A method and device for simulating calculation of super-high-speed collision space debris cloud

Abstract

The application relates to a kind of super-high-speed collision space debris cloud simulation calculation method and device in aerospace technology field, the method comprises the following steps: establishing the three-dimensional geometric model of projectile and target plate, the model is meshed, each grid corresponds one SPH particle, reads initial parameter and assigns to the SPH particle, searches the particle adjacent to the SPH particle and the particle adjacent to the SDPH particle, calculates the update parameter of the SPH particle and the update parameter of the SDPH particle based on the search result, judges whether SPH particle is converted into SDPH particle or not;If not, the update parameter of SPH particle is used to update SPH particle parameter;If yes, the update parameter of the SDPH particle obtained by using the update parameter calculation method of SDPH particle is used to update the SDPH particle parameter, after the end of the above loop calculation, the debris cloud shape distribution and scale distribution can be visualized and displayed.The application reduces the amount of calculation, and has better accuracy.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of spaceflight, and particularly relates to a simulation calculation method and device for a space debris cloud in super-speed collision. BACKGROUND

[0002] With the rapid development of space technology, a large number of space debris are left in the near-earth orbit of the earth, and these space debris with super-speed have a significant threat to the safety of spacecraft. The technology of adding a buffer protection screen outside the cabin wall of the spacecraft is an effective spacecraft protection technology. The protection mechanism is that after the space debris penetrates the protection screen, the space debris is broken into a large number of smaller debris, and the broken debris is like a cloud in a macroscopic view, which is called a debris cloud. The formation of the debris cloud makes the kinetic energy of the space debris highly dispersed and partially dissipated in the form of heat energy, which can greatly reduce the damage strength of the space debris to the spacecraft.

[0003] There are mainly two methods for studying the motion process of the space debris cloud in super-speed collision:

[0004] The first method is an experimental method, a local model of a projectile impacting a target plate is established based on the physical process of the space debris cloud in super-speed collision, an ultra-high-speed collision test bench is built, and a high-speed camera is used to capture the impact process of the projectile impacting the target plate and the diffusion shape of the debris cloud formed after the impact. The disadvantages of this method are that the experimental device is large in size, time-consuming and labor-consuming to build, the experimental results are random, and it is difficult to obtain the mechanical parameters in the collision process and the size distribution of the debris in the debris cloud through experimental means.

[0005] The second method is a numerical simulation method, and the current numerical simulation of the space debris cloud in super-speed collision mostly adopts a smoothed particle hydrodynamics method (SPH) or a discrete element method (DEM), the former is difficult to accurately track the motion of a large number of discrete debris in the formation process of the debris cloud, and the latter is too large in consumption of computing resources and is difficult to be used in actual engineering. SUMMARY

[0006] To solve the above technical problems, an embodiment of the present application provides a simulation calculation method for a space debris cloud in super-speed collision to solve the problems in the prior art.

[0007] To achieve the above purpose, an embodiment of the present application adopts the following technical solution:

[0008] An embodiment of the present application provides a simulation calculation method for a space debris cloud in super-speed collision, which is used for simulating the formation and motion process of the space debris cloud in super-speed collision, obtaining the shape distribution and size distribution of the debris cloud, and the method comprises the following steps:

[0009] Step 1, establishing a three-dimensional geometric model of a projectile and a target plate, meshing the model, and corresponding each mesh to a smoothed particle hydrodynamics (SPH) particle;

[0010] Step 2, reading initial parameters and assigning them to the SPH particles;

[0011] Step 3, searching for neighboring particles of the SPH particles, and if a smoothed discrete particle hydrodynamics (SDPH) particle is found, searching for neighboring particles of the SDPH particle;

[0012] Step 4, calculating updated parameters of the SPH particles and updated parameters of the SDPH particles based on the search results;

[0013] Step 5, determining whether the SPH particle is converted into the SDPH particle; if not, updating the SPH particle parameters using the calculated updated parameters of the SPH particle; if yes, updating the SDPH particle parameters using the calculated updated parameters of the SDPH particle;

[0014] The above steps 3-5 are repeatedly executed until a preset time length is reached:

[0015] Step 6, after the above loop calculation ends, visualizing and displaying the distribution and scale of the debris cloud according to the updated SPH particle parameters and the updated SDPH particle parameters.

[0016] Optionally, the initial parameters include:

[0017] parameters in a state equation during the process of the projectile impacting the target plate; and

[0018] parameters in a constitutive model of the projectile impacting the target plate.

[0019] Optionally, the step of calculating the updated parameters of the SPH particles based on the search results includes:

[0020] if the SPH particle searches for the SDPH particle, the external force of the SDPH particle on the SPH particle is additionally calculated, the external force is added to a momentum conservation equation of the SPH particle, and the momentum conservation equation, a mass conservation equation, and an energy conservation equation are solved to obtain the updated parameters of the SPH particle.

[0021] Optionally, the updated parameters of the SPH particle include at least mass, velocity, position, and energy.

[0022] Optionally, the step of calculating the updated parameters of the SDPH particle includes:

[0023] If a SPH particle adjacent to the SDPH particle is searched, a stress in the form of quasi-two-body collision between the SPH particle and the SDPH particle is calculated, and the stress in the form of quasi-two-body collision is added to the momentum conservation equation of the SDPH particle to solve the momentum conservation equation, the mass conservation equation and the energy conservation equation, so that the updated parameters of the SDPH particle are obtained.

[0024] Optionally, the updated parameters of the SDPH particle at least include mass, velocity, position and quasi-temperature.

[0025] Optionally, the step of judging whether the SPH particle is converted into the SDPH particle comprises:

[0026] judging whether the damage value of the SPH particle is equal to 1;

[0027] If the damage value is equal to 1, it is confirmed that the material is completely damaged to form discrete fragments, and it is further judged whether the average characteristic size of the fragments is smaller than the initial size of the SPH particle.

[0028] If the average characteristic size of the fragments is smaller than the initial size of the SPH particle, it is confirmed that the SPH particle is converted into the SDPH particle.

[0029] Another embodiment of the present application provides a device for simulating the formation and movement process of a space debris cloud in a hypervelocity impact, and obtaining the shape distribution and size distribution of the space debris cloud, the device comprising:

[0030] a model establishing unit, configured to establish a three-dimensional geometric model of a projectile and a target plate, divide the model into grids, and correspond each grid to a smooth particle hydrodynamics (SPH) particle;

[0031] a parameter reading unit, configured to read initial parameters and assign the initial parameters to the SPH particles;

[0032] a neighboring particle searching unit, configured to search for particles adjacent to the SPH particle, and if a smooth discrete particle hydrodynamics (SDPH) particle is searched, search for particles adjacent to the SDPH particle;

[0033] a parameter calculating unit, configured to calculate updated parameters of the SPH particle and updated parameters of the SDPH particle based on the search results;

[0034] a judging and parameter updating unit, configured to judge whether the SPH particle is converted into the SDPH particle, if not, update the parameters of the SPH particle by using the calculated updated parameters of the SPH particle, and if yes, update the parameters of the SDPH particle by using the calculated updated parameters of the SDPH particle;

[0035] A visualization unit is configured to visualize the distribution of the shape and the scale of the debris cloud according to the updated SPH particle parameters and the updated SDPH particle parameters after the calculation is completed.

[0036] Another embodiment of the present application provides an electronic device, comprising a processor and a machine readable storage medium, the machine readable storage medium stores machine executable instructions which can be executed by the processor, and the processor is prompted by the machine executable instructions to implement the method described above.

[0037] Yet another embodiment of the present application provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method described above.

[0038] The embodiments of the present application have the following beneficial effects:

[0039] The embodiments of the present application adopt the SPH-SDPH coupling method to perform three-dimensional numerical simulation on the problem of super-high-speed collision space debris cloud, can not only accurately track the real debris trajectory, but also greatly reduce the calculation amount, can simulate the movement of a large number of debris with fewer particles, obtain the space movement and distribution of the debris cloud, and obtain the scale of the debris cloud, the shape distribution of the debris cloud is basically consistent with the experimental results, has better accuracy compared with the existing numerical simulation method, and needs less computing resources.

[0040] Of course, implementing any product or method of the present application does not necessarily need to achieve all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0042] Figure 1 A flow chart of a super-high-speed collision space debris cloud simulation calculation method according to an embodiment of the present application;

[0043] Figure 2-1 A left view of the particle model of the dispersed projectile and target plate according to the built model;

[0044] Figure 2-2 A top view of the particle model of the dispersed projectile and target plate according to the built model;

[0045] Figure 3 A schematic diagram of the corresponding relationship between the SDPH particle and the debris cloud;

[0046] Figure 4-1 This is a schematic diagram illustrating insufficient material fragmentation in the SPH-SDPH coupling method.

[0047] Figure 4-2 This is a schematic diagram illustrating the complete material fragmentation process in the SPH-SDPH coupling method.

[0048] Figure 5 This is a map showing the morphological distribution of debris clouds simulated using the SPH-SDPH coupling method.

[0049] Figure 6-1 The left view shows the scale distribution of debris clouds simulated using the SPH-SDPH coupling method.

[0050] Figure 6-2 This is a top view of the fragment cloud scale distribution simulated using the SPH-SDPH coupling method;

[0051] Figure 7 This is a schematic diagram of a high-speed collision space debris cloud simulation computing device according to an embodiment of this application;

[0052] Figure 8 This is a structural block diagram of a device for simulating and calculating ultra-high-speed collision space debris clouds according to an embodiment of this application;

[0053] Figure 9 This is a schematic diagram of the structure of a server according to an embodiment of this application. Detailed Implementation

[0054] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can also be combined with each other.

[0055] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of the invention, the terms "first," "second," "third," "fourth," etc., are used only to distinguish descriptions and should not be construed as merely or implying relative importance.

[0056] This invention proposes a simulation method for ultra-high-speed collision space debris clouds. It transforms the traditional SPH method into an SDPH method suitable for solving discrete media. This SDPH method establishes a one-to-one correspondence between SDPH particles and real debris by introducing parameters such as pseudo-temperature, debris scale distribution, and the number of represented debris. This extends the SPH single particle from a geometric point mass to a physical point mass that can represent a discrete debris group with a certain particle size distribution, thereby achieving the solution for discrete media. Furthermore, the method of this invention establishes an SPH-SDPH coupled algorithm that considers the full development of debris. This not only accurately tracks the motion trajectory of real debris but also significantly reduces the computational load. It can simulate the motion of a large number of debris with fewer particles, obtaining both the spatial motion and distribution of the debris cloud, as well as its scale. The morphological distribution of the debris cloud basically matches the experimental results, demonstrating better accuracy and requiring fewer computational resources compared to existing numerical simulation methods.

[0057] like Figure 1 The diagram shows a flowchart of the simulation calculation method for ultra-high-speed collision space debris clouds according to an embodiment of the present invention. The method is used to simulate the formation and motion process of ultra-high-speed collision space debris clouds, and to obtain the morphological distribution and scale distribution of the debris clouds. The method includes:

[0058] Step 1: Establish a three-dimensional geometric model of the projectile and the target plate, divide the model into meshes, and assign each mesh to an SPH particle.

[0059] Based on the actual problem of space debris clouds from hypersonic collisions, a three-dimensional geometric model of the projectile and target plate is established. The model is then meshed, discretized using SPH (Spatial Phosphorescent) technology, and the mesh is converted into SPH particles. The model material is aluminum alloy, and the model dimensions are consistent with the experimental conditions. The method for establishing the three-dimensional geometric model of the projectile and target plate can be implemented using existing methods, such as Hypermesh software; this invention does not impose specific limitations.

[0060] The implementation process of this step may include the following sub-steps:

[0061] Step 10: Use Hypermesh software to create geometric models of the projectile and target plate.

[0062] Step 11: Mesh the established geometric model in Hypermesh.

[0063] Step 12: Convert the mesh files of the projectile and target plates formed after division into meshes to particles: following the principle of one mesh corresponding to one particle, the volume of the hexahedral mesh is the volume of the SPH particle, and the center of mass of the mesh is the center of mass of the SPH particle, which is the initial position of the SPH particle. This yields the particle model of the structure. The volume of a single SPH particle determines its mass, and the center of mass of the SPH particle directly determines the initial position of the matter.

[0064] Figure 2-1 and Figure 2-2 The images show the left and top views of the discretized particle models of the projectile and target plate, respectively, based on the established model. The circular area represents the projectile, and the square area represents the target plate. The diameter of the SPH particles is 0.4 mm, the diameter of the projectile is 10 mm, and the number of discretized SPH particles in the projectile is 8217. The length and width of the target plate are both 40 mm, the thickness is 4 mm, and the number of discretized SPH particles in the target plate is 100,000. The projectile impacts the target plate head-on with an impact velocity of 6.18 km / s and a time step of 0.1. The smooth length is taken as 1.3 times the interparticle distance. The elastic modulus E of the projectile and target plate materials is 68 GPa, and the Poisson's ratio is... The density is 0.33. It is 2790 kg / m3.

[0065] Step 2: Read the initial parameters and assign them to the SPH particles.

[0066] The initial parameters of the projectile impact target model are read and the physical information is stored on the SPH particle. These initial parameters include the parameters in the state equation during the projectile impact on the target and the parameters in the constitutive model of the projectile impact on the target.

[0067] The parameters in the state equation during the projectile impact on the target plate include:

[0068] The parameters in the constitutive model of the projectile impacting the target plate include:

[0069] m=1.0, n=0.34.

[0070] Its parameters are used in the following formula:

[0071] Gruneisen equation of state:

[0072] (1)

[0073] in,

[0074] (2)

[0075] In the formula, , For material density, The initial density of the material, This represents the internal energy of the material. A constant coefficient. They are respectively:

[0076] (3)

[0077] (4)

[0078] (5)

[0079] The constitutive models for the projectile and target plate materials in this embodiment of the invention are as follows: The constitutive model for the aluminum projectile and aluminum target plate materials adopts the Johnson-Cook constitutive model with damage model, in which the yield stress... The expression is:

[0080] (6)

[0081] In the formula, D is the damage variable. For accumulated damage plastic strain, where Represents cumulative plastic strain, dimensionless plastic strain rate for , , For custom reference strain rate, temperature , At room temperature Let A be the melting point of the material, and B, C, n, and m be material constants. , This indicates that the material is undamaged. This indicates that the material has completely failed. This is the fracture plastic strain, which is related to the material's stress triaxiality, strain rate, and temperature. For material constants, For stress triaxiality, This represents the average value of the normal stress.

[0082] The initial parameters read in this embodiment of the invention are all the parameters in Table 1 below, as well as the parameters used for contact force.

[0083] Table 1

[0084]

[0085] Step 3: Search for particles near the SPH particle. If a smooth discrete particle hydrodynamic SDPH particle is found, then search for particles near the SDPH particle.

[0086] This invention employs a neighbor-nearest particle search method to search for particles near the SPH particle. If an SDPH particle is found near the SPH particle, the external force exerted by the SDPH particle on the SPH particle is calculated, and the mass, momentum, and energy conservation equations for the SPH particle are solved to obtain updated parameters for the SPH particle. Similarly, the neighbor-nearest particle search method is used to search for particles near the SDPH particle. When an SPH particle is found, the stress in the quasi-two-body collision form between the SPH and SDPH particles is calculated, and the mass, momentum, and energy conservation equations are solved to obtain updated parameters for the SDPH particle. If no SPH particle is found near the SDPH particle, the mass, momentum, and energy conservation equations for the SDPH particle are solved to obtain updated parameters for the SDPH particle.

[0087] Step 4: Calculate the update parameters of the SPH particles and the update parameters of the SDPH particles based on the search results;

[0088] To calculate the motion and stress of discrete fragment groups after a target plate breaks due to damage, this invention improves the traditional SPH method to the SDPH method, which is suitable for solving discrete media. Discrete particles are treated as pseudo-fluids, and the fluid model is solved by representing a series of discrete particle groups with a certain particle size distribution using each SDPH particle, thereby achieving effective simulation of discrete particle media. Furthermore, to accurately simulate the formation process of ultra-high-speed collision space debris clouds, track the motion of a large number of fragments, and obtain the scale distribution of the fragments, a coupled SPH-SDPH algorithm is proposed and established.

[0089] First, SDPH particles are introduced. The correspondence between SDPH particles and real discrete particulate media is established as follows:

[0090] (7)

[0091] in, The effective density of the particles, For particle subscripts, and Let N and denot be the volume fraction of the particles and the actual density of the particulate medium, respectively. If the number of particles in the flow field region is N, the average volume of the particles is... The average mass of the particles is The total volume of the space occupied by the flow field region is Therefore, the above correspondence can be expressed as:

[0092] (8)

[0093] in The mass of an SDPH particle is equal to the total mass of the particle swarm it represents, its density is the effective density of the particle swarm, and its velocity, pseudo-temperature, and pressure are all the mean values ​​of the represented particle swarm. The pseudo-temperature is defined as... , This indicates the pulsation velocity of the particles. This represents the average velocity of the particles.

[0094] The SDPH method was used to simulate the debris cloud. Each SDPH particle represented a real debris swarm with a certain number and size distribution. The correspondence between SDPH particles and debris clouds is shown in the diagram below. Figure 3 As shown.

[0095] SDPH method for discrete particulate media:

[0096] The mass conservation equation, momentum conservation equation, and energy conservation equation (quasi-temperature equation) for the granular phase are as follows:

[0097] (9)

[0098] (10)

[0099] (11)

[0100] in, , , These represent the particle volume fraction, density, and average velocity, respectively. For discrete medium pressure gradient, External volume force The energy generated by the stress of the granular medium. For energy dissipation, The energy dissipation coefficient, The energy dissipation terms resulting from interparticle collisions are expressed as follows:

[0101] (12)

[0102] (13)

[0103] in, The particle diameter is [value missing].

[0104] Let be the viscous stress tensor of the particles, defined as follows:

[0105] (14)

[0106] in, and These are the shear viscosity and volume viscosity of the particles. It is a unit tensor.

[0107] Discretize the SDPH conservation equations (9), (10), and (11) as follows:

[0108] (15)

[0109] (16)

[0110] (17)

[0111] Stress in the formula , The particle phase pressure is expressed as:

[0112] (18)

[0113] in, Let be the radial distribution function of the particles.

[0114] The SPH method is an existing technology and will not be described in detail in this invention.

[0115] Step 5: Determine whether SPH particles have been converted into SDPH particles;

[0116] If not, proceed to step 6-1 to update the SPH particle parameters using the calculated update parameters of the SPH particles.

[0117] If so, proceed to step 6-2 and update the SDPH particle parameters using the SDPH particle update parameter calculation method.

[0118] The damage value of SPH particles is calculated. When the damage value is less than 1, the material has not failed, and the SPH particles are not transformed. When the damage value is equal to 1, it represents complete material failure, forming discrete fragments. The average characteristic size of the fragments is further calculated. If the average characteristic size of the fragments is smaller than the initial discrete SPH particle size, the SPH particles are transformed into SDPH particles to simulate a discrete fragment group with a certain particle size distribution. If the average characteristic size of the fragments is larger than the initial discrete SPH particle size, the SPH particles are not transformed, and the discrete fragments are still simulated by SPH particles. The damage calculation formula is as follows:

[0119] (19)

[0120] in, To accumulate plastic strain, The fracture plastic strain is represented by the damage value D, which ranges from 0 to 1. When D=0, it indicates that the material is undamaged; when D=1, it indicates that the material has completely failed and formed fragments. The average characteristic size s of the fragments is calculated using the following material dynamic fracture criterion formula:

[0121] (20)

[0122] Where Y is the yield strength, The critical failure strain. For material density, The material strain rate.

[0123] The initial discrete SPH particles in the model have a diameter of 0.4 mm. Therefore, 0.4 mm is used as the boundary for the transformation from SPH particles to SDPH particles in the simulation. When the average characteristic size s of the fragments is greater than 0.4 mm, the SPH method is used for simulation, with multiple SPH particles jointly representing a single actual fragment. When the average characteristic size s of the fragments is less than 0.4 mm, the SPH particles are transformed into SDPH particles for calculation, with each SDPH particle representing a certain number of fragment groups. By using different methods to simulate fragments of different scales, an SPH-SDPH coupling method framework is established, such as... Figure 4-1 This is a schematic diagram illustrating insufficient material fragmentation in the SPH-SDPH coupling method. Figure 4-2 This is a schematic diagram illustrating the complete material fragmentation process in the SPH-SDPH coupling method.

[0124] If SPH particles do not transform into SDPH particles, the SPH particle parameters are updated using the calculated update parameters of the SPH particles. If SPH particles transform into SDPH particles, the SDPH particle parameters are updated using the update parameters of the SDPH particles calculated using the SDPH particle update parameter calculation method. The update parameters of the SPH particles include at least: mass, velocity, position, and energy. The update parameters of the SDPH particles include at least: mass, velocity, position, and pseudo-temperature.

[0125] Step 7: Determine if the calculation time has reached the specified duration;

[0126] Repeat steps 3 to 6 above. After each round of calculation, update the total calculation time until the total calculation time reaches the preset time, that is, compare the total calculation time T with the program stop time. At that time, the SPH-SDPH coupled calculation ends.

[0127] Through the above numerical simulation calculations, data such as velocity, stress, damage, fragment cloud distribution, and fragment size distribution during the projectile impact on the target plate can be obtained. The entire process of the projectile impacting the target plate, from deformation to damage and then to fragmentation and the formation of a fragment cloud, can be simulated, and the stress distribution, damage factor distribution, fragment cloud morphology distribution, and fragment size distribution during this process can be obtained.

[0128] Step 8: After the above iterative calculations are completed, visualize the morphological distribution and scale distribution of the fragment cloud based on the updated SPH particle parameters and the updated SDPH particle parameters.

[0129] This step is a post-processing procedure for the calculation results, which can be completed using Tecplot software. Import the data calculated in the above steps into Tecplot to visualize the data such as velocity, stress, damage factor, fragment size distribution, and fragment cloud morphology distribution during the projectile impact on the target plate. Figure 5 The figure shows the morphological distribution of debris clouds simulated using the SPH-SDPH coupling method. The region represents a concentrated area of ​​the kernel debris cloud, and the expansion length of the debris cloud is expressed as... The expansion width of the fragment cloud is represented by... express, This refers to the aspect ratio, which characterizes the morphological features of fragment clouds. Figure 6-1 The left view shows the scale distribution of fragment clouds. Figure 6-2 This is a top view showing the scale distribution of fragment clouds. Figure 6-1 The analysis was conducted in four regions: A, B, C, and D. Region B is the region with the smallest average feature size of the fragments in the entire fragment cloud, less than 0.05 mm. This indicates that each SDPH particle represents dozens to hundreds of discrete fragments. If the traditional SPH method is used for simulation, accurately tracking the distribution of these fragments would result in a very large computational load for the entire case. However, by using the new SPH-SDPH coupling method, the fragment cloud morphology distribution in region B can be simulated with fewer particles, and the fragment density in this region can be predicted based on the fragment cloud scale distribution, greatly reducing the computational load.

[0130] This embodiment employs the SPH-SDPH coupling method for three-dimensional numerical simulation of the ultra-high-speed collision space debris cloud problem. By simulating the motion of a large number of discrete debris particles with a smaller number of particles, the morphological and scale distribution of the debris cloud during the projectile impact on the target plate was obtained. The morphological distribution of the debris cloud shows good agreement, confirming the effectiveness of the SPH-SDPH coupling method. This provides data support and guidance for the optimized design of spacecraft protective shields.

[0131] This invention also provides a simulation computing device for ultra-high-speed collision space debris clouds, such as... Figure 7The diagram shows the structure of the device, which is used to simulate the formation and motion of a hypersonic collision space debris cloud, and to obtain the morphological and scale distribution of the debris cloud. The device includes:

[0132] Model building unit 70 is used to build a three-dimensional geometric model of the projectile and the target plate, and to divide the model into meshes, with each mesh corresponding to a smooth particle hydrodynamic (SPH) particle.

[0133] Parameter reading unit 71 is used to read initial parameters and assign them to the SPH particles;

[0134] The neighboring particle search unit 72 is used to search for particles near the SPH particle. If a smooth discrete particle hydrodynamic SDPH particle is found, then the neighboring particles of the SDPH particle are searched.

[0135] The parameter calculation unit 73 is used to calculate the updated parameters of the SPH particles and the updated parameters of the SDPH particles based on the search results.

[0136] The judgment and parameter update unit 74 is used to determine whether SPH particles are converted into SDPH particles; if not, the SPH particle parameters are updated using the calculated update parameters of the SPH particles; if so, the SDPH particle parameters are updated using the update parameters of the SDPH particles calculated using the update parameter calculation method of the SDPH particles.

[0137] Visualization unit 75 is used to visualize the morphological and scale distribution of the fragment cloud based on the updated SPH particle parameters and the updated SDPH particle parameters after the calculation is completed.

[0138] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0139] In summary, the simulation calculation method and apparatus for hypervelocity collision space debris clouds provided by this invention can predict the morphological and scale distribution of hypervelocity collision space debris clouds while significantly reducing computational complexity. This invention introduces a novel SPH-SDPH coupled algorithm, which not only incorporates the SPH method to simulate incompletely damaged portions and fragments with an average feature size larger than the initial discrete SPH particle diameter, but also transforms the traditional SPH method into an SDPH method suitable for solving discrete media. Each SDPH particle can represent a set of discrete fragments with a specific particle size distribution, capable of reproducing the entire physical process of debris cloud formation after complete target damage. This invention provides an effective approach for studying the motion and distribution of hypervelocity collision debris clouds and optimizing the protective performance of spacecraft shields.

[0140] Furthermore, this invention can not only obtain the morphological distribution of debris clouds but also their scale distribution, and analyze the formation process and damage influencing factors. Simultaneously, this invention not only reflects the actual motion of discrete debris but also significantly reduces the computational load. Therefore, for the problem of hypervelocity collision debris clouds in the aerospace field, this new technology has achieved excellent prediction results in terms of the formation process, morphological distribution, and scale distribution of debris clouds.

[0141] This invention also provides an apparatus for simulating and calculating space debris clouds from hypersonic collisions, comprising a memory and one or more programs, wherein the programs are stored in the memory and configured to be executed by one or more processors. The programs contain instructions for performing the following operations: Step 1: Establishing a three-dimensional geometric model of the projectile and the target plate, dividing the model into meshes, and assigning each mesh to a smooth particle hydrodynamic (SPH) particle; Step 2: Reading initial parameters and assigning them to the SPH particle; Step 3: Searching for particles neighboring the SPH particle; if a smooth discrete particle hydrodynamic (SDPH) particle is found, then searching for the SDPH particle... Step 4: Calculate the updated parameters of the SPH particles and the updated parameters of the SDPH particles based on the search results; Step 5: Determine whether the SPH particles have been converted into SDPH particles; if not, update the SPH particle parameters using the calculated updated parameters of the SPH particles; if yes, update the SDPH particle parameters using the calculated updated parameters of the SDPH particles; Repeat steps 3 to 5 until a preset time is reached; Step 6: After the above cyclic calculations are completed, visualize the fragment cloud morphology and scale distribution based on the updated SPH particle parameters and the updated SDPH particle parameters.

[0142] Figure 8 This is a block diagram illustrating an apparatus 800 for simulating and calculating a hypersonic collision space debris cloud according to an exemplary embodiment. For example, apparatus 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0143] Reference Figure 8 The device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0144] Processing component 802 typically controls the overall operation of device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0145] Memory 804 is configured to store various types of data to support the operation of device 800. Examples of this data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0146] Power supply component 806 provides power to various components of device 800. Power supply component 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 800.

[0147] Multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0148] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when device 800 is in an operating mode, such as call mode, recording mode, and voice information processing mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0149] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0150] Sensor assembly 814 includes one or more sensors for providing status assessments of various aspects of device 800. For example, sensor assembly 814 can detect the on / off state of device 800, the relative positioning of components such as the display and keypad of device 800, and can also detect changes in the position of device 800 or a component of device 800, the presence or absence of user contact with device 800, the orientation or acceleration / deceleration of device 800, and temperature changes of device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0151] Communication component 816 is configured to facilitate wired or wireless communication between device 800 and other devices. Device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency information processing (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0152] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0153] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of the device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0154] Figure 9 This is a schematic diagram of the server structure in some embodiments of the present invention. The server 1900 can vary considerably depending on its configuration or performance, and may include one or more central processing units (CPUs) 1922 (e.g., one or more processors) and memory 1932, and one or more storage media 1930 (e.g., one or more mass storage devices) for storing application programs 1942 or data 1944. The memory 1932 and storage media 1930 can be temporary or persistent storage. The program stored in the storage media 1930 may include one or more modules (not shown in the diagram), each module including a series of instruction operations on the server. Furthermore, the CPU 1922 may be configured to communicate with the storage media 1930 and execute the series of instruction operations in the storage media 1930 on the server 1900.

[0155] Server 1900 may also include one or more power supplies 1926, one or more wired or wireless network interfaces 1950, one or more input / output interfaces 1958, one or more keyboards 1956, and / or one or more operating systems 1941, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0156] A non-transitory computer-readable storage medium that, when instructions in the storage medium are executed by a processor of a device (server or terminal), enables the device to perform... Figure 1 The simulation calculation method for ultra-high-speed collision space debris clouds is shown.

[0157] A non-transitory computer-readable storage medium, wherein when the instructions in the storage medium are executed by a processor of a device (server or terminal), the device is able to perform the aforementioned... Figure 1 The description of the data processing method in the corresponding embodiments is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program products or computer program embodiments related to this application, please refer to the description of the method embodiments of this application.

[0158] Furthermore, it should be noted that this application also provides a computer program product or computer program, which may include computer instructions, which may be stored in a computer-readable storage medium. The processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor may execute the computer instructions, causing the computer device to perform the aforementioned actions. Figure 1 The description of the data processing method in the corresponding embodiments is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program products or computer program embodiments related to this application, please refer to the description of the method embodiments of this application.

[0159] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0160] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0161] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A simulation calculation method for ultra-high-speed collision space debris clouds, characterized in that, The method is used to simulate the formation and motion of ultra-high-speed collision space debris clouds, and to obtain the morphological and scale distribution of the debris clouds. The method includes: Step 1: Establish a three-dimensional geometric model of the projectile and the target plate, divide the model into meshes, and assign each mesh to a smooth particle hydrodynamic (SPH) particle. Step 2: Read the initial parameters and assign them to the SPH particles; Step 3: Search for particles near the SPH particle. If a smooth discrete particle hydrodynamic SDPH particle is found, then search for particles near the SDPH particle. Step 4: Calculate the update parameters of the SPH particles and the update parameters of the SDPH particles based on the search results; Step 5: Determine whether SPH particles are converted into SDPH particles; if not, update the SPH particle parameters using the calculated update parameters of the SPH particles; if yes, update the SDPH particle parameters using the update parameters of the SDPH particles calculated using the update parameter calculation method of the SDPH particles. The step of determining whether SPH particles are converted into SDPH particles includes: Determine if the damage value of the SPH particles is equal to 1; If the damage value is equal to 1, it is confirmed that the material is completely damaged and forms discrete fragments. Further determination is needed to determine whether the average characteristic size of the fragments is less than the initial size of the SPH. If the size is smaller than the initial size of SPH, then it is confirmed that the SPH particles are converted into SDPH particles. Repeat steps 3 through 5 until the preset time is reached: Step 6: After the above iterative calculations are completed, visualize the morphological distribution and scale distribution of the fragment cloud based on the updated SPH particle parameters and the updated SDPH particle parameters.

2. The method according to claim 1, characterized in that, The initial parameters include: The parameters in the state equation during the projectile impact on the target plate; and Parameters in the constitutive model of a projectile impacting a target plate.

3. The method according to claim 1, characterized in that, The step of calculating the updated parameters of the SPH particles based on the search results includes: If an SDPH particle is found in the vicinity of an SPH particle, the external force exerted by the SDPH particle on the SPH particle is calculated and added to the solution of the momentum conservation equation of the SPH particle. The momentum conservation equation, mass conservation equation, and energy conservation equation are then solved to obtain the updated parameters of the SPH particle.

4. The method according to claim 1 or 3, characterized in that, The updated parameters of the SPH particles include at least: mass, velocity, position, and energy.

5. The method according to claim 1, characterized in that, The step of calculating the updated parameters of the SDPH particles includes: If an SPH particle is found to be near the SDPH particle, the stress in the pseudo-two-body collision between the SPH particle and the SDPH particle is calculated. The stress in the pseudo-two-body collision is then added to the solution of the momentum conservation equation of the SDPH particle. The momentum conservation equation, mass conservation equation, and energy conservation equation are then solved to obtain the updated parameters of the SDPH particle.

6. The method according to claim 1 or 5, characterized in that, The updated parameters of the SDPH particles include at least: mass, velocity, position, and pseudo-temperature.

7. A simulation computing device for ultra-high-speed collision space debris clouds, characterized in that, The device is used to simulate the formation and motion of ultra-high-speed collision space debris clouds, and to obtain the morphological and scale distribution of the debris clouds. The device includes: The model building unit is used to build a three-dimensional geometric model of the projectile and the target plate, and to divide the model into meshes, with each mesh corresponding to a smooth particle hydrodynamic (SPH) particle. A parameter reading unit is used to read initial parameters and assign them to the SPH particles; The neighboring particle search unit is used to search for particles near the SPH particle. If a smooth discrete particle hydrodynamic SDPH particle is found, then the neighboring particles of the SDPH particle are searched. The parameter calculation unit is used to calculate the updated parameters of the SPH particles and the updated parameters of the SDPH particles based on the search results. The judgment and parameter update unit is used to determine whether SPH particles are converted into SDPH particles; if not, the SPH particle parameters are updated using the calculated update parameters of the SPH particles; if so, the SDPH particle parameters are updated using the update parameters of the SDPH particles calculated using the update parameter calculation method of the SDPH particles. The step of determining whether SPH particles are converted into SDPH particles includes: Determine if the damage value of the SPH particles is equal to 1; If the damage value is equal to 1, it is confirmed that the material is completely damaged and forms discrete fragments. Further determination is needed to determine whether the average characteristic size of the fragments is less than the initial size of the SPH. If the size is smaller than the initial size of SPH, then it is confirmed that the SPH particles are converted into SDPH particles. The visualization unit is used to visualize the morphological and scale distribution of the fragment cloud based on the updated SPH and SDPH particle parameters after the calculation is completed.

8. An electronic device, characterized in that, The method includes a processor and a machine-readable storage medium storing machine-executable instructions that can be executed by the processor, the processor being prompted by the machine-executable instructions to perform the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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