A rocket engine jet flow field rapid reconstruction method and system based on similarity criterion mapping

Abstract

This invention discloses a method and system for rapid reconstruction of rocket engine exhaust flow fields based on similarity criterion mapping, belonging to the field of rocket engine technology. Addressing the problems of cumbersome procedures, long computation times, and difficulty in meeting the needs of large-scale operating conditions and rapid prediction in traditional CFD numerical simulations, this invention constructs a standard flow field database containing dimensionless flow fields and key similarity criteria. It obtains target operating condition parameters and calculates the number of similarity criteria, matches them with the database to determine the mapping template, and then rapidly reconstructs the exhaust flow field through similarity transformation. Simultaneously, it employs preset tolerance matching and multi-template collaborative correction to improve accuracy, eliminating the need for repeated iterative solutions. This invention can achieve second-level calculation of exhaust flow fields while ensuring engineering accuracy, significantly improving efficiency and making it suitable for rocket engine exhaust infrared characteristic analysis, engine design optimization, and rapid engineering evaluation under multiple operating conditions.

Description

Technical Field

[0001] This invention belongs to the field of rocket engine technology, and in particular relates to a method and system for rapid reconstruction of rocket engine jet flow field based on similarity criterion mapping. Background Technology

[0002] The rocket engine exhaust is a complex flow formed by the movement and diffusion of high-temperature, high-speed combustion gases ejected from the engine thrust chamber in the external environment. It involves intense chemical reactions, multiphase flow, and turbulent mixing processes, exhibiting strong infrared radiation characteristics. To investigate the influence of propellant formulation, morphological parameters (such as combustion chamber pressure, temperature, and nozzle size) and flight parameters (such as altitude, velocity, and angle of attack) on the infrared radiation characteristics of the exhaust, accurate and reliable exhaust flow field data must first be obtained as the input basis.

[0003] Currently, conventional calculations of jet flow fields typically rely on computational fluid dynamics (CFD) numerical simulations. This process is complex and cumbersome, usually involving: establishing a detailed geometric model, meshing the complex computational domain, defining governing equations and turbulence models, inputting boundary conditions and physical property parameters, configuring the solver and discretization scheme, performing long-term iterative calculations until convergence, and finally post-processing and analyzing the results. This process involves multiple professional steps and is significantly computationally time-consuming. When faced with massive computational needs such as large-scale parameter studies, multi-condition comparisons, or rapid predictions, it is often inefficient and fails to meet the timeliness requirements of engineering design and evaluation.

[0004] This invention analyzes similarity criteria and leverages the consistent dimensionless distribution of the reference flow field and the target jet flow field when geometric, kinematic, and dynamic similarity conditions are met. It establishes a mapping relationship between the existing reference and target flow fields, directly deriving key parameters of the target flow field through similarity transformation, thus avoiding the need for repeated full CFD numerical simulations. This mapping method significantly reduces computational steps, greatly saving computation time and resources, and providing a new technical path for rapid prediction of jet flow fields.

[0005] Therefore, this application aims to propose a rapid reconstruction method for rocket engine jet flow field based on similarity criterion mapping, in order to achieve efficient acquisition of key physical quantities of the jet flow field while ensuring a certain level of accuracy, thereby providing rapid and practical technical support for subsequent infrared radiation characteristic analysis and engine design optimization. Summary of the Invention

[0006] This invention addresses the problems of cumbersome and time-consuming calculation processes for rocket engine exhaust flow fields, which are difficult to adapt to the needs of massive computing tasks. It proposes a rapid reconstruction method for rocket engine exhaust flow fields based on similarity criterion mapping.

[0007] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping, the method comprising the following steps: Step 1: Construct a standard flow field database for rocket engine exhaust; Step 2: Obtain the parameters of the target working condition and calculate its key similarity criterion number; Step 3: Compare the obtained parameters of the target working condition and the number of key similarity criteria with the constructed standard flow field database to determine the mapping template; Step 4: Based on the mapping template, the jet flow field of the target working condition is reconstructed through similarity transformation.

[0008] Furthermore, step one of the present invention specifically includes: By acquiring jet flow field data under various operating conditions and performing dimensionless processing, a standard flow field database for rocket engine jets is constructed. The flow field database includes fuel type and number of key similarity criteria; The number of key similarity criteria includes specific heat ratio. γ ,Mach number Ma Mass fraction of main components Y i Pressure ratio NPR speed ratio NVR.

[0009] Furthermore, step two of the present invention specifically includes: For the target engine, determine the fuel type, collect data on nozzle outlet diameter, pressure, temperature, density, velocity, component mass fraction, and incoming flow parameters, and calculate the number of key similarity criteria corresponding to the target operating condition.

[0010] Furthermore, step three of the present invention specifically includes: The target operating condition's fuel type and key similarity criteria number are compared with a standard database. A standard flow field with the same fuel type and the closest key criteria number is selected as the mapping template through a preset tolerance range.

[0011] Furthermore, for target working conditions where the matching degree is outside the preset tolerance range, the present invention introduces a multi-template collaborative correction mechanism to further improve the reconstruction accuracy.

[0012] Furthermore, the preset tolerance range described in this invention is: specific heat ratio γ Error <1%, Mach number Ma Error <1%, pressure ratio NPR Error <2%, speed ratio NVR Error <2%.

[0013] Furthermore, step four of the present invention specifically includes: Geometric scale restoration: Multiply the standard flow field scale by the target engine nozzle diameter to obtain the true flow field size; Physical parameter reconstruction: The standard temperature field, density field, and velocity field are multiplied by the nozzle exit static temperature, density, and velocity, respectively; the component mass fraction field is adjusted according to the proportion of the exit components, and the target flow field is finally reconstructed quickly.

[0014] Based on the same inventive concept, the rapid reconstruction method of rocket engine exhaust flow field based on similarity criterion mapping described in this invention can be entirely implemented using computer software. Therefore, correspondingly, this invention also provides a rapid reconstruction system of rocket engine exhaust flow field based on similarity criterion mapping.

[0015] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the aforementioned method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping.

[0016] Furthermore, the present invention also provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping described above.

[0017] The beneficial effects of this invention are as follows: 1. Significantly improved computational efficiency: This invention completely avoids the enormous time-consuming process of mesh generation and iterative solution of complex Navier-Stokes equations for each calculation. Through database matching and similarity mapping, this invention can obtain a jet flow field that meets engineering accuracy requirements within seconds or even milliseconds, improving efficiency by several orders of magnitude.

[0018] 2. Greatly adaptable to massive computing needs, this invention is particularly suitable for tasks such as overall optimization design, sensitivity analysis, and uncertainty quantification analysis that require tens of thousands of flow field calculations, solving the bottleneck problem of unbearable computing resources in traditional CFD methods in such scenarios.

[0019] 3. It maintains a clear physical mechanism basis. This invention is rooted in the similarity criteria of fluid mechanics. The simplification process has a clear physical basis, ensuring the physical rationality and reliability of the rapid reconstruction results, rather than pure black-box data fitting.

[0020] 4. Strong engineering applicability: This invention constructs a standard flow field set, transforming high-fidelity CFD or experimental data into knowledge and modular data, forming reusable assets. As the database continues to be enriched and expanded, the applicability and accuracy of the method can be continuously enhanced.

[0021] 5. Flexible implementation: The standard flow field set constructed by this invention can be expanded and optimized by continuously supplementing new high-precision calculation or experimental data, so that the method can adapt to the development of new propellants and new engine configurations. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping, as described in this invention. Figure 2 This is a schematic diagram comparing the CFD simulation results of the exhaust flame temperature field of a certain type of rocket engine described in this invention with the calculation results of this invention. Figure 3 This is a schematic diagram comparing the CFD simulation results of the exhaust flame density field of a certain type of rocket engine described in this invention with the calculation results of this invention. Figure 4 This is a schematic diagram comparing the CFD simulation results of the exhaust velocity field of a certain type of rocket engine described in this invention with the calculation results of this invention. Figure 5 This is a schematic diagram comparing the CFD simulation results of the CO2 mass fraction field of a certain type of rocket engine exhaust with the calculation results of this invention. Figure 6 This is a schematic diagram comparing the CFD simulation results of the H2O mass fraction field of a certain type of rocket engine exhaust with the calculation results of this invention. Detailed Implementation

[0024] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

[0025] Example 1: This example addresses the problem that existing rocket engine exhaust flow field calculation processes are cumbersome, time-consuming, and difficult to adapt to the needs of massive computing tasks. It proposes a rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping.

[0026] The method includes the following steps: Step 1: Construct a standard flow field database for rocket engine exhaust; Step 2: Obtain the parameters of the target working condition and calculate its key similarity criterion number; Step 3: Compare the obtained parameters of the target working condition and the number of key similarity criteria with the constructed standard flow field database to determine the mapping template; Step 4: Based on the mapping template, the jet flow field of the target working condition is reconstructed through similarity transformation.

[0027] Furthermore, in this embodiment, each of the above steps is described in detail; Step 1: Construct a standard flow field database for rocket engine exhaust. Obtain exhaust flow field data (temperature, density, velocity, component distribution, etc.) under various operating conditions through high-precision CFD simulations or experiments, and perform dimensionless processing. The database needs to record fuel type and the number of key similarity criteria (specific heat ratio). γ ,Mach number Ma Mass fraction of main components Y i Pressure ratio NPR speed ratio NVR This forms a reusable standard dataset.

[0028] Step two: Obtain the parameters of the target operating condition and calculate its key similarity criterion number. This involves data acquisition and dimensionless conversion of the target operating condition; for the target engine, determine the fuel type, collect nozzle outlet diameter, pressure, temperature, density, velocity, component mass fraction, and incoming flow parameters, and calculate the key similarity criterion number corresponding to the target operating condition.

[0029] Step 3: Compare the acquired parameters and key similarity criteria of the target operating condition with the constructed standard flow field database to determine the mapping template. Standard flow field matching and filtering: Compare the fuel type and key similarity criteria of the target operating condition with the standard database, and select the appropriate template based on a preset tolerance range (specific heat ratio). γ Error <1%, Mach number Ma Error <1%, pressure ratio NPR Error <2%, speed ratio NVR With an error of <2%, standard flow fields with the same fuel type and the closest number of key criteria are selected as mapping "templates". For target operating conditions where the matching degree is outside the preset tolerance range, a multi-template collaborative correction mechanism is introduced to further improve the reconstruction accuracy.

[0030] Step four: Based on the mapping template, reconstruct the jet flow field of the target operating condition through similarity transformation. Rapid flow field reconstruction based on similarity criterion mapping includes: Geometric scale restoration: Multiply the standard flow field scale by the target engine nozzle diameter to obtain the true flow field size; Physical parameter reconstruction: The standard temperature field, density field, and velocity field are multiplied by the nozzle exit static temperature, density, and velocity, respectively, to restore the parameters; the component mass fraction field is adjusted according to the proportion of the exit components. Finally, the target flow field is rapidly reconstructed.

[0031] In this embodiment, the jet flow field is reconstructed based on the principle of similarity: when the reference flow field and the target jet flow field satisfy geometric, kinematic, and dynamic similarity conditions, they have a consistent distribution pattern in dimensionless form. Based on this pattern, this invention establishes a correspondence between the reference flow field and the target working condition flow field, and directly obtains the key physical parameters of the target flow field using similarity transformation. This eliminates the need to repeatedly perform complete CFD numerical simulations for each working condition, effectively simplifying the calculation process, reducing calculation time, and providing a way to quickly obtain the jet flow field.

[0032] The following is combined Figure 1 This embodiment provides an overall description of a method for rapid reconstruction of rocket engine jet flow field based on similarity criterion mapping. like Figure 1 As shown, the method includes the following steps: Step 1: Construct a standard flow field database for rocket engine exhaust. Through high-precision computational fluid dynamics (CFD) numerical simulations or rigorous ground / high-altitude bench experiments, systematically acquire fundamental data on exhaust flow fields covering various typical operating conditions. Specifically, extensive flow field solutions and data acquisition are required for different fuel types (e.g., liquid hydrogen / liquid oxygen, kerosene / liquid oxygen), different engine profile parameters (e.g., combustion chamber pressure, temperature, nozzle size), and different flight conditions (covering multiple characteristic states from ground stationary to high-altitude high-speed). The acquired flow field information must comprehensively include detailed temperature, density, velocity, and mass fraction distribution fields of each chemical component in the exhaust region. All acquired flow field data must undergo dimensionless standardization. Simultaneously, for each calculation or experimental condition, the key similarity criteria number at the nozzle exit must be accurately extracted and recorded, primarily including: specific heat ratio. γ ,Mach number Ma Each major component (such as H2O, CO) 2、 Mass fraction of H2, CO, etc. Y i and pressure ratio NPR Ratio to speed NVR Dimensionless numbers, etc. Finally, all the above information is integrated to form a standard dataset. This dataset not only contains a large amount of standardized flow field information but also the fuel type under this condition and the set of all relevant key similarity criteria. The flow field parameter standardization method is as follows: Flow field scale standardization: Temperature field normalization: Density field normalization: Speed ​​standardization: In this context, the upper horizontal line represents a standardized physical quantity, and the subscript 0 represents a physical quantity of the nozzle exit section.

[0033] Step two: Data acquisition and dimensionless conversion for the target operating condition. For a target rocket engine that requires rapid reconstruction of the jet flow field, first, its fuel type is determined. Second, the nozzle exit diameter, pressure, temperature, density, velocity, mass fraction of each major component, and incoming flow pressure and velocity of the rocket engine are collected. Finally, based on these parameters, the set of key similarity criteria corresponding to the target operating condition is calculated.

[0034] Step 3, Standard Flow Field Matching and Screening. The fuel type and similarity criterion set for the target operating condition obtained in Step 2 are compared with the standard flow field database constructed in Step 1. A reasonable tolerance range (specific heat ratio) is set. γ Error <1%, Mach number Ma Error <1%, pressure ratio NPR Error <2%, speed ratio NVR (With an error <2%), a standard flow field with the same fuel type and the closest number of key similarity criteria is selected from the database as the "template" for subsequent mapping. When the number of similarity criteria for the target condition cannot be matched within the tolerance range with a single standard template in the database, several neighboring standard flow fields that are closest to the target condition will be automatically retrieved from the database. These standard flow fields each have different parametric distances from the target condition. Based on the distance, the contribution factor of each neighboring flow field is calculated using a specific weighting algorithm. Subsequently, the contribution factors of each standard flow field are weighted and fused to generate a correction compensation amount for the current non-ideal condition, thereby improving the simulation accuracy and applicability under the target condition.

[0035] Step four: Rapid flow field reconstruction based on similarity criteria. This step "scales" the standard template flow field to the actual flow field of the target operating condition. First, the physical scale of the jet flow field is determined by multiplying the standard flow field scale obtained in the previous step by the actual nozzle diameter of the current engine, thus obtaining the flow field size corresponding to the actual geometry. Next, the physical parameter fields of the flow field are reconstructed. The temperature field, density field, and velocity field of the jet are generated by mapping the standard temperature field, standard density field, and standard velocity field obtained in the previous step, respectively. Specifically, the standard temperature field needs to be multiplied by the static temperature at the engine nozzle exit section for restoration; the standard density field needs to be multiplied by the medium density at the nozzle exit section; the standard velocity field needs to be multiplied by the velocity at the nozzle exit section; and the mass fraction fields of each component are adjusted proportionally according to the component fraction at the exit.

[0036] Example 2, Combination Figures 2 to 6This embodiment will be described in detail. To verify the accuracy and efficiency of the rapid reconstruction method (RFFC) for rocket engine exhaust flow field based on similarity criterion mapping described in this invention, the exhaust flow field results obtained by traditional CFD numerical simulation methods and the method of this invention will be compared and analyzed.

[0037] Figures 2 to 6 The diagrams show a comparison of results from existing computational methods (CFD-based numerical simulation) and the rapid reconstruction method of this invention (RFFC) on key physical quantities in rocket engine exhaust. The diagrams clearly show that the computational results of this invention and the high-precision CFD simulation results exhibit a high degree of agreement in both spatial distribution and numerical values ​​for the temperature, density, velocity, and component concentration fields of the exhaust. This verifies that the method of this invention has good consistency with existing high-reliability methods in terms of computational accuracy and can accurately and reliably reproduce the complex multiphysics distribution details of rocket engine exhaust.

[0038] Comparative experimental data show that for the same jet flow field calculation task, the existing method takes approximately one hour to complete the simulation, while the calculation time of the present invention is only in the seconds. Quantitative calculations show that the present invention achieves a computational speedup of up to 3.6 × 10⁻⁶ compared to the existing method. 3 This significant efficiency improvement means that the present invention can obtain high-precision jet flow field data in a very short time, thereby greatly improving the computational efficiency of rocket engine design, analysis, and performance evaluation, and providing strong technical support for real-time or near-real-time engineering applications.

[0039] In summary, the rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping described in this invention has the following innovative features: First, computational efficiency is significantly improved, completely avoiding the enormous time-consuming process of mesh generation and iterative solution of complex Navier-Stokes equations for each calculation. Through database matching and similarity mapping, a jet flow field that meets engineering accuracy requirements can be obtained within seconds or even milliseconds, resulting in an efficiency improvement of several orders of magnitude.

[0040] Secondly, it is highly adaptable to massive computing demands, and is particularly suitable for tasks such as overall optimization design, sensitivity analysis, and uncertainty quantification analysis that require tens of thousands of flow field calculations. It solves the bottleneck problem of unbearable computing resources in such scenarios by traditional CFD methods.

[0041] Third, it maintains a clear physical mechanism basis. This method is rooted in the similarity criterion of fluid mechanics, and the simplification process has a clear physical basis, ensuring the physical rationality and reliability of the rapid reconstruction results, rather than pure black box data fitting.

[0042] Fourth, it has strong engineering practicality. By constructing standard flow field sets, high-fidelity CFD or experimental data can be knowledge-based and modularized to form reusable assets. As the database continues to be enriched and expanded, the applicability and accuracy of the method can be continuously enhanced.

[0043] Fifth, it is flexible in implementation. The standard flow field set can be expanded and optimized by continuously supplementing new high-precision calculation or experimental data, so that the method can adapt to the development of new propellants and new engine configurations.

[0044] Example 3: The rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping described above can be entirely implemented using computer software. Therefore, this example provides a rapid reconstruction system for rocket engine exhaust flow field based on similarity criterion mapping.

[0045] Example 4: This example provides a computer-readable storage medium storing a computer program. When the computer program is run by a processor, it executes the rapid reconstruction method for rocket engine jet flow field based on similarity criterion mapping described above.

[0046] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be accomplished by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0047] Example 5: This example provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping described above.

[0048] This embodiment provides a computer device. This part of the hardware device is a general model and is not shown in the figure. The system includes a processor and a memory, which can be connected by a bus or other means. The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, as well as corresponding program instructions / modules. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions and modules stored in the memory, so as to realize the rapid reconstruction method of rocket engine exhaust flow field based on similarity criterion mapping described above.

[0049] The memory may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, mobile communication networks, and combinations thereof.

[0050] One or more modules are stored in the memory. When the processor executes, it performs the method steps in the embodiments. In this way, the inventive purpose of the present invention can be achieved through the method, apparatus and process of the present invention. The specific details of the above-mentioned computer device can be understood by referring to the relevant descriptions and effects in the embodiments, and will not be repeated here.

[0051] The above description of the technical solution provided by the present invention through several specific embodiments is intended to highlight the advantages and benefits of the technical solution provided by the present invention. However, the above-described specific embodiments are not intended to limit the present invention. Any reasonable modifications and improvements to the present invention, reasonable combinations of implementation methods and equivalent substitutions based on the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping, characterized in that, The methods include: Step 1: Construct a standard flow field database for rocket engine exhaust; Step 2: Obtain the parameters of the target working condition and calculate its key similarity criterion number; Step 3: Compare the obtained parameters of the target working condition and the number of key similarity criteria with the constructed standard flow field database to determine the mapping template; Step 4: Based on the mapping template, the jet flow field of the target working condition is reconstructed through similarity transformation.

2. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 1, characterized in that, Step one specifically includes: By acquiring jet flow field data under various operating conditions and performing dimensionless processing, a standard flow field database for rocket engine jets is constructed. The flow field database includes fuel type and number of key similarity criteria; The number of key similarity criteria includes specific heat ratio. γ ,Mach number Ma Mass fraction of main components Y i Pressure ratio NPR speed ratio NVR .

3. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 1, characterized in that, Step two specifically includes: For the target engine, determine the fuel type, collect data on nozzle outlet diameter, pressure, temperature, density, velocity, component mass fraction, and incoming flow parameters, and calculate the number of key similarity criteria corresponding to the target operating condition.

4. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 3, characterized in that, Step three specifically includes: The target operating condition's fuel type and key similarity criteria number are compared with a standard database. A standard flow field with the same fuel type and the closest key criteria number is selected as the mapping template through a preset tolerance range.

5. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 4, characterized in that, For target working conditions where the matching degree is outside the preset tolerance range, a multi-template collaborative correction mechanism is introduced to further improve the reconstruction accuracy.

6. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 4, characterized in that, The preset tolerance range is: specific heat ratio γ Error <1%, Mach number Ma Error <1%, pressure ratio NPR Error <2%, speed ratio NVR Error <2%.

7. The method for rapid reconstruction of rocket engine exhaust flow field based on similarity criterion mapping according to claim 4, characterized in that, Step four specifically includes: Geometric scale restoration: Multiply the standard flow field scale by the target engine nozzle diameter to obtain the true flow field size; Physical parameter reconstruction: The standard temperature field, density field, and velocity field are multiplied by the nozzle exit static temperature, density, and velocity, respectively; the component mass fraction field is adjusted according to the proportion of the exit components, and the target flow field is finally reconstructed quickly.

8. A rapid reconstruction system for the jet flow field of a rocket engine based on similarity criterion mapping, characterized in that, The system is implemented using a rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs a method for rapid reconstruction of the rocket engine exhaust flow field based on similarity criterion mapping as described in any one of claims 1-7.

10. A computer device, characterized in that, The device includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a rapid reconstruction method for rocket engine exhaust flow field based on similarity criterion mapping as described in any one of claims 1-7.

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