed impact and crack propagation.

[0142] Through the above formulas (6) and (7), the near-field dynamics model can effectively describe the nonlocal interactions and damage propagation of composite materials, and thus predict the stress response and intralaminar and interlaminar damage modes of composite laminates, including fiber fracture, matrix cracking, interface debonding, and delamination. In specific implementation, after calculating the displacement of the particle at a certain time step, the damage factor d of each bond of the particle at that time step can be determined based on this displacement.

[0143] The determination of the corresponding damage factor d and the damage mode characterized can differ for different types of bonds, as detailed below:

[0144] For fibrous bonds, the corresponding damage factor d can be determined by comparing the elongation of the fibrous bond calculated based on particle displacement with the critical elongation. The damage mode characterized by the damage factor d is fiber fracture. The criterion for judging fiber fracture can be: s f >s f,c ; where s f It is the elongation of the fiber bond, s f,c It is the critical elongation of the fiber bond. When the elongation of the fiber bond exceeds its critical elongation, the fiber breaks and the corresponding d is 1; otherwise, the corresponding d is 0.

[0145] For matrix bonds, the corresponding damage factor d can be determined by comparing the matrix bond elongation calculated based on particle displacement with the critical elongation. The damage mode characterized by the damage factor d is matrix cracking. The criterion for judging matrix cracking can be: s m >s m,c ; where s m It is the elongation of the matrix bond, s m,c It is the critical elongation of the matrix bond. When the elongation of the matrix bond exceeds its critical elongation, the matrix cracks, and the corresponding d is 1; otherwise, the corresponding d is 0.

[0146] For interfacial bonds within intralayer interfaces and interfacial bonds between interlayer interfaces, the corresponding damage factor d can be determined by comparing the relative displacement calculated from particle displacement with the critical displacement. The damage mode characterized by the corresponding damage factor d is interfacial debonding. The criterion for judging interfacial debonding can be: s ab >δc. Where, s ab δc is the relative displacement of the particles connecting the bond, and δc is the critical debonding displacement. That is, when the relative displacement of the particles connecting a certain bond exceeds the critical debonding displacement, it indicates that the interface where the bond is located has undergone interfacial debonding. It can be understood that if the bond is an interfacial bond, the interface where the bond is located is an intralayer interface or the first interface; if the bond is an interlayer bond, the interface where the bond is located is an interlayer interface or the second interface.

[0147] The above critical elongation s f,c s m,c (can be collectively referred to as s) c The critical debonding displacement can be determined based on actual needs. In some embodiments, the critical elongation can be calculated based on the fracture toughness (GIC) of different material components, such as by formula (9):

[0148]

[0149] Where ν represents Poisson's ratio; δ represents the near-field range of a particle, which is the maximum radius range within which a particle can interact.

[0150] After obtaining the damage factors of each bond in the particle, the total number of damaged bonds can be determined based on these damage factors, thus determining the particle's first damage variable. The particle's first damage variable can characterize the degree of damage to the particle and reflect the overall destructive extent of the particle.

[0151] In practice, for each particle, the number of bonds with a value of 1 in the damage factor d of each bond can be counted to obtain the total number of damaged bonds (Nd) of the particle. Then, the ratio of the total number of damaged bonds of the particle to the total number of bonds (Nt) of the particle can be determined as the first damage variable D of the particle, that is, D = Nd / Nt.

[0152] It is understandable that the particle's initial damage variable D is continuously updated with each time step. By progressively calculating the damage variable, the evolution of the crack can be dynamically tracked, and the final failure mode of the composite material can be predicted. Subsequently, based on the particle's initial damage variable D at each time step, a damage distribution simulation map of the laminate corresponding to low-velocity impact can be generated.

[0153] Furthermore, for different types of bonds in particles, such as interlayer normal bonds and interlayer shear bonds, the damage variables for each type of bond can be calculated separately to determine the damage evolution of different bonds and generate corresponding damage distribution simulation maps. The damage variable for a certain type of bond in a particle can be obtained based on the ratio of the number of damaged bonds of that type to the total number of bonds of that type in the particle.

[0154] For easier understanding, please refer to Figure 5 and Figure 6 ,in, Figure 5 The overall damage evolution cloud map of the laminate simulation model is generated based on the total damage variable of particles; Figure 6 To verify the interlaminar shear damage distribution cloud map of the instance, damage variables based on interlaminar shear bonds of particles are generated.

[0155] like Figure 5 As shown, the cracks mainly propagate outwards from the impact point, and the damaged area closely matches the damage morphology observed in experiments. Near the impact point, the matrix cracks, fiber fractures are concentrated in the bottom region of the laminate, and interfacial debonding mainly occurs at the interlaminar interfaces of the laminate. These damage modes conform to the actual failure mechanism of composite materials, indicating that the embodiments of this application can accurately predict the damage evolution process of composite laminates under low-velocity impact.

[0156] Figure 6 The distribution of interlaminar shear damage is shown, which can accurately capture the coupling effect between interlaminar debonding and fiber fracture. In the initial stage of impact, the damage is mainly limited to the area around the impact point. As the impact energy is released, the damage gradually propagates along the interior of the laminate. The initial stage of interlaminar shear damage is mainly concentrated at the interlaminar interface. As the impact force increases, the interface damage gradually propagates to the matrix and fiber layers, eventually forming a crack network that penetrates the interlaminar layers. Figure 6 This study demonstrates the entire process of interlaminar damage expanding from initial micro-fractures to large-scale damage, highlighting the evolutionary characteristics of interlaminar coupled damage. Calculation results show that the propagation velocity of translaminar damage is closely related to the propagation rate of stress waves, and the development trend of interlaminar shear damage is consistent with experimental observations. The numerical simulation using the embodiments of this application can accurately predict the coupling behavior of interface debonding, fiber fracture, and shear damage, providing a new approach for damage analysis of composite materials.

[0157] In the above embodiments, the particle displacement is updated based on the near-field dynamics equations, which in turn updates the particle's damage variables. Then, the evolution of the crack is dynamically tracked based on the particle's damage variables at each time step. This can accurately predict the damage evolution of composite laminates under low-speed impact and improve the accuracy of low-speed impact simulation.

[0158] In traditional methods, damage between different layers is often modeled in isolation, making it difficult to capture damage coupling and propagation phenomena. Therefore, this application further introduces a cross-layer damage propagation rule (also known as a cross-layer coupling mechanism or cross-layer mechanism). This rule is based on the physical mechanism of interlayer bond damage weakening the mechanical properties of adjacent layers (which may, but is not limited to, weakening the stiffness coefficient of interlayer bonds), allowing interlayer damage to propagate between different layers and optimizing the problem of damage isolation in traditional methods. Specifically, this can be achieved by defining a second damage variable D. interface The degree of damage at the interface particles is quantified and used as the criterion for triggering cross-layer mechanisms. In some embodiments, the second damage variable may also be referred to as the interface damage variable.

[0159] In some embodiments, the near-field dynamics equations of motion include the interparticle bonding force density, and the interparticle bonding force density is determined based on the stiffness coefficient of the interparticle bonds.

[0160] After determining the damage factors of each bond in a particle at a time step based on the particle's displacement at that time step, the method further includes:

[0161] The number of damaged interlayer bonds in a particle at a time step is determined based on the damage factor of the interlayer bonds at the time step.

[0162] The ratio of the number of damaged interlayer bonds to the total number of interlayer bonds in the particle is determined as the second damage variable of the particle at the time step. The second damage variable of each particle is used to characterize the degree of breakage of the interlayer bonds of the particle.

[0163] When the second damage variable of a particle is greater than the damage threshold, the stiffness coefficient corresponding to the bonding force density of the interlayer bonds of the particle is multiplied by the stiffness reduction factor, where the stiffness reduction factor is less than 1.

[0164] In practical implementation, after obtaining the damage factors of each bond in the particle, for each particle, the number of bonds with a value of 1 in the damage factor d of the interlayer bonds can be counted to obtain the number of damaged interlayer bonds of that particle. Then, the ratio of the number of damaged interlayer bonds of that particle to the total number of interlayer bonds of that particle can be determined as the second damage variable D of that particle. interface .

[0165] A damage threshold, such as 0.7, is preset. This threshold can be used to determine whether the interlayer bonds of the particles have undergone severe debonding or even complete breakage. Specifically, if the particle's second damage variable D... interfaceA value ≥ the damage threshold indicates that the interlayer bonds of the particle are damaged, which can trigger the cross-layer damage propagation rule, weaken the stiffness coefficient of the interlayer bonds of the particle, and reduce the constraint ability between the upper and lower layers. This stiffness reduction will make the adjacent layers more prone to fiber fracture or matrix cracking under external load, thereby realizing the natural propagation of interlayer damage.

[0166] In practical implementation, if the second damage variable D of a certain particle interface If the damage threshold is greater than or equal to a certain threshold, when determining the particle's displacement using the peridynamic equations, a stiffness reduction operation can be performed on the stiffness coefficient of the interparticle bonding force density in those equations. Specifically, this can be achieved by multiplying the stiffness coefficient corresponding to the interlayer bond bonding force density of the particle by a stiffness reduction factor (also known as a scaling factor), where the stiffness reduction factor is less than 1. Furthermore, the stiffness reduction factor can be different for different types of interlayer bonds.

[0167] For ease of understanding, the following example is provided:

[0168] When the second damage variable D of a certain particle interface A value ≥0.7 indicates that the interlayer bonds of the particle have undergone severe debonding or even complete breakage. At this point, the corresponding particle pairs in the adjacent layers above and below the particle can be automatically identified, and cross-layer coupling bonds can be established along the normal direction of the laminate (e.g., ...). Figure 3 The diagram shows "interlayer normal keys" and "interlayer shear keys," and a "stiffness reduction" treatment is applied to these interlayer keys (i.e., the aforementioned interlayer keys). Specifically, the normal and tangential stiffness coefficients of the interlayer keys are updated by scaling factors γn and γs, respectively (e.g., γn = 0.5, γs = 0.3), explicitly reducing the constraint capacity between upper and lower layers.

[0169] In these embodiments, introducing cross-layer damage propagation rules during the near-field dynamics calculation can simulate the mechanical effect of interface debonding on local regions of the upper / lower layers, allowing damage to gradually propagate to adjacent layers and form realistic cross-layer through cracks. Furthermore, using cross-layer damage propagation rules to control the damage propagation path (which can be viewed as an energy dissipation-driven damage evolution strategy) ensures that crack propagation follows a path of minimum energy release, improving computational physics consistency.

[0170] In some embodiments, the external force acting on the particle may also include the frictional force between the impactor simulation model and the laminate simulation model at the time step.

[0171] Based on the external forces acting on the particle at a time step, and using the peri-field dynamics equations, the displacement of the particle at the time step is determined. The method also includes:

[0172] Obtain the relative sliding velocity of the impactor simulation model and the laminate simulation model at the time step;

[0173] Determine the friction coefficient adjustment factor for the time step based on the relative sliding speed;

[0174] The actual friction coefficient at the time step is determined based on the initial static friction coefficient and the friction coefficient adjustment factor.

[0175] Based on the actual friction coefficient and the normal contact force between the impactor simulation model and the laminate simulation model at the time step, the friction force between the impactor simulation model and the laminate simulation model at the time step is determined.

[0176] In these embodiments, a velocity-dependent friction correction model is introduced, which can adjust the friction coefficient in real time based on the impact velocity to more realistically describe the sliding behavior of the interface during impact contact.

[0177] In practice, the friction coefficient adjustment factor can be determined based on the relative sliding speed between the impactor simulation model and the laminate simulation model. Then, the initial static friction coefficient can be adjusted based on this friction coefficient adjustment factor to obtain the actual friction coefficient.

[0178] In some implementations, the actual friction coefficient μ can be calculated using formula (10):

[0179] μ=μ0+β·v_slide (10)

[0180] Where μ0 is the initial static friction coefficient; v_slide is the relative sliding velocity between the impact simulation model and the laminate simulation model, which can be calculated based on the contact force; β is the velocity sensitivity coefficient, used to adjust the evolution of friction force with velocity; β·v_slide represents the friction coefficient adjustment factor.

[0181] In formula (10), the friction coefficient adjustment factor is expressed as β·v_slide, but this does not limit the way the friction coefficient adjustment factor is determined. Any method that can determine the friction coefficient adjustment factor based on the relative sliding speed can fall within the protection scope of the embodiments of this application. The actual friction coefficient μ is expressed as the sum of μ0 and the friction coefficient adjustment factor. In other implementations, it can also be expressed as the product of the two. The specific setting can be determined according to actual needs.

[0182] The normal contact force between the impactor simulation model and the laminate simulation model at the time step can be understood as the normal component of the contact force between the impactor simulation model and the laminate simulation model at the time step. Friction force can be calculated using formula (11):

[0183] F friction =μ·F normal (11)

[0184] In these embodiments, the friction coefficient μ can be updated in real time according to the change in impact velocity, making the sliding friction force more consistent with the experimental measurement data, thereby improving the accuracy of impact simulation.

[0185] It is understood that in other embodiments, the coefficient of friction μ may also be set to a fixed value.

[0186] It should be noted that the various embodiments described in this application can be combined with each other or implemented individually without conflict, and this application does not limit this.

[0187] This application discloses a method for simulating the low-speed impact response of composite laminates based on a heterogeneous composite material model and a near-field dynamics method. By constructing a particle-scale heterogeneous composite structure model, particles composed of different materials (such as fibers and matrix) are accurately characterized, and the nonlocal near-field dynamics (PD) method is combined to simulate the damage evolution, crack propagation, and mechanical response of the material. This application proposes a modeling rule for the interface transition zone and uses a progressive stiffness decay function to simulate the gradient change of interlaminar mechanical properties, achieving an accurate description of interlaminar debonding, shear damage, and cross-layer damage transmission. Simultaneously, a power-law nonlinear elastic contact force model is developed, combined with a dynamic friction coefficient update mechanism, to improve the accuracy of impact contact simulation. This application overcomes the limitations of traditional local mechanical models, accurately predicting the complex evolution process of fiber fracture, matrix cracking, and interface damage, and significantly improving the accuracy and computational efficiency of damage simulation. This application is applicable to the design of composite material structures in aerospace, automotive, and shipbuilding fields, providing a reliable numerical analysis tool for optimizing the impact resistance of engineering structures.

[0188] The embodiments of this application may include the following aspects:

[0189] 1. A heterogeneous composite material model is employed: This application utilizes a particle-scale fiber / matrix / interface composite structure characterization method to define each particle of the composite material as a different material composition (e.g., matrix particles, reinforcing fiber particles, etc.), and optimizes their spatial distribution to achieve a realistic reconstruction of heterogeneous characteristics. This is achieved through differentiated assignment of material parameters (e.g., the elastic modulus E of fiber particles). 11 =130GPa, matrix particle E 22 =7.7 GPa) to reconstruct realistic heterogeneous features; a modeling rule for the transition zone of the layered interface is proposed, and an asymptotic bond stiffness attenuation function (such as the interface stiffness reduction coefficient α = 0.2-0.8) is used to simulate the gradient change of mechanical properties at the interlayer interface. This method avoids the complexity of multi-scale modeling and simplifies the simulation process.

[0190] 2. Application of Peri-Field Dynamics Model: This application employs a peri-field dynamics method, overcoming the limitations of traditional local mechanical models. It describes the force transmission and damage evolution within the material through non-local mechanical relationships. Unlike the traditional finite element method, the peri-field dynamics method does not rely on local stress concentration points but simulates the overall response of the material through integral mechanical equilibrium equations. The peri-field dynamics model can more accurately capture long-range interactions between particles, simulating the interaction forces between material particles under low-speed impact loading, effectively improving the accuracy of damage prediction.

[0191] 3. Simulation of Interface Damage and Description of Debonding Behavior: This application's embodiments accurately simulate the debonding behavior of the fiber-matrix interface and interlayer interfaces in composite laminates using an interface damage model. Interface debonding is determined by relative displacement; when the relative displacement of the interface exceeds a critical displacement, debonding occurs, simulating the interaction between the fiber-matrix and different layers. This application's embodiments can accurately predict the occurrence and evolution of interface damage.

[0192] 4. Simplified Model and Efficient Computation: Unlike traditional multi-scale methods, the method in this embodiment simplifies the complex composition of composite materials to the particle level using a heterogeneous composite material model, reducing the number of computational units and lowering computational costs. Combined with a variable-step long-time integration strategy, the time step adjustment is optimized, improving computational accuracy and stability. Through the near-field dynamics method, large-scale mesh generation and complex local stress calculations are no longer required, significantly improving computational efficiency and speed.

[0193] 5. Low-velocity impact load simulation and damage prediction: Low-velocity impact loads can be simulated using concentrated impact or uniform loading methods, with impact energy ranging from 0J to 40J and impact velocities from 0m / s to 6m / s. By simulating interparticle interactions and damage evolution, the stress response and intralaminar and interlaminar damage modes of composite laminates can be predicted, including fiber fracture, matrix cracking, interfacial debonding, and delamination.

[0194] 6. Advanced contact model and dynamic friction correction: A power-law nonlinear elastic contact force model is proposed and a dynamic friction update mechanism is introduced. The friction coefficient changes according to the impact velocity to ensure the consistency between calculation and physics.

[0195] 7. Numerical Solution and Verification: The model can be solved using a dedicated near-field dynamics solver, and the Newton-Raphson iteration method is employed to improve solution stability. The output includes contact force-time curves, intra-layer damage distribution, and inter-layer shear damage distribution maps. The accuracy and effectiveness of the proposed method are verified by comparing the results with experimental data.

[0196] Compared with related technologies, it has the following advantages:

[0197] 1. Simplify the calculation process and reduce calculation costs.

[0198] Traditional multi-scale modeling methods (such as the Representative Volume Element (RVE) model) typically require fine meshing of the composite material's hierarchical structure and complex interlayer coupling calculations, resulting in high computational costs and low efficiency. This application innovatively employs a heterogeneous composite material particle model, decomposing the composite material into particles of different material compositions and constructing laminates using these particles, thus avoiding the complexity of multi-scale modeling. Simultaneously, based on the peri-field dynamics (PD) method, this application effectively overcomes the local stress concentration problem in traditional finite element methods. Through integral-form nonlocal interaction calculations, it significantly reduces the number of computational elements and computational complexity, thereby achieving a more efficient and stable computational framework, particularly suitable for the rapid simulation of large-scale laminates.

[0199] 2. Accurately simulate nonlocal interactions and long-range mechanical effects.

[0200] Under low-velocity impact conditions, the damage behavior of composite materials often involves long-range interactions and nonlocal mechanical effects between particles within the material. Traditional local mechanical methods (such as the finite element method) often fail to effectively capture these complex interactions, leading to inaccurate damage predictions. In contrast, the embodiments of this application utilize a peri-field dynamics model to naturally simulate nonlocal interactions between particles and crack propagation, ensuring accurate prediction of damage evolution. The peri-field dynamics method is based on mechanical equilibrium equations and describes interaction forces through integration, thereby avoiding stress concentration and singularity problems found in traditional methods. Especially in complex composite materials, this method can better simulate crack propagation and damage propagation paths, providing more accurate damage analysis results.

[0201] 3. Accurately simulates interface damage and debonding behavior.

[0202] Interfacial damage in composite materials (such as debonding and slippage between fibers and the matrix) is a key factor in damage occurrence under low-velocity impact. Existing simulation methods often fall short in simulating interfacial damage, failing to fully consider the slippage and debonding effects at the interface. This application addresses this issue by defining an interfacial damage criterion (a failure criterion based on critical stress and critical energy release rate, describing particle fracture, matrix cracking, and interfacial debonding behavior, respectively) and using relative displacement to determine interfacial debonding, thus accurately simulating the occurrence and evolution of interfacial damage. Through the description of nonlocal interactions, this method can effectively simulate the debonding process between fibers and the matrix, and between layers, while considering slippage behavior at material interfaces, thereby obtaining a more realistic damage mode when simulating the low-velocity impact response of composite laminates. Furthermore, this application can effectively simulate the evolution mechanism of interlaminar shear damage, particularly how interfacial debonding damage triggers intralaminar damage, achieving cross-layer damage coupling analysis. This is crucial for accurately predicting the damage mode of composite laminates and optimizing structural design.

[0203] 4. Improve the accuracy of damage prediction.

[0204] Traditional damage prediction methods mostly rely on finite element mesh generation for local stress calculation, which is difficult to accurately reflect the damage evolution process of complex heterogeneous materials, especially in the simulation of interface damage and crack propagation. This application's embodiment uses a nonlocal near-field dynamic damage evolution method to accurately capture the entire process of crack propagation, interface debonding, and fiber fracture, and achieves precise evolution of damage modes under impact loading. The numerical simulation results are highly consistent with experimental data; under low-velocity impact conditions, the damage morphology and crack propagation path have an error of less than 5% compared to experimental observations, demonstrating the high accuracy and feasibility of this application's embodiment.

[0205] 5. Widely applicable to the design and evaluation of various composite laminates.

[0206] The methods described in this application can be used not only for traditional composite materials (such as carbon fiber reinforced composites and glass fiber composites), but also for simulating other complex composite materials, such as metal matrix composites and ceramic matrix composites. This gives the embodiments of this application strong versatility and broad application potential. In aerospace, automotive, and marine fields, the technical solutions of the embodiments of this application can provide reliable numerical prediction tools for the design and optimization of composite material structures, helping engineers to more accurately evaluate the low-velocity impact performance of materials and optimize the design of composite laminates.

[0207] For ease of understanding, a specific embodiment will be used as an example:

[0208] This specific embodiment may include the following steps:

[0209] Step 1, Preprocessing: This application's embodiments pioneer a microscopic modeling strategy for particle-level composite materials, employing a heterogeneous composite particle model to distinguish the matrix, fibers, and interface materials at the microscopic level. Through differentiated assignment of material parameters and spatial optimization distribution, realistic reconstruction of heterogeneous characteristics is achieved. Furthermore, a new rule for modeling the transition zone of laminated interfaces is proposed, using a progressive bond stiffness decay function (stiffness reduction coefficient) to simulate the gradient changes in the mechanical properties of intra- and inter-layer interfaces. This method avoids the problem of abrupt changes in interface stiffness in traditional discrete models, making the inter-layer load transfer more consistent with physical reality.

[0210] Step 2: The mechanical behavior of the composite material is described using the peri-field dynamics method, specifically as shown in the aforementioned formulas (7) and (8). Through these formulas, the peri-field dynamics model can effectively describe the nonlocal interactions and damage propagation of the composite material. Each particle in the model interacts with other particles through the bonding force density and can accurately capture the mechanical behavior of the composite material under complex loading conditions such as low-speed impact and crack propagation.

[0211] Step 3: Processing the contact behavior of the impactor-laminated plate, interlayer interface and particles based on dynamic contact algorithm.

[0212] A multi-scale adaptive contact algorithm is introduced to dynamically adjust contact stiffness and friction during impact, improving the physical consistency and accuracy of the calculation. The contact force adopts a dynamically adjustable power-law nonlinear elastic contact force model. Compared to the traditional fixed-exponential model, this method can adjust the contact stiffness in real time according to material properties and impact energy, enhancing the stability of the contact force calculation.

[0213] A velocity-dependent friction correction model is introduced to adjust the friction coefficient in real time based on the impact velocity, so as to more realistically describe the interface slippage behavior during the impact contact process.

[0214] During the calculation, the contact between the impactor and the laminate, the interlaminar interface, and the particles is dynamically monitored at each time step. Based on changes in impact energy and material stiffness, k(x), q1, q2, and μ are adaptively adjusted to ensure calculation stability. This ensures that the evolution of contact force during the contact initiation, slippage, and recovery stages conforms to actual material behavior, avoiding non-physical oscillation phenomena.

[0215] Step 4: Crack propagation and cross-layer damage propagation based on dynamic damage evolution mechanism.

[0216] An adaptive damage evolution mechanism based on energy dissipation is introduced, which, combined with the cross-layer damage transmission rule, enables the simulation of the entire process of fiber fracture, matrix cracking, and interface debonding, and optimizes the calculation accuracy of crack propagation path.

[0217] Step 5, Calculation Process: During the calculation process, the geometric model of the composite laminate and the impactor is first initialized, and an impact load is applied. The impact loading adopts a displacement-controlled method, with the initial impact velocity set at 6 m / s, and the impact process is gradually advanced in increments of 0.01 mm.

[0218] During the contact phase, a contact algorithm is first applied to calculate the contact force. At each time step, the program dynamically detects the distance between the impactor and the laminate to determine whether contact has occurred and calculates the normal contact force accordingly. A velocity-dependent friction correction model is used, with the friction coefficient adjusted in real time based on the impact velocity. During the impact, the contact force is dynamically updated as the impactor's displacement changes and gradually decreases with the impactor's rebound.

[0219] During damage evolution, the near-field dynamics (PD) method is used to calculate the interaction forces between particles, simulating stress propagation and damage propagation within the laminate. At each time step, the current stress state is calculated, and it is determined whether the damage variable has reached the failure condition. When the damage variable exceeds a threshold, the bonds within the material break, leading to crack formation and propagation. To improve computational efficiency, the Newton-Raphson iterative method is used for numerical solutions, ensuring computational stability and convergence. When debonding occurs at the interface layer, the stress calculation of adjacent layers is automatically adjusted. A gradual stiffness degradation strategy is adopted to ensure smooth changes in interlayer mechanical properties. When the interface damage variable D... interface When the value is ≥0.7, it triggers a weakening of the mechanical properties of adjacent layers.

[0220] Impact response can be analyzed using contact force-time curves, intralaminar damage distribution, and interlaminar shear damage distribution diagrams. Experimental verification shows that the calculated contact force-time curves, damage modes, and crack propagation paths are in high agreement with experimental data, with a peak contact force error of less than 5%, and the crack propagation paths are consistent with experimental results. These results demonstrate that the embodiments of this application can accurately predict the impact response of composite materials, providing a reliable theoretical basis for composite material structural design and optimization.

[0221] Compared to traditional finite element methods (FEM), the embodiments of this application exhibit significant advantages in simulating crack propagation, interface debonding, and fiber fracture, avoiding mesh dependency issues. The nonlocality of the PD method enables it to effectively simulate the damage evolution process of composite materials, providing a more accurate numerical simulation tool for engineering applications. The successful application of the embodiments of this application not only improves the reliability of composite material structures under impact conditions but also provides a new research direction for future impact damage prediction of composite materials.

[0222] Based on the low-velocity impact simulation method for laminates based on peri-field dynamics provided in the above embodiments, this application also provides a computational framework for simulating the low-velocity impact response of composite laminates based on a heterogeneous composite material model and peri-field dynamics methods, which may include:

[0223] • A module used to define the geometry and particle distribution of composite laminates;

[0224] • Material properties module used to describe particle mechanical properties;

[0225] • A near-field dynamics calculation module for calculating nonlocal interactions between particles;

[0226] • A contact algorithm module used to simulate inter-particle contact behavior and calculate contact forces;

[0227] • A numerical solution module for applying impact loads and solving damage evolution;

[0228] • Output module for post-processing and result visualization.

[0229] The numerical solution module can simulate damage modes such as fiber fracture, matrix cracking and interface debonding, and output contact force-time curves, as well as intralayer damage distribution and interlayer shear damage distribution maps.

[0230] In one example, the above computational framework can be as follows: Figure 7 As shown.

[0231] Based on the low-velocity impact simulation method for laminates based on peri-field dynamics provided in the above embodiments, this application also provides specific implementation methods for a low-velocity impact simulation device for laminates based on peri-field dynamics. Please refer to the following embodiments.

[0232] See Figure 8 The low-velocity impact simulation device for laminates based on near-field dynamics provided in this application embodiment may include:

[0233] The acquisition module 801 is used to acquire the near-field dynamic impact model, which includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using near-field dynamics.

[0234] Impact module 802 is used to control the impactor simulation model to perform low-speed impact on the laminate simulation model;

[0235] The determination module 803 is used to determine the contact stiffness of each particle in the contact area of ​​the impactor simulation model in response to a low-velocity impact and in contact with the laminate simulation model, for each time step, based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at the time step; to determine the contact force of each particle in the contact area at the time step based on the contact stiffness and deformation ratio at the time step; and to determine the contact force between the impactor simulation model and the laminate simulation model at the time step based on the contact force of each particle in the contact area at the time step.

[0236] Output module 804 is used to generate a simulation curve of contact force versus time for the laminate corresponding to low-velocity impact, based on the contact force between the impactor simulation model and the laminate simulation model at each time step.

[0237] The low-speed impact simulation device for laminates based on near-field dynamics provided in this application embodiment can realize the various processes in the method embodiment, and will not be repeated here to avoid repetition.

[0238] Figure 9 A schematic diagram of the hardware structure for low-speed impact simulation of laminates based on near-field dynamics provided in an embodiment of this application is shown.

[0239] The low-speed impact simulation device for laminates based on near-field dynamics may include a processor 901 and a memory 902 storing computer program instructions.

[0240] Specifically, the processor 901 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0241] Memory 902 may include mass storage for data or instructions. For example, and not limitingly, memory 902 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 902 may include removable or non-removable (or fixed) media. Where appropriate, memory 902 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 902 is non-volatile solid-state memory.

[0242] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0243] The processor 901 reads and executes computer program instructions stored in the memory 902 to implement any of the low-speed impact simulation methods for laminates based on near-field dynamics in the above embodiments.

[0244] In one example, the low-velocity impact simulation device for laminates based on near-field dynamics may further include a communication interface 909 and a bus 910. Wherein, as Figure 9 As shown, the processor 901, memory 902, and communication interface 909 are connected through bus 910 and complete communication with each other.

[0245] The communication interface 909 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0246] Bus 910, including hardware, software, or both, couples together components of a low-velocity impact simulation device for laminates based on near-field dynamics. This is an example, not a limitation.

[0247] The bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 910 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0248] Furthermore, in conjunction with the insulation resistance detection methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the insulation resistance detection methods in the above embodiments.

[0249] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0250] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. The programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM, floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0251] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0252] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0253] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for simulating low-velocity impacts on laminates based on near-field dynamics, characterized in that, include: A near-field dynamic impact model is obtained, wherein the near-field dynamic impact model includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using near-field dynamics; The impactor simulation model is controlled to subject the laminate simulation model to a low-speed impact; When the impact simulation model contacts the laminate simulation model in response to the low-velocity impact, for each time step, the contact stiffness of each particle in the contact area of ​​the impact simulation model at that time step is determined based on the material properties of each particle in the contact area and the deformation ratio at that time step; the contact force of each particle in the contact area at that time step is determined based on the contact stiffness and the deformation ratio at that time step; and the contact force between the impact simulation model and the laminate simulation model at that time step is determined based on the contact force of each particle in the contact area at that time step. Based on the contact force between the impactor simulation model and the laminate simulation model at each time step, a simulation curve of the contact force versus time corresponding to the low-speed impact of the laminate is generated.

2. The method according to claim 1, characterized in that, The step of determining the contact force of each particle in the contact region at a given time step based on the contact stiffness and deformation ratio of each particle in the contact region at that time step includes: For each particle in the contact area, the first difference between the deformation ratio of the particle at the time step raised to the power of q1 and the deformation ratio of the particle at the time step raised to the power of q2 is obtained, where q1 and q2 are adjustable power exponents, and q1 and q2 are determined based on the material and shape of the impactor simulation model and the laminate simulation model, and q1 is greater than q2. The contact force of the particle at the time step is determined based on the contact stiffness of the particle at the time step and the first difference.

3. The method according to claim 1, characterized in that, The acquisition of the near-field dynamic impact model includes: Establish a three-dimensional spatial model of the laminate; The layers of the three-dimensional spatial model are discretized into a particle matrix consisting of multiple rows and columns. Based on the material properties of the laminate, the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix are set to obtain the simulation model of the laminate. In this configuration, the column direction of the particle matrix corresponding to each layup is the same as the fiber direction of the layup. Each column of particles is divided into a fiber phase particle column or a matrix phase particle column according to a preset fiber content. The fiber phase particle column and the matrix phase particle column are staggered along the row direction of the particle matrix.

4. The method according to claim 3, characterized in that, The mechanical property parameters include the elastic modulus of the particle, and the near-field dynamic bond parameters include the stiffness coefficient of the interlayer bonds of the particle. The step of setting the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix according to the material properties of the laminate includes: Based on the material properties of the laminate, the elastic modulus of each particle in the particle matrix is ​​set; For each particle in the particle matrix, the first basic stiffness coefficient of the target interlayer bond is determined based on the elastic modulus of the particle and the elastic modulus of the connecting particles of the target interlayer bond. Based on the normal height of the particle in the laminate simulation model, the interlayer bond attenuation factor of the particle is determined, wherein the interlayer bond attenuation factor is positively correlated with the normal height; The product of the first basic stiffness coefficient and the interlayer bond attenuation factor is determined as the actual stiffness coefficient of the target interlayer bond.

5. The method according to claim 4, characterized in that, The step of determining the interlayer bond attenuation factor of the particle based on its normal height in the laminate simulation model includes: The ratio of the second difference to the ply thickness of the laminate simulation model is determined as the weighting coefficient of the interlaminar bond stiffness reduction factor of the particle, wherein the second difference is the difference between the normal height and the normal coordinate value of the center position of the first ply of the laminate simulation model. Obtain the maximum stiffness reduction factor and the minimum stiffness reduction factor of the interlaminar bonds in the simulation model of the laminated plate; The difference between the maximum stiffness reduction factor of the interlayer bond and the minimum stiffness reduction factor of the interlayer bond is determined as the basic adjustment step size of the interlayer bond stiffness reduction factor of the laminate simulation model. The product of the weighting coefficient and the basic adjustment step size is determined as the actual adjustment step size of the interlayer bond stiffness reduction coefficient of the particle. The sum of the minimum stiffness reduction factor of the interlayer bond and the actual adjustment step size is determined as the interlayer bond attenuation factor of the particle.

6. The method according to claim 3, characterized in that, The mechanical property parameters include the elastic modulus of the particle, and the near-field dynamic bond parameters include the stiffness coefficient of the interfacial bond of the particle. The step of setting the mechanical property parameters and near-field dynamic bond parameters of each particle in the particle matrix according to the material properties of the laminate includes: Based on the material properties of the laminate, the elastic modulus of each particle in the particle matrix is ​​set; For each particle in the particle matrix, the second basic stiffness coefficient of the target interface bond is determined based on the elastic modulus of the particle and the elastic modulus of the connected particles of the target interface bond of the particle. Obtain the interface adjustment coefficient of the interface where the particle is located; The product of the second basic stiffness coefficient and the interface adjustment coefficient is determined as the actual stiffness coefficient of the target interface key.

7. The method according to claim 1, characterized in that, After determining the contact force between the impactor simulation model and the laminate simulation model at the time step, the method further includes: For each particle in the laminate simulation model, the displacement of the particle in the time step is determined by the near-field dynamics equation based on the external force acting on the particle in the time step; wherein, the external force includes the contact force between the impactor simulation model and the laminate simulation model in the time step; Based on the displacement of the particle at the time step, the damage factor of each bond of the particle at the time step is determined, wherein the damage factor of each bond characterizes whether the bond is damaged. The total number of damaged bonds in the particle at the time step is determined based on the damage factor of each bond in the particle at the time step. The ratio of the total number of damaged bonds to the total number of bonds of the particle is determined as the first damage variable of the particle at the time step, wherein the first damage variable of each particle characterizes the degree of damage of the particle. Based on the first damage variable of each particle at each time step in the laminate simulation model, a damage distribution simulation diagram of the laminate corresponding to the low-velocity impact is generated.

8. The method according to claim 7, characterized in that, The near-field dynamics equations of motion include the interparticle bonding force density, which is determined based on the stiffness coefficient of the interparticle bonds. After determining the damage factor of each bond of the particle at the time step based on the particle's displacement at that time step, the method further includes: The number of damaged interlayer bonds of the particle at the time step is determined based on the damage factor of the interlayer bonds of the particle at the time step. The ratio of the number of damaged interlayer bonds to the total number of interlayer bonds of the particle is determined as the second damage variable of the particle at the time step, wherein the second damage variable of each particle is used to characterize the degree of breakage of the interlayer bonds of the particle. If the second damage variable of the particle is greater than the damage threshold, the stiffness coefficient corresponding to the bonding force density of the interlayer bonds of the particle is multiplied by a stiffness reduction factor, wherein the stiffness reduction factor is less than 1.

9. The method according to claim 7, characterized in that, The external force also includes the frictional force between the impactor simulation model and the laminate simulation model at the time step; Before determining the displacement of the particle at a given time step using near-field dynamics equations based on the external force acting on the particle at that time step, the method further includes: Obtain the relative sliding velocity between the impactor simulation model and the laminate simulation model at the time step; The friction coefficient adjustment factor for the time step is determined based on the relative sliding speed. The actual friction coefficient at the time step is determined based on the initial static friction coefficient and the friction coefficient adjustment factor. Based on the actual friction coefficient and the normal contact force between the impact simulation model and the laminate simulation model at the time step, the friction force between the impact simulation model and the laminate simulation model at the time step is determined.

10. A low-velocity impact simulation device for laminates based on near-field dynamics, characterized in that, The device includes: The acquisition module is used to acquire a near-field dynamic impact model, wherein the near-field dynamic impact model includes a laminate simulation model and an impactor simulation model; both the laminate simulation model and the impactor simulation model are particle models constructed using near-field dynamics. The impact module is used to control the impactor simulation model to perform low-speed impact on the laminate simulation model; A determination module is configured to, for each time step, determine the contact stiffness of each particle in the contact area of ​​the impactor simulation model at a given time step based on the material properties of each particle in the contact area of ​​the impactor simulation model and the deformation ratio at that time step; determine the contact force of each particle in the contact area at that time step based on the contact stiffness and the deformation ratio at that time step; and determine the contact force between the impactor simulation model and the laminate simulation model at that time step based on the contact force of each particle in the contact area at that time step. The output module is used to generate a simulation curve of the contact force versus time of the laminate corresponding to the low-velocity impact, based on the contact force between the impactor simulation model and the laminate simulation model at each time step.

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