Numerical simulation parallel computing method, device and medium for two-phase wall turbulent flow of ablation particles

Abstract

The application relates to the technical field of aircrafts, and discloses an ablative particle two-phase wall turbulent flow numerical simulation parallel computing method, equipment and medium, the method comprising the following steps: in each sub-time step, calling a fluid solver to calculate flow field information; using a dynamic array to read particle information from a dynamic linked list array one by one; calling a single particle solver to update the particle information read by the dynamic array, and updating the updated particle information to the dynamic linked list array one by one; after traversing all the particles in the dynamic linked list array, entering the next sub-time step, until the time loop is completed, and outputting all the information of the flow field and the particles. In this way, the direct numerical simulation of compressible ablative particle two-phase flow can be accurately realized, the problem that the prior art does not have the direct numerical simulation of compressible particle two-phase flow at all is solved, and the blank of the direct numerical simulation of compressible ablative particle two-phase flow in China is filled.

Description

Technical Field

[0001] This invention relates to the field of aircraft technology, and in particular to a parallel computing method, equipment and medium for numerical simulation of turbulent two-phase wall ablation of particles. Background Technology

[0002] High-speed aircraft are crucial national assets with a wide range of applications. During reentry, the aircraft's nose is heated by high temperatures at stagnation points, generating ablation particles. These particles, under aerodynamic stripping, enter the downstream boundary layer. The interaction between these ablation particles and the compressible boundary layer alters its dynamics and thermodynamic processes. This makes traditional single-phase flow-based compressible fluid dynamics solvers inaccurate numerical simulations of the physical processes in the two-phase flow boundary layer containing compressible particles, leading to design redundancy and lower effective payloads in the aircraft.

[0003] Aerospace technology involves numerous scientific problems related to particulate two-phase flow. However, aerospace engineering problems often occur under extreme mechanical conditions, making it impossible for ground-based wind tunnels to reproduce the actual physical processes at high altitudes. Furthermore, flight tests cannot provide detailed local information. Therefore, numerical wind tunnel experiments and tests are needed to obtain accurate physical field information of the ablated particle turbulent boundary layer, enabling precise direct numerical simulation and measurement. However, direct numerical simulation of compressible particulate two-phase flow problems remains currently impossible. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a parallel computational method, device, and medium for numerical simulation of two-phase flow turbulence in ablation particles, which can accurately realize direct numerical simulation of compressible ablation particle two-phase flow. The specific solution is as follows:

[0005] A parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls includes:

[0006] Within each sub-time step, the fluid solver is invoked to calculate the flow field information;

[0007] Particle information is read one by one from a dynamic linked list array using a dynamic array;

[0008] The single-particle solver is invoked to update the particle information read from the dynamic array, and the updated particle information is then updated one by one to the dynamic linked list array.

[0009] After traversing all the particles in the dynamic linked list array, proceed to the next sub-time step until the time loop is completed, and output all information about the flow field and particles.

[0010] Preferably, in the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, after updating the updated particle information to the dynamic linked list array one by one, the method further includes:

[0011] MPI communication is used to exchange particle entry and exit information between different parallel blocks.

[0012] Preferably, in the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, MPI communication is used to exchange particle entry and exit information between different parallel blocks, including:

[0013] During the particle initialization phase, the numbers of the 26 adjacent MPI parallel blocks of each MPI block are defined;

[0014] During the communication phase, the target MPI block traverses 26 adjacent parallel MPI blocks and determines whether to send or receive data to the granules based on set conditions.

[0015] Preferably, in the parallel computational method for numerical simulation of two-phase wall turbulence of ablation particles provided in the embodiments of the present invention, before calling the fluid solver to calculate the flow field information, the method further includes:

[0016] Initialize the dynamic linked list array and allocate granular memory.

[0017] Preferably, in the parallel calculation method for numerical simulation of two-phase wall turbulence of ablation particles provided in the embodiments of the present invention, the flow field information is calculated using the following formula:

[0018]

[0019]

[0020]

[0021] Where ρ is the fluid density, T is the fluid temperature, and Einstein tensor representation is used. k and u l Both are fluid velocity vectors, x k and x l All are coordinate vectors, with subscripts k and l being Einstein dummy scales, t representing time, p representing fluid pressure, and σ representing... kl It is the fluid stress tensor, E is the fluid enthalpy, λ is the fluid thermal conductivity, and ρ is the fluid stress tensor. p It is particle density, C p,p It is the specific heat capacity of particles, τ p It is the particle inertial relaxation coefficient, τ p,convec It is the particle thermal response coefficient, V k It is the particle velocity vector, T p It is the particle temperature, N p,cell is the number of particles, and j is the particle ordinal number.

[0022] Preferably, in the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, calling the single-particle solver to update the particle information read from the dynamic array includes:

[0023] By using third-order Runge-Kutta time progression, the particle displacement vector, particle velocity vector, and particle temperature of particle dynamics and thermodynamics are updated.

[0024] Preferably, in the parallel calculation method for numerical simulation of two-phase wall turbulence of ablation particles provided in the embodiments of the present invention, the particle information is updated using the following formula:

[0025]

[0026]

[0027]

[0028] Among them, X j It is the particle coordinate vector, V j It is a fluid coordinate vector, using non-Einstein tensor representation, where u is the fluid vector and T is the fluid vector. p,j It is the temperature of the j-th particle in the particle swarm, where j ranges from 1 to N. p,cell .

[0029] Preferably, in the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, before initializing the dynamic linked list array and allocating particle memory, the method further includes:

[0030] Initialize the particle preprocessing module, defining all necessary dispersed particle phase information, dynamic arrays, and dynamic linked list arrays.

[0031] This invention also provides an electronic device, including a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence as described above in this invention.

[0032] This invention also provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence as described in this invention.

[0033] As can be seen from the above technical solution, the parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence provided by the present invention includes: in each sub-time step, calling the fluid solver to calculate the flow field information; using a dynamic array to read particle information one by one from the dynamic linked list array; calling the single particle solver to update the particle information read from the dynamic array, and updating the updated particle information one by one to the dynamic linked list array; after traversing all particles in the dynamic linked list array, entering the next sub-time step, until the time loop is completed, and outputting all information of the flow field and particles.

[0034] The parallel computational method for numerical simulation of ablation particle two-phase wall turbulence provided by this invention iterates through all particles in each sub-time step. In each iteration, a dynamic array is used to read information about one particle from a dynamic linked list array, followed by calculation using a single-particle solver to update the particle information in the dynamic array. This process is repeated until all particle information is updated, completing one sub-time step. After the time loop is complete, all information about the two phases of the particle flow is output. This method accurately achieves direct numerical simulation of compressible ablation particle two-phase flow, solving the problem that existing technologies completely lack the capability for direct numerical simulation of compressible particle two-phase flow.

[0035] Furthermore, this invention also provides corresponding equipment and computer-readable storage media for the parallel computation method of numerical simulation of turbulence in two-phase walls of ablation particles, further making the above method more practical. The equipment and computer-readable storage media have corresponding advantages. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0037] Figure 1 A flowchart of a parallel computational method for numerical simulation of turbulence in ablation-particle two-phase wall provided in an embodiment of the present invention;

[0038] Figure 2 This is a flowchart illustrating the parallel computational method for numerical simulation of turbulent two-phase wall ablation of particles provided in an embodiment of the present invention.

[0039] Figure 3 A schematic diagram illustrating memory allocation for a dynamic linked list array provided in an embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram of parallel communication using a dynamic linked list provided in an embodiment of the present invention.

[0041] Figure 5 This is a schematic diagram illustrating the interaction data between the linked list array particle swarm and the single particle solver provided in an embodiment of the present invention.

[0042] Figure 6 This is a schematic diagram of the calculation process of the single-particle solver provided in an embodiment of the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] This invention provides a parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls, such as... Figure 1 As shown, it includes the following steps:

[0045] S101. Within each sub-time step, call the fluid solver to calculate the flow field information;

[0046] S102. Use a dynamic array to read particle information one by one from a dynamic linked list array;

[0047] S103. Call the single-particle solver to update the particle information read from the dynamic array, and update the updated particle information to the dynamic linked list array one by one.

[0048] It should be noted that, as Figure 2 As shown, steps S102 and S103 can be internal operations of the particle solver. At each sub-time step, the fluid solver and particle solver are called sequentially. Inside the particle solver module, information about the particle group is read one by one from the dynamic linked list array using a dynamic array data structure. That is, one particle is read at a time, then the single-particle solver is called to update the particle information, and then the updated particle information is updated one by one to the dynamic linked list array.

[0049] S104. After traversing all particles in the dynamic linked list array, proceed to the next sub-time step until the time loop is completed, and output all information about the flow field and particles.

[0050] In the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, all particles are traversed and looped within each sub-time step. In each loop, the information of a particle is read from the dynamic linked list array using a dynamic array, and then the single-particle solver is called to calculate it, updating the particle information in the dynamic array. Then, the dynamic array is used to update the particle information in the dynamic linked list array. This process is repeated until all particle information is updated, thus completing the calculation of one sub-time step. When the time loop is completed, all information of the two phases of the particles is output. This method can accurately realize direct numerical simulation of compressible ablation particle two-phase flow, solving the problem that the prior art is completely unable to directly numerically simulate compressible particle two-phase flow.

[0051] Furthermore, in a specific implementation, in the above-mentioned parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, before executing step S101 to call the fluid solver to calculate the flow field information, it may also include: initializing the dynamic linked list array and allocating particle memory.

[0052] Figure 3 The technical details of allocating memory for dispersed particle swarms using dynamic linked list arrays are presented. Generally, large-scale parallel computation of fluid solvers is based on the Eulerian coordinate system, meaning memory allocation is pre-defined before computation. However, dispersed particle phases are based on the Lagrangian coordinate system, meaning memory allocated by the fluid solver cannot be directly used for dispersed particle swarms. This is because particles move, and the number of particles in each MPI block changes over time. Therefore, the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in this embodiment of the invention employs dynamic linked list array technology to dynamically allocate memory for the dispersed particle phase, such as... Figure 3 As shown.

[0053] Furthermore, in a specific implementation, in the above-mentioned parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, before initializing the dynamic linked list array and allocating particle memory, it may also include: initializing the particle preprocessing module, defining all the required dispersed particle phase information, dynamic array and dynamic linked list array.

[0054] Specifically, first, when the program starts, the particle preprocessing module is initialized, defining all necessary dispersed particle phase information, dynamic arrays, and dynamic linked list arrays. Second, the program reads relevant parameters from the user interface and initializes program variables and dynamic arrays. Afterward, the dynamic linked list array is initialized and particle memory is allocated.

[0055] Furthermore, in a specific implementation, in the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided in the embodiments of the present invention, after executing step S103 to update the updated particle information to the dynamic linked list array one by one, it may further include: exchanging particle entry and exit information between different parallel blocks using MPI communication. In the present invention, the dispersed particle group exchanges information between different blocks of the dispersed particle group through standard parallel MPI statements, without the need for separate allocation of buffer memory, greatly reducing the number of complex program statements in the communication module.

[0056] Specifically, the above steps use MPI communication to exchange particle entry and exit information between different parallel blocks. Specifically, it may include: in the particle initialization stage, defining the numbers of the 26 adjacent MPI parallel blocks of each MPI block; in the communication stage, the target MPI block traverses the 26 adjacent MPI parallel blocks and determines whether to perform sending and receiving operations on the particle by setting conditions.

[0057] Figure 4 The technical details of the dynamic linked list parallel communication scheme are presented. First, during the granular initialization phase, the numbers of the 26 adjacent MPI parallel blocks for each MPI block are predefined; subsequently, during the communication phase, the target MPI block (e.g., ...) is... Figure 4 The middle block is traversed through 26 adjacent MPI parallel blocks, and a conditional judgment is made to determine whether to perform send and receive operations on the particle.

[0058] Figure 5 The technical details and steps for data interaction between a particle swarm with a dynamic linked list array and a single-particle solver are presented. Within each sub-time step, all particles are iterated. In each iteration, the dynamic array is used to read all the kinetic and thermodynamic information of a single particle from the dynamic linked list array. Then, the single-particle solver is called to calculate this information, updating the particle information in the dynamic array. This process is repeated until all particles are updated, completing one sub-time step.

[0059] Furthermore, in specific implementation, in the parallel calculation method for numerical simulation of two-phase wall turbulence of ablation particles provided in the embodiments of the present invention, the following formula is used to calculate the flow field information:

[0060]

[0061] Where ρ is the fluid density, T is the fluid temperature, and Einstein tensor representation is used. k and u l Both are fluid velocity vectors, x k and x lAll are coordinate vectors, with subscripts k and l being Einstein dummy scales, t representing time, p representing fluid pressure, and σ representing... kl It is the fluid stress tensor, E is the fluid enthalpy, λ is the fluid thermal conductivity, and ρ is the fluid stress tensor. p It is particle density, C p,p It is the specific heat capacity of particles, τ p It is the particle inertial relaxation coefficient, τ p,convec It is the particle thermal response coefficient, V k It is the particle velocity vector, T p It is the particle temperature, N p,cell is the number of particles, and j is the particle ordinal number.

[0062] It should be noted that the particles are dragged by the fluid and move randomly in the flow field with the turbulence; at the same time, the particles feed back interphase drag. Momentum equation for fluid; work done by interphase drag feedback The energy equations for heat transfer between phases to the fluid are altered, thus changing the dynamics and thermodynamic processes of the boundary layer. This is distinctly different from single-phase compressible boundary layer flow. Therefore, numerical simulation of engineering problems involving compressible boundary layers with ablation particles requires the parallel computational method for numerical simulation of two-phase wall turbulence with ablation particles provided in the embodiments of this invention.

[0063] In a specific implementation, in the parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence provided in the above embodiment of the present invention, step S103 calls the single particle solver to update the particle information read from the dynamic array, which may specifically include: using third-order Runge-Kutta time advancement to update the particle displacement vector, particle velocity vector and particle temperature of particle dynamics and thermodynamics.

[0064] In specific implementation, in the parallel calculation method for numerical simulation of two-phase wall turbulence of ablation particles provided in the above embodiments of the present invention, the particle information is updated using the following formula:

[0065]

[0066] Among them, X j It is the particle coordinate vector, V j It is the particle velocity vector, using non-Einstein tensor representation, where u is the fluid vector, and T is the particle velocity vector. p,j It is the temperature of the j-th particle in the particle swarm, where j ranges from 1 to N. p,cell .

[0067] It is important to emphasize that the expressions for interphase drag and interphase heat transfer in equation (2) must reflect compressibility effects, and are entirely different from the particle flow under incompressible conditions. The inertial relaxation coefficient under compressible conditions is τ. p =f(St,Re) p Map ), compare τ in the incompressible case p =f(St,Re) p The thermal response relaxation coefficient under compressible conditions is τ. p =f(Re,Ma,Re) p Ma p ,Pr), compared to the incompressible case τ p =f(Re,Re) p ,Pr), where St is the particle inertia coefficient, Re p It is the particle slip Reynolds number, Ma p is the particle slip Mach number, Re is the fluid Reynolds number, Ma is the fluid Mach number, and Pr is the Prandtl number.

[0068] Figure 6 The technical details and steps of the single-particle solver are given. First, the dynamic array obtains the information of a single particle from the linked list array and then enters the single-particle solver module; then the right-hand side of particle dynamics and thermodynamics is calculated, that is, the right-hand side of equation (2); finally, the numerical ordinary differential equation technique Runge-Kutta 3rd order time advance is used to calculate the particle displacement vector, particle velocity vector and particle temperature of particle dynamics and thermodynamics, that is, the left-hand side of equation (2).

[0069] Accordingly, this invention also discloses an electronic device, including a processor and a memory; wherein, when the processor executes the computer program stored in the memory, it implements the parallel calculation method for numerical simulation of ablation particle two-phase wall turbulence disclosed in the foregoing embodiments.

[0070] For more detailed information on the above methods, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0071] Furthermore, the present invention also discloses a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, it implements the aforementioned parallel computation method for numerical simulation of turbulent flow in ablation particles two-phase walls.

[0072] For more detailed information on the above methods, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0073] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the devices and storage media disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0074] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0075] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0076] In summary, the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence provided by this invention includes: calculating flow field information by calling a fluid solver in each sub-time step; reading particle information one by one from a dynamic linked list array using a dynamic array; updating the particle information read from the dynamic array by calling a single-particle solver, and updating the updated particle information to the dynamic linked list array one by one; after traversing all particles in the dynamic linked list array, proceeding to the next sub-time step until the time loop is completed, and outputting all information of the flow field and particles. This can accurately realize direct numerical simulation of compressible ablation particle two-phase flow, solving the problem that existing technologies completely lack the capability for direct numerical simulation of compressible particle two-phase flow. Furthermore, this invention also provides corresponding equipment and computer-readable storage media for the parallel computation method of numerical simulation of ablation particle two-phase wall turbulence, further enhancing the practicality of the above method. The equipment and computer-readable storage media have corresponding advantages.

[0077] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0078] The foregoing has provided a detailed description of the parallel calculation method, equipment, and medium for numerical simulation of ablation particle two-phase wall turbulence provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls, characterized in that, include: Within each sub-time step, the fluid solver is invoked to calculate the flow field information using the following formula: ； in, It is fluid density. It refers to fluid temperature, expressed using Einstein's tensor notation. and Both are fluid velocity vectors. and All are coordinate vectors, with subscripts. k and l It's Einstein's silo. It is time. It is fluid pressure. It is the fluid stress tensor. It is fluid enthalpy. It is the thermal conductivity of the fluid. It is particle density. It is the specific heat capacity of particles. It is the particle inertial relaxation coefficient. It is the particle thermal response coefficient. It is the particle velocity vector. It is the particle temperature. It refers to the number of particles. It is the particle number; Particle information is read one by one from a dynamic linked list array using a dynamic array; The single-particle solver is invoked to update the particle information read from the dynamic array using the following formula: ； in, It is a particle coordinate vector. It is a fluid coordinate vector, represented using a non-Einstein tensor notation. It is a fluid vector. It is the first in the particle group j The temperature of each particle j The value ranges from 1 to ; The updated particle information is then updated one by one in the dynamic linked list array; After traversing all the particles in the dynamic linked list array, proceed to the next sub-time step until the time loop is completed, and output all information about the flow field and particles.

2. The parallel computational method for numerical simulation of ablation particle two-phase wall turbulence according to claim 1, characterized in that, After updating the updated particle information to the dynamic linked list array one by one, the process also includes: MPI communication is used to exchange particle entry and exit information between different parallel blocks.

3. The parallel computational method for numerical simulation of ablation particle two-phase wall turbulence according to claim 2, characterized in that, MPI communication is used to exchange granular input / output information between different parallel blocks, including: During the particle initialization phase, the numbers of the 26 adjacent MPI parallel blocks of each MPI block are defined; During the communication phase, the target MPI block traverses 26 adjacent parallel MPI blocks and determines whether to send or receive data to the granules based on set conditions.

4. The parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls according to claim 3, characterized in that, Before calling the fluid solver to calculate the flow field information, the following steps are also included: Initialize the dynamic linked list array and allocate granular memory.

5. The parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls according to claim 4, characterized in that, Invoking the single-particle solver to update the particle information read from the dynamic array includes: By using third-order Runge-Kutta time progression, the particle displacement vector, particle velocity vector, and particle temperature of particle dynamics and thermodynamics are updated.

6. The parallel computational method for numerical simulation of turbulent flow in ablation-particle two-phase walls according to claim 4, characterized in that, Before initializing the dynamic linked list array and allocating granular memory, the following steps are also included: Initialize the particle preprocessing module, defining all necessary dispersed particle phase information, dynamic arrays, and dynamic linked list arrays.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the parallel computation method for numerical simulation of ablation particle two-phase wall turbulence as described in any one of claims 1 to 6.

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