A Finite Element Method for Refined Distributed Artillery System

Abstract

This invention discloses a finite element method and apparatus for a refined distributed projectile-guided system. The method constructs simulation models of the projectile body and target plate. The projectile model consists of three propellant charges, two propellant separators positioned between adjacent charges, a fuze holder mounted at the bottom of the projectile, and an outer shell. A sensor is installed in each of the two propellant separators, and a sensor is installed in each base fuze within the fuze holder. Finite element simulation of the penetration process is performed, and acceleration time history curves from sensors located at the projectile tip, mid-projectile, and base are collected. The signals from the three sensors are cross-correlated and filtered to obtain acceleration time history curves decoupled from stress wave aliasing. This invention can reproduce the actual projectile-guided system structure, supports distributed sensor arrangement, and, with the aid of signal processing algorithms, can solve signal aliasing and noise interference problems, achieving high-precision overload signal acquisition.

Description

Technical Field

[0001] This invention belongs to the field of penetration simulation technology, specifically relating to a finite element method and apparatus for a refined distributed missile system. Background Technology

[0002] In the field of engineering, bridges, tunnels, protective structures, underground engineering projects, and warehouse buildings often face unexpected loads such as impacts, collisions, and penetrations. Structural safety monitoring, penetration process testing, and overload signal identification are key technologies for engineering protective design and structural health monitoring. To accurately obtain the true mechanical response inside the structure during penetration, engineering often uses built-in sensors to acquire time-history signals such as acceleration and overload, thereby enabling penetration layer identification, impact intensity judgment, and structural damage assessment.

[0003] In penetration testing and layer counting technology research, experiments are costly, time-consuming, and have poor repeatability; therefore, finite element simulation methods are typically used for simulation verification. Currently, simulation methods for projectile penetration of concrete targets mainly include the following typical technical solutions:

[0004] The first method is the conventional projectile penetration numerical simulation method. The penetration analysis is completed through element selection, model establishment, mesh generation, contact definition, boundary and load application, solution and post-processing. It can quickly simulate the damage effect of the target plate and reduce the test cost. However, the model is relatively simplified and it is difficult to reflect the real mechanical transmission relationship of the internal structure of the projectile.

[0005] The second approach is to construct a physical model for penetration that considers the self-sharpening effect. By establishing the control equations, momentum equations, and penetration pressure equations for the target plate and the projectile, a physical model that can describe the erosion of the projectile is formed. This approach is suitable for the simulation of new armor-piercing materials, but it does not focus on the acquisition and analysis of sensor signals inside the projectile.

[0006] The third method is a simplified modeling approach for penetrating thick concrete targets. Based on the equivalent penetration depth, the reinforced concrete is equivalent to a plain concrete model, which greatly reduces the modeling complexity and computational load. However, it also only focuses on the macroscopic penetration results and does not involve the distributed sensing and overload signal extraction inside the projectile.

[0007] In summary, existing penetration simulation methods generally have the following shortcomings: Most methods only focus on the macroscopic damage characteristics and external mechanical parameters of the projectile penetration, and lack sufficient reproduction of the actual structure of the projectile's internal charge, partitions, fuses, sensors, etc., and cannot accurately obtain the overload signals at different locations inside the projectile.

[0008] Therefore, the applicant considered using a distributed sensing method to collect penetration signals, and installed sensors at multiple locations within the projectile to collect distributed sensing signals. However, due to the influence of stress wave incidence, reflection, and superposition, signals from different measuring points will exhibit severe aliasing. High-frequency noise and local vibrations will mask the true rigid body overload characteristics, resulting in low layer identification accuracy and poor signal reliability, making it difficult to meet the needs of protective engineering for accurate monitoring of the penetration process. Summary of the Invention

[0009] In view of this, the present invention provides a finite element method and apparatus for a refined distributed missile-launching system, which can restore the actual missile-launching system structure, support distributed sensing arrangement, and solve the problems of signal aliasing and noise interference, thereby achieving high-precision overload signal acquisition.

[0010] To solve the above-mentioned technical problems, the present invention is implemented as follows.

[0011] A refined finite element method for distributed articulated systems includes: Step 1: Construct a simulation model of the projectile and target plate. The projectile model consists of 3 explosive charges, 2 explosive charge partitions placed between adjacent explosive charges, a fuse holder installed at the bottom of the projectile, and an outer shell. A sensor is set in each of the 2 explosive charge partitions, and a sensor is set in each fuse at the bottom of the projectile in the fuse holder. Step 2: Mesh the simulation model and set its properties in the finite element software; Step 3: Perform finite element simulation of the penetration process and collect acceleration time history curves from sensors located at the warhead, mid-section, and base of the warhead; Step 4: Based on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, and the spatial uncorrelation of local vibration and noise, the signals collected by the three sensors are cross-correlated in pairs and filtered to obtain the acceleration time history curve of decoupled stress wave aliasing.

[0012] Preferably, in step 2, the grid division is as follows: the internal explosive charge partition, the base fuse, and the sensor are subjected to grid densification; the projection areas of the middle part of the target plate and the tip of the projectile are subjected to grid densification.

[0013] Preferably, in step 2, the property settings include material parameter settings, specifically: The material model for the concrete material is the MAT_JOHNSON_HOLMQUIST_CONCRETE model from the LS-DYNA software. The material models for the cartridge case, propellant charge, propellant charge divider, and fuse seat were all modeled using the MAT_PLASTIC_KINEMATIC model in LS-DYNA software, which simulates the elastic-plastic behavior of materials.

[0014] Preferably, the parameters of the concrete material model MAT_JOHNSON_HOLMQUIST_CONCRETE are set as follows: The material density Ro is 2.175. The shear modulus G is 0.1179 GPa; the normalized cohesive strength A is 0.79; the normalized compressive strength coefficient B is 1.6; the strain rate coefficient C is 0.007; the compressive hardening index N is 0.61; and the normalized quasi-static uniaxial compressive strength FC is... ; The normalized value of the maximum tensile hydrostatic pressure T is The reference strain rate EPS0 is The minimum cumulative plastic strain EFMIN before failure is 0.01; the normalized maximum strength SFMAX is 7.0; and the normalized crushing pressure PC is... The crushing volumetric strain UC is The normalized value of the lock-up pressure PL is 0.012. The locked volumetric strain UL is 0.186; the first damage evolution coefficient D1 is 0.043; the second damage evolution coefficient D2 is 1.0; the first state equation coefficient K1 is 1.3737 GPa; the second state equation coefficient K2 is -9.719 GPa; the third state equation coefficient K3 is 34.834301 GPa; and the failure strain FS is 0.2.

[0015] Preferably, the parameters of the model MAT_PLASTIC_KINEMATIC, which simulates the elastoplastic behavior of materials, are set as follows: The density Ro of the cartridge case is 7.85. The elastic modulus E is 2.01 GPa, and the Poisson's ratio PR is 0.33; The density Ro of the explosive charge is 1.81. The elastic modulus E is 2.01 GPa, and the Poisson's ratio PR is 0.33; The material density Ro of the charge compartment and fuse holder is 4.5. The elastic modulus E is 1.0316 GPa, and the Poisson's ratio PR is 0.31.

[0016] Preferably, in step 2, the attribute settings include the setting of boundary conditions and contact conditions, specifically: The connections between the sensor and the fuse holder, the sensor and the charge plate, the base fuse and the fuse holder, the cartridge case and the fuse holder, and the cartridge case and the charge plate are all made using the contact model CONTACT_TIED_SURFACE_TO_SURFACE in the LS-DYNA software. The projectile and the target plate are connected using a bidirectional erosion contact type model, CONTACT_ERODING_SURFACE_TO_SURFACE, which is used in LS-DYNA software to simulate the contact between two deformable bodies.

[0017] Preferably, in step 1, SOLIDWORKS is used to construct simulation models of the projectile and the target plate.

[0018] The present invention also provides a finite element simulation device for a refined distributed missile-launch system, used to execute the above method; the device includes: a simulation model, a simulation setting module, an acceleration acquisition module, and an aliasing decoupling module; The simulation model includes a projectile model and a target plate model; wherein, the projectile model consists of 3 explosive charges, 2 explosive charge partitions set between adjacent explosive charges, a fuse seat installed at the bottom of the projectile, and an outer shell; a sensor is set in each of the 2 explosive charge partitions, and a sensor is set in each fuse at the bottom of the projectile in the fuse seat; The simulation settings module is used to perform mesh generation and attribute settings on the constructed simulation model in the finite element software; The acceleration acquisition module is used to acquire the acceleration time history curves of three sensors located at the warhead, mid-projectile, and base of the warhead during the finite element simulation of the penetration process. The aliasing decoupling module is used to obtain the acceleration time history curve of decoupled stress wave aliasing by performing pairwise cross-correlation processing and filtering on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, while local vibration and noise exhibit spatial uncorrelation.

[0019] Beneficial effects: (1) This invention abandons the traditional modeling method of simplifying the projectile into a single whole. According to the actual assembly relationship, the projectile body is refined into a distributed structure of multiple charges, charge partitions, fuse seats, fuses and shells. Sensors are arranged in the charge partitions and the fuse at the base of the projectile to form distributed measurement points at the projectile head, the middle of the projectile and the base of the projectile. It can restore the real structure and mechanical transmission path of the projectile-fuse system to the greatest extent, accurately obtain the acceleration overload signal at different positions inside the projectile body, and better fit the actual engineering test conditions. It can deeply explore the signal characteristics presented by different parts of the projectile body. At the same time, in response to the signal aliasing, high-frequency noise and local vibration problems caused by distributed sensing, it uses the similarity of the response waveforms of different measurement points to the same layering event and the spatial uncorrelation of noise and local vibration. It adopts a pairwise cross-correlation calculation and filtering scheme. It can effectively decouple the stress wave aliasing interference, suppress incoherent noise, highlight the rigid body overload characteristics, and significantly improve the accuracy and stability of layer identification.

[0020] (2) The present invention refines the mesh of key parts such as the internal partition, fuse, and sensor of the projectile and the contact area in the middle of the target plate, and uses coarse mesh for non-critical areas; while ensuring simulation accuracy, it improves calculation efficiency and can accurately capture the stress wave propagation law and local dynamic response, making the overload signal calculation more reliable.

[0021] (3) The present invention sets binding contact for the fixed part of the projectile, erosion contact for the projectile target penetration, and automatic surface-to-surface contact for the conventional interaction. Combined with the HJC concrete constitutive model and elastoplastic material model, it accurately describes the mechanical behavior of the material. The simulation model has high consistency with the actual physical process. The error between the velocity-time curve and the theoretical calculation result is less than 1.3%. The model has high accuracy and strong versatility and can be directly used for impact monitoring and structural safety assessment of civil protection engineering.

[0022] (4) This invention constructs a complete load transfer chain from projectile body to fuse holder to fuse to sensor through refined structural modeling and distributed signal acquisition; it can truly reflect the dynamic response differences of internal measuring points during penetration, and provide high-fidelity data support for penetration layer calculation algorithm research, fuse design and overload testing. Attached Figure Description

[0023] Figure 1 This is a flowchart of the finite element method for a refined distributed missile-launching system according to an embodiment of the present invention; Figure 2 This is a quarter-section schematic diagram of the finite element model of the projectile in an embodiment of the present invention; Figure 3 The time history curves of the acceleration of the warhead, mid-course, and base fuses under the condition of 700 m / s. Figure 4 Comparison of the results of cross-correlation processing and filtering of the projectile, mid-course, and tail signals; (a) Cross-correlation processing result and filtered result of the projectile and mid-course signals; (b) Cross-correlation processing result and filtered result of the projectile and tail signals; (c) Cross-correlation processing result and filtered result of the mid-course and tail signals. Figure 5 This is a comparison chart of the simulated velocity-time curve of the projectile and the theoretical calculation results.

[0024] Figure 6 This is a block diagram of the finite element apparatus for the refined distributed missile-launching system of the present invention. Detailed Implementation

[0025] This invention provides a finite element method for a refined distributed projectile-guiding system. This method abandons the traditional modeling approach that simplifies the projectile into a single whole. Instead, it refines the projectile body into a distributed structure consisting of multiple sections of propellant, propellant partition, fuze seat, fuze, and projectile casing, according to the actual assembly relationship. This approach maximizes the reproduction of the actual structure and mechanical transmission path of the projectile-guiding system in engineering practice. At the same time, sensors are deployed at key locations on the propellant partition and the projectile base fuze to achieve synchronous acquisition of overload signals at multiple locations, including the projectile head, mid-projectile, and projectile base.

[0026] However, during actual penetration, distributed sensing at multiple locations can cause signal aliasing due to stress wave incidence, reflection, and superposition, accompanied by high-frequency noise and interference from local structural vibrations. This masks the true rigid body overload characteristics, significantly reducing the accuracy of layer identification. To address this, this application conducts in-depth research on multi-location overload signals, discovering that sensors at different locations exhibit waveform similarities in their responses to the same penetration event, while local vibrations and noise show spatial incoherence. Based on this key principle, a cross-correlation signal processing scheme is designed. By enhancing the coherent components of the signal and suppressing incoherent interference, the aliased signals are effectively decoupled, ultimately obtaining clear and reliable penetration layer characteristic signals, significantly improving the accuracy and stability of layer identification.

[0027] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0028] Figure 1 A flowchart of the finite element method for a distributed missile-launching system according to an embodiment of the present invention is shown. See [link / reference]. Figure 1 In this process, the establishment of the projectile-target simulation model mainly utilizes SOLIDWORKS software to initially build the geometric models of the projectile and target plate. Then, in HYPERMESH, the built geometric model is meshed and the material model is set. Contact, constraint, and loading conditions between the various solid parts are defined. After generating the k-file, it is imported into LS-DYNA for solving and reading. The specific implementation process is shown in the following steps: Step 1: Construct simulation models of the projectile and the target plate.

[0029] The projectile model consists of three propellant charges, two propellant separators positioned between adjacent charges, a fuse holder mounted at the bottom of the projectile, and an outer casing. To study the acceleration signals of the projectile's front and middle sections and the fuse at the bottom, a sensor is installed in each of the two propellant separators, and a sensor is installed in each fuse at the bottom of the fuse holder. In this embodiment, the fuse holder at the bottom of the projectile has two symmetrical fuses, each containing a sensor.

[0030] Step 2: Mesh the simulation model and set its properties in the finite element software.

[0031] (1) Grid division In finite element analysis, the accuracy of mesh generation is crucial, directly affecting mesh size, density, and morphology. Ref proposes a method to set the target surface mesh along the thickness direction to 1 / 6 of the projectile radius, which significantly improves the algorithm's convergence. Based on this optimization strategy, this embodiment further adaptively adjusts the mesh size according to the specific structure and actual motion state of the simulated projectile. The specific adjustment method is as follows: For the mesh division of the projectile: the mesh of the key parts in the center of the projectile, including the explosive charge partition, the fuse at the base of the projectile, and the sensors, is made more dense, while the mesh of the shell part is arranged relatively sparsely.

[0032] All finite element models used the cm-GS unit system. Detailed projectile mesh generation results are shown below. Figure 2 The image clearly shows the grid division and optimized layout of each area. The dark gray area represents the projectile casing, while the yellow, bright red, and dark red areas represent the propellant charge. The alternating dark blue and light green sections represent the propellant charge separators, and the blue area represents the fuse holder. The light blue section within the fuse holder is the base fuse. The screenshot shows the dark green sensor mounted on the base fuse, while the sensors in the head and middle sections are located within the propellant charge separators.

[0033] For target mesh generation: the mesh is refined in the projected areas of the target plate's center and the projectile's nose tip. Specifically, the target plate mesh is divided into a central region and an edge region. Since the central region of the target plate is in direct contact with the projectile, its stress and deformation characteristics are more significant. Therefore, the mesh density in the central region is appropriately increased, and the mesh size is correspondingly reduced. The mesh size is approximately equal to the size of the projectile's nose tip projected onto the target plate, aiming to improve the accuracy and precision of the simulation. The edge region and the target plate's thickness direction use a coarse mesh, with a mesh size twice that of the central region. In one example, the specific dimensions of the target plate and its mesh are shown in Table 1.

[0034] Table 1. Target plate grid size parameters (cm)

[0035] (2) Material parameter settings When simulating concrete materials, the HJC model in LS-DYNA software was selected. The full name of this model is MAT_JOHNSON_HOLMQUIST_CONCRETE. The HJC model is a material model used to simulate the behavior of concrete materials under high strain rate, high pressure and large deformation conditions. It is widely used to simulate the concrete response in extreme events such as explosion, impact and high-speed penetration. For detailed parameter settings, please refer to Table 2.

[0036] Table 2 MAT_JOHNSON_HOLMQUIST_CONCRETE model

[0037] The parameters and units in Table 2 above are: material density Ro (units) Shear modulus G (unit: GPa); Normalized cohesive strength A (dimensionless); Normalized pressure hardening coefficient B (dimensionless); Strain rate coefficient C (dimensionless); Pressure hardening index N (dimensionless); Normalized quasi-static uniaxial compressive strength FC (dimensionless); Normalized maximum tensile hydrostatic pressure T (dimensionless); Reference strain rate EPS0 (unit: ); Minimum cumulative plastic strain EFMIN before failure (dimensionless); Normalized maximum strength SFMAX (dimensionless); Normalized crushing pressure PC (dimensionless); Crushing volumetric strain UC (dimensionless); Normalized locking pressure PL (dimensionless); Locking volumetric strain UL (dimensionless); First damage evolution coefficient D1 (dimensionless); Second damage evolution coefficient D2 (dimensionless); First equation of state coefficient K1 (unit: GPa); Second equation of state coefficient K2 (unit: GPa); Third equation of state coefficient K3 (unit: GPa); Failure strain FS (dimensionless).

[0038] The material models for the cartridge case, propellant charge, propellant charge diaphragm, and fuse seat all employ the MAT_PLASTIC_KINEMATIC model in LS-DYNA software, which simulates the elastoplastic behavior of materials, to more accurately reflect their physical properties. This is a strain rate-dependent elastoplastic material model with failure characteristics. In finite element analysis software such as LS-DYNA, this keyword is used to define the elastoplastic behavior of materials. Detailed parameter settings in this embodiment are listed in Table 3.

[0039] Table 3 Material Parameters of MAT_PLASTIC_KINEMATI

[0040] (3) Setting boundary conditions and contact conditions For the connections between the sensor and the fuze holder, the sensor and the propellant compartment, the base fuze and the fuze holder, the cartridge case and the fuze holder, and the cartridge case and the propellant compartment, these connections are tightly bound and there is no relative sliding or separation during the simulation. Therefore, this invention uses the contact model CONTACT_TIED_SURFACE_TO_SURFACE to maintain the joint movement or deformation of the nodes between them. This keyword is commonly used in finite element analysis to simulate contact between two surfaces that are fixed together. This type of contact can be used to simulate the interaction between two objects (or parts of objects) when they are tightly joined together by welding, strong adhesive, or other means.

[0041] CONTACT_AUTOMATIC_SURFACE_TO_SURFACE is a powerful contact type that can automatically handle complex contact problems and consider various contact effects during simulation. It is typically used to handle complex contact problems such as collisions, impacts, and penetrations. This keyword is also used for bidirectional contacts between other parts. During simulation, it can automatically adjust the position and shape of the contact surfaces to accommodate the relative motion and deformation between objects. It can also consider contact effects such as friction and damping to more accurately simulate real physical phenomena.

[0042] To simulate the penetration relationship between the projectile and each target layer, the projectile and target plate employed the bidirectional erosion contact type model CONTACT_ERODING_SURFACE_TO_SURFACE, which simulates the contact between two deformable bodies. This keyword is particularly suitable for simulation scenarios that may involve material failure, fracture, or erosion. That is, when two surfaces come into contact, this keyword allows for the determination of whether erosion has occurred based on the contact conditions and material properties. If erosion is detected, it will adjust the contact interface and apply corresponding forces accordingly, thereby handling material failure and erosion. This makes it perform excellently in simulating material behavior under extreme conditions such as impact, explosion, and high-speed collision.

[0043] Step 3: Perform finite element simulation on the penetration process and collect acceleration time history curves from sensors located at the warhead, mid-projectile, and base of the warhead.

[0044] Acceleration time history curves of the fuzes at three locations—the warhead, mid-course, and base—were collected at a speed of 700 m / s, as shown in the figure. The figure reveals significant differences in the local vibration characteristics of the signals at the three different locations: the mid-course sensor exhibits the highest peak amplitude, but its oscillations during interlayer flight are also the most intense; the base sensor shows a relatively lower amplitude, and its trailing oscillations after penetrating layers persist for a longer period; the vibration characteristics of the warhead sensor fall between the two. This difference is closely related to the propagation path of the stress wave within the warhead: the warhead is the first to experience the impact, which then generates a stress wave that propagates towards the base; the mid-course location simultaneously receives the incident wave from the warhead and the reflected wave from the base, and the superposition of these two waves significantly enhances the vibration response; while the base, as the structural end, experiences a slower energy dissipation rate after stress wave reflection, resulting in a longer trailing oscillation.

[0045] The above analysis results show that sensors at different locations exhibit waveform similarities in their responses to the same trans-layer event, while local vibrations and noise show spatial independence. This characteristic provides direct physical support for using cross-correlation methods to extract common signal components and suppress uncorrelated interference. The core principle of cross-correlation operation is to achieve signal decoupling by strengthening the coherent parts of the two signals and weakening the incoherent parts.

[0046] Step 4: Based on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, and the spatial uncorrelation of local vibration and noise, the signals collected by the three sensors are cross-correlated in pairs and filtered to obtain the acceleration time history curve of decoupled stress wave aliasing.

[0047] like Figure 4 As shown, after performing cross-correlation and filtering on the acquired triaxial acceleration signals, the high-frequency noise components in the signals are effectively suppressed, the intensity of interlayer interference signals is significantly reduced, and at the same time, the intensity of rigid body overload signals is enhanced, and the interlayer characteristics are clear. From Figure 4 It can be observed that the envelope signal of the cross-correlation function exhibits five peaks, which is consistent with the actual situation of a projectile penetrating a five-layer target, indicating that the algorithm is reliable.

[0048] The effectiveness of the present invention was verified.

[0049] Existing research has focused on the dynamic response characteristics of projectiles. Through diverse methods such as solving wave equations and projectile modal analysis, scholars have explored the close relationship between fuze load characteristics and projectile dynamic response. Based on these analyses, researchers have conducted extensive work on layer-counting algorithm design. Based on cavity expansion theory, the relationship between projectile-target force and velocity during penetration can be obtained through formula derivation. Based on this research, given the projectile-target system parameters, initial conditions can be defined, and the projectile velocity versus time history curve can be derived using Newton's second law.

[0050] The drag force experienced by a rigid projectile during penetration forms the basis for establishing a model to calculate the penetration depth. Based on the cavity expansion model, Forrestal et al. and Chen et al. gave the general form of the rigid projectile penetration drag F as follows: (1) In the formula D For the diameter of the bullet, The uniaxial compressive strength of the target body. For target density, A and B These are constants related to the target material. The instantaneous velocity of the projectile during penetration. P and Q It is a dimensionless number related to the geometry of the warhead and the friction between the projectile and the target.

[0051] According to Newton's second law: (2) In the formula x For the displacement of the projectile, m For the mass of the projectile.

[0052] Combining these two methods, given the detailed parameters of the target, we can derive the formula for calculating the trajectory curve of the projectile's penetration velocity versus time: (3) The projectile, traveling at a velocity of 700 m / s, penetrates five layers of C40 targets spaced 1.8 m apart, with thicknesses of 30 cm, 18 cm, 18 cm, 18 cm, and 18 cm respectively. The simulated time-velocity curves of the projectile are shown below. Figure 5 .

[0053] Depend on Figure 5 It can be seen that the entry and exit times of the projectile when penetrating each layer, as well as the velocity during the interlayer flight phase after penetrating each layer, i.e. the remaining velocity after passing through a layer of target plate, can be compared with the theoretically calculated theoretical remaining velocity of each layer to obtain the error value, as shown in Table 4.

[0054] Table 4. Velocity drop per layer during projectile penetration.

[0055] The data above shows that the error values ​​are all within the allowable range, and the overall reliability of the model has been verified.

[0056] Based on the aforementioned finite element method for refined distributed missile-launching systems, this invention also provides a finite element apparatus for refined distributed missile-launching systems, such as... Figure 6 As shown, it includes a simulation model, a simulation settings module, an acceleration acquisition module, and an aliasing decoupling module.

[0057] The simulation model includes a projectile model and a target plate model. The projectile model consists of three explosive charges, two explosive charge partitions placed between adjacent explosive charges, a fuse holder installed at the bottom of the projectile, and an outer shell. A sensor is installed in each of the two explosive charge partitions, and a sensor is installed in each fuse at the bottom of the projectile in the fuse holder.

[0058] The simulation settings module is used to mesh and set properties for the simulation model built in the finite element software.

[0059] The acceleration acquisition module is used to acquire acceleration time history curves from sensors located at the warhead, mid-projectile, and base of the projectile during the finite element simulation of the penetration process.

[0060] The aliasing decoupling module is used to obtain the acceleration time history curve of decoupled stress wave aliasing by performing pairwise cross-correlation processing and filtering on the signals collected by the three sensors based on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, while local vibration and noise exhibit spatial uncorrelation characteristics.

[0061] The specific embodiments described above only illustrate the design principles of the present invention. The shapes and names of the components in this description may differ and are not limited. Therefore, those skilled in the art can modify or make equivalent substitutions to the technical solutions described in the foregoing embodiments; and these modifications and substitutions do not depart from the inventive spirit and technical solutions of the present invention, and should all fall within the protection scope of the present invention.

Claims

1. A finite element method for refining a distributed projectile launch system, characterized by, include: Step 1: Construct a simulation model of the projectile and target plate. The projectile model consists of 3 explosive charges, 2 explosive charge partitions placed between adjacent explosive charges, a fuse holder installed at the bottom of the projectile, and an outer shell. A sensor is set in each of the 2 explosive charge partitions, and a sensor is set in each fuse at the bottom of the projectile in the fuse holder. Step 2: Mesh the simulation model and set its properties in the finite element software; Step 3: Perform finite element simulation of the penetration process and collect acceleration time history curves from sensors located at the warhead, mid-section, and base of the warhead; Step 4: Based on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, and the spatial uncorrelation of local vibration and noise, the signals collected by the three sensors are cross-correlated in pairs and filtered to obtain the acceleration time history curve of decoupled stress wave aliasing.

2. The method of claim 1, wherein, In step 2, the grid division is as follows: the internal explosive charge partition, the base fuse, and the sensor are subjected to grid densification; the projection areas of the middle part of the target plate and the tip of the projectile are subjected to grid densification.

3. The method as described in claim 1, characterized in that, In step 2, the attribute settings include material parameter settings, specifically: The material model for the concrete material is the MAT_JOHNSON_HOLMQUIST_CONCRETE model from the LS-DYNA software. The material models for the cartridge case, propellant charge, propellant charge divider, and fuse seat were all modeled using the MAT_PLASTIC_KINEMATIC model in LS-DYNA software, which simulates the elastic-plastic behavior of materials.

4. The method as described in claim 3, characterized in that, The parameters of the concrete material model MAT_JOHNSON_HOLMQUIST_CONCRETE are set as follows: The material density Ro is 2.

175. The shear modulus G is 0.1179 GPa. Normalized cohesive strength A is 0.79; normalized compressive strength coefficient B is 1.6; strain rate coefficient C is 0.007; compressive hardening index N is 0.61; normalized quasi-static uniaxial compressive strength FC is... ; The normalized value of the maximum tensile hydrostatic pressure T is The reference strain rate EPS0 is The minimum cumulative plastic strain EFMIN before failure was 0.

01. The normalized maximum strength (SFMAX) is 7.0; the normalized crushing pressure (PC) is... The crushing volumetric strain UC is The normalized value of the lock-up pressure PL is 0.

012. The locked volumetric strain UL is 0.186; the first damage evolution coefficient D1 is 0.043; the second damage evolution coefficient D2 is 1.0; the first state equation coefficient K1 is 1.3737 GPa; the second state equation coefficient K2 is -9.719 GPa; the third state equation coefficient K3 is 34.834301 GPa; and the failure strain FS is 0.

2.

5. The method as described in claim 3, characterized in that, The parameters of the model MAT_PLASTIC_KINEMATIC, which simulates the elastoplastic behavior of materials, are set as follows: The density Ro of the cartridge case is 7.

85. The elastic modulus E is 2.01 GPa, and the Poisson's ratio PR is 0.33; The density Ro of the explosive charge is 1.

81. The elastic modulus E is 2.01 GPa, and the Poisson's ratio PR is 0.33; The material density Ro of the charge compartment and fuse holder is 4.

5. The elastic modulus E is 1.0316 GPa, and the Poisson's ratio PR is 0.

31.

6. The method as described in claim 1, characterized in that, In step 2, the attribute settings include the setting of boundary conditions and contact conditions, specifically: The connections between the sensor and the fuse holder, the sensor and the charge plate, the base fuse and the fuse holder, the cartridge case and the fuse holder, and the cartridge case and the charge plate are all made using the contact model CONTACT_TIED_SURFACE_TO_SURFACE in the LS-DYNA software. The projectile and the target plate are connected using a bidirectional erosion contact type model, CONTACT_ERODING_SURFACE_TO_SURFACE, which is used in LS-DYNA software to simulate the contact between two deformable bodies.

7. The method as described in claim 1, characterized in that, In step 1, SOLIDWORKS is used to build simulation models of the projectile and the target plate.

8. A finite element simulation device for a refined distributed missile-launch system, characterized in that, The apparatus for performing the method according to any one of claims 1-7 comprises: a simulation model, a simulation setting module, an acceleration acquisition module, and an aliasing decoupling module; The simulation model includes a projectile model and a target plate model; wherein, the projectile model consists of 3 explosive charges, 2 explosive charge partitions set between adjacent explosive charges, a fuse seat installed at the bottom of the projectile, and an outer shell; a sensor is set in each of the 2 explosive charge partitions, and a sensor is set in each fuse at the bottom of the projectile in the fuse seat; The simulation settings module is used to perform mesh generation and attribute settings on the constructed simulation model in the finite element software; The acceleration acquisition module is used to acquire the acceleration time history curves of three sensors located at the warhead, mid-projectile, and base of the warhead during the finite element simulation of the penetration process. The aliasing decoupling module is used to obtain the acceleration time history curve of decoupled stress wave aliasing by performing pairwise cross-correlation processing and filtering on the waveform similarity of the responses of sensors at different locations to the same trans-layer event, while local vibration and noise exhibit spatial uncorrelation.

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