A method and system for predicting the asynchronous outflow interference of a parallel connection of vehicles

Abstract

The application discloses a kind of navigation body parallel asynchronous water disturbance prediction method and prediction system, and the method is by obtaining the geometric parameter and multiple groups of working condition parameters of target navigation body combination;Based on the geometric parameter of target navigation body combination, construct flow field calculation model;Through flow field calculation model in the simulation of multiple groups of working condition parameters, the load of the precursor navigation body and the load of the subsequent navigation body corresponding to working condition parameters are obtained;According to multiple groups of working condition parameters, the load of the precursor navigation body and the load of the subsequent navigation body corresponding to working condition parameters, calculate the axial interference factor corresponding to working condition parameters;Based on each axial interference factor, generate the parallel asynchronous water disturbance prediction result of target navigation body combination, can be solved independently by double coupling interface, adaptive time step and phase change source correction, accurately simulate cavitation evolution and load transfer, improve the parallel asynchronous water disturbance prediction precision and calculation stability of double launch navigation body, provide reliable support for launch parameter optimization.

Description

Technical Field

[0001] This application relates to the field of multiphase flow coupling simulation technology, and in particular to a method and system for predicting interference from parallel asynchronous water discharge of a vehicle. Background Technology

[0002] Underwater launch technology is a core component of modern underwater equipment systems. Parallel launch of twin-engine vessels is a highly efficient strike mode, categorized into synchronous and asynchronous modes based on the launch sequence. Asynchronous launch mode, in particular, has broad application prospects due to its ability to achieve sequential strikes, reduce system peak load, and enhance penetration capabilities, thus meeting actual combat requirements. In this mode, the cavitation evolution, free surface deformation, and wake field structure generated by the launch of the preceding vessel alter the inflow conditions and load environment of the subsequent vessel, resulting in a highly unsteady and nonlinear process that requires precise prediction of its dynamic interference effects.

[0003] In current interference prediction for parallel asynchronous launches of twin-engine aircraft, axial spacing is the dominant factor affecting the interference effect, but it lacks systematic quantitative analysis and cannot provide a basis for launch timing optimization. Existing technologies are difficult to accurately simulate the dynamic interference of cavitation from the preceding aircraft to the following aircraft, and existing models have large prediction deviations for timing-related dynamic loads, especially the insufficient accuracy in predicting the impact and asymmetric loads caused by cavitation collapse. This makes it difficult to quickly evaluate and optimize launch timing schemes. Summary of the Invention

[0004] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0005] The main objective of this disclosure is to propose a method and system for predicting interference from parallel asynchronous launches of aircraft. This method can accurately simulate cavitation evolution and load transfer through independent solution of dual-coupled interfaces, adaptive time step, and phase change source term correction. This improves the accuracy and computational stability of interference prediction for parallel asynchronous launches of dual-engine aircraft, and provides reliable support for launch parameter optimization.

[0006] A first aspect of this application provides a method for predicting interference from parallel asynchronous water emergence of a vessel, the method comprising:

[0007] Obtain the geometric parameters and multiple sets of operational parameters of the target vehicle assembly; the target vehicle assembly includes at least a preceding vehicle and a following vehicle, the geometric parameters include at least the vehicle length, the operational parameters include axial spacing, initial velocity, and launch time interval, the axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle, and the launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle;

[0008] Based on the geometric parameters of the target vehicle combination, a flow field calculation model is constructed; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water.

[0009] By simulating multiple sets of operating parameters using the flow field calculation model, the loads of the preceding and subsequent vehicles under the corresponding operating parameters are obtained.

[0010] Based on the multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel, the axial interference factor of the corresponding operating condition parameters is calculated; the axial interference factor represents the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters.

[0011] Based on each of the axial interference factors, the parallel asynchronous water discharge interference prediction results of the target vehicle combination are generated.

[0012] In some embodiments of this application, constructing a flow field calculation model based on the geometric parameters of the target vehicle assembly includes:

[0013] A fluid control model is constructed based on unsteady fluid motion equations, multiphase flow models, turbulence models, and cavitation models, combined with the geometric parameters of the target vehicle assembly.

[0014] A cavitation dynamic encryption region is set in the fluid control model; the cavitation dynamic encryption region is used to characterize the cavitation evolution details generated during the water exit process of the preceding vehicle.

[0015] The fluid control model is coupled with a preset structural control model to form the flow field calculation model; the structural control model is constructed based on the plastic dynamic constitutive relation of the target vehicle assembly and is used to calculate the structural stress response of the target vehicle assembly during the water exit process.

[0016] In some embodiments of this application, before simulating the multiple sets of operating parameters using the flow field calculation model, the method further includes: constructing the fluid-structure interaction interface of the preceding and subsequent navigation bodies respectively.

[0017] In some embodiments of this application, after obtaining the loads of the preceding and following vessels corresponding to the operating parameters through the flow field calculation model by simulating multiple sets of operating parameters, the method further includes:

[0018] The simulation process of the dynamic densification region of cavitation in the flow field calculation model corresponding to the multiple sets of operating parameters is monitored to determine the cavitation interaction mode of the dynamic densification region of cavitation in the flow field calculation model; the cavitation interaction mode includes at least one of the following: encapsulation effect, edge effect, collapse effect and wake effect.

[0019] In some embodiments of this application, the formula for calculating the axial interference factor is as follows:

[0020] ;

[0021] in, For the axial spacing is and the length of the subsequent navigation body correspond Axial interference factor of transmission time interval, This refers to the axial spacing. The length of the subsequent navigation body. For normalized axial spacing, The axial spacing of the subsequent navigation bodies is correspond Payload during launch intervals For the preceding navigation body in The payload for the launch interval.

[0022] In some embodiments of this application, generating the parallel asynchronous water-emergence interference prediction results of the target vehicle combination based on each of the axial interference factors includes:

[0023] Based on each of the axial interference factors, the safe operating area for the target vehicle combination to exit the water asynchronously in parallel is divided; the safe operating area includes at least a safe area, a transition area and a dangerous area, the safe area is the area where the absolute value of the axial interference factor is less than or equal to a first preset threshold, the transition area is the area where the absolute value of the axial interference factor is greater than the first preset threshold and less than a second preset threshold, and the dangerous area is the area where the absolute value of the axial interference factor is greater than or equal to the second preset threshold.

[0024] Based on the safe operating area and the corresponding operating parameters of the safe operating area, the parallel asynchronous water discharge interference prediction results of the target vehicle combination are generated.

[0025] In some embodiments of this application, after generating the parallel asynchronous water-emergence interference prediction results of the target vehicle combination based on each of the axial interference factors, the method further includes:

[0026] Based on the prediction results of the parallel asynchronous water discharge interference of the target navigation body combination and the target navigation requirements of the target navigation body combination, the optimal axial spacing range is determined; the optimal axial spacing range is the axial spacing interval corresponding to the working condition parameter with the smallest absolute value of the axial interference factor.

[0027] Based on the optimal axial spacing range, a suggested emission parameter is generated; the suggested emission parameter is at least the optimal axial spacing range and the corresponding emission time interval.

[0028] The first aspect of this application provides a method for predicting interference from parallel asynchronous launch of aircraft. This method involves acquiring the geometric parameters and multiple sets of operating parameters of a target aircraft combination; constructing a flow field calculation model based on the geometric parameters of the target aircraft combination; simulating the flow field calculation model under multiple operating parameters to obtain the loads of the preceding and subsequent aircraft corresponding to the operating parameters; calculating the axial interference factor of the corresponding operating parameters based on the multiple sets of operating parameters, the loads of the preceding and subsequent aircraft corresponding to the operating parameters; and generating the prediction result of the parallel asynchronous launch interference of the target aircraft combination based on each axial interference factor. This method can accurately simulate cavitation evolution and load transfer through independent solution at a dual-coupling interface, adaptive time step, and phase change source term correction, thereby improving the prediction accuracy and computational stability of interference from parallel asynchronous launch of dual-engine aircraft and providing reliable support for launch parameter optimization.

[0029] To achieve the above objectives, a second aspect of the present invention provides a parallel asynchronous water emergence interference prediction system for aeronautical bodies, the system comprising:

[0030] The acquisition module is used to acquire the geometric parameters and multiple sets of operational parameters of the target vehicle assembly; the target vehicle assembly includes at least a preceding vehicle and a following vehicle, the geometric parameters include at least the vehicle length, the operational parameters include axial spacing, initial velocity, and launch time interval, the axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle, and the launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle;

[0031] A construction module is used to construct a flow field calculation model based on the geometric parameters of the target vehicle combination; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water.

[0032] The simulation module is used to obtain the loads of the preceding and subsequent vehicles under the corresponding operating conditions by simulating the multiple sets of operating conditions through the flow field calculation model.

[0033] The calculation module is used to calculate the axial interference factor of the corresponding operating condition parameters based on the multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel; the axial interference factor represents the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters.

[0034] The prediction module is used to generate the parallel asynchronous water discharge interference prediction results of the target vehicle combination based on each of the axial interference factors.

[0035] To achieve the above objectives, a third aspect of the present invention provides an electronic device, comprising: at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, the instructions being executed by the at least one control processor to enable the at least one control processor to perform the above-described method for predicting interference in parallel asynchronous water launch of a vessel.

[0036] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the above-described method for predicting interference in parallel asynchronous water launch of a vessel.

[0037] It is understood that the beneficial effects of the second to fourth aspects compared with the related technologies are the same as the beneficial effects of the first aspect compared with the related technologies. Please refer to the relevant description in the first aspect above, which will not be repeated here. Attached Figure Description

[0038] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0039] Figure 1 This is a flowchart illustrating a method for predicting interference from parallel asynchronous water exit of a vessel, as provided in an embodiment of this application.

[0040] Figure 2 This is a schematic diagram of a twin-engine hull launching asynchronously in parallel, according to an embodiment of this application.

[0041] Figure 3 This is a schematic diagram of a mesh generation method provided in an embodiment of this application;

[0042] Figure 4 This is a schematic diagram of the parallel asynchronous water cavitation development of a navigation body provided in an embodiment of this application;

[0043] Figure 5This is a schematic diagram of the stress distribution cloud map of the left preceding vessel during the cavitation collapse stage when the axial spacing is 0.25L (left) and 0.50L (right) according to the embodiments of this application;

[0044] Figure 6 This is a schematic diagram of the time-varying curves of the maximum surface pressure of the left preceding (left) vehicle and the right following (right) vehicle under different axial spacings provided in the embodiments of this application;

[0045] Figure 7 This is a schematic diagram of the structure of a parallel asynchronous water exit interference prediction system for a vessel provided in an embodiment of this application;

[0046] Figure 8 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application;

[0047] in, Figure 1 S110 is used to obtain the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; Figure 1 S120 is a flow field calculation model constructed based on the geometric parameters of the target vehicle assembly; Figure 1 S130 is a simulation of multiple sets of operating parameters using a flow field calculation model to obtain the loads of the preceding and subsequent vessels under the corresponding operating parameters. Figure 1 S140 is used to calculate the axial disturbance factor of the corresponding working condition parameters based on multiple sets of working condition parameters, the load of the preceding and subsequent vehicles corresponding to the working condition parameters; Figure 1 S150 is the prediction result of parallel asynchronous water discharge interference of the target vehicle combination based on interference factors of each axis; Figure 7 710 is the acquisition module; Figure 7 720 is the building block; Figure 7 The 730 is an analog module; Figure 7 740 is the computing module; Figure 7 The 750 is the prediction module. Detailed Implementation

[0048] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0049] In the description of this application, the use of terms such as "first," "second," etc., is for the purpose of distinguishing technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0050] In the description of this application, it should be understood that the orientation descriptions, such as up, down, etc., are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0051] In the description of this application, it should be noted that, unless otherwise explicitly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0052] Underwater launch technology is a core component of modern underwater equipment systems. Parallel launch of twin-engine vessels is a highly efficient strike mode, categorized into synchronous and asynchronous modes based on the launch sequence. Asynchronous launch mode, in particular, has broad application prospects due to its ability to achieve sequential strikes, reduce system peak load, and enhance penetration capabilities, thus meeting actual combat requirements. In this mode, the cavitation evolution, free surface deformation, and wake field structure generated by the launch of the preceding vessel alter the inflow conditions and load environment of the subsequent vessel, resulting in a highly unsteady and nonlinear process that requires precise prediction of its dynamic interference effects.

[0053] In current interference prediction for parallel asynchronous launches of twin-engine aircraft, axial spacing is the dominant factor affecting the interference effect, but it lacks systematic quantitative analysis and cannot provide a basis for launch timing optimization. Existing technologies are difficult to accurately simulate the dynamic interference of cavitation from the preceding aircraft to the following aircraft, and existing models have large prediction deviations for timing-related dynamic loads, especially the insufficient accuracy in predicting the impact and asymmetric loads caused by cavitation collapse. This makes it difficult to quickly evaluate and optimize launch timing schemes.

[0054] Based on this, the embodiments of this application provide a method and system for predicting interference from parallel asynchronous water emergence of aircraft carriers. The aim is to accurately simulate cavitation evolution and load transfer by solving independently through dual-coupled interfaces, adaptive time steps, and phase change source term correction, thereby improving the prediction accuracy and computational stability of interference from parallel asynchronous water emergence of dual-engine aircraft carriers and providing reliable support for the optimization of launch parameters.

[0055] The method and system for predicting interference from parallel asynchronous water discharge of a vessel provided in this application are specifically described through the following embodiments. First, the method for predicting interference from parallel asynchronous water discharge of a vessel in this application is described.

[0056] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0057] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0058] The method for predicting interference from parallel asynchronous water discharge of a vehicle provided in this application relates to the field of multiphase flow coupling simulation technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the method for predicting interference from parallel asynchronous water discharge of a vehicle, but is not limited to the above forms.

[0059] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0060] Therefore, referring to Figure 1This application provides a method for predicting interference in parallel asynchronous water discharge of a vessel. This method is applied to a central controller, which can be a server, an electronic device, or a mobile terminal, etc. There are no specific limitations here. The method includes the following steps S110 to S140.

[0061] Step S110: Obtain the geometric parameters and multiple sets of operational parameters of the target vehicle assembly; the target vehicle assembly includes at least a preceding vehicle and a following vehicle, the geometric parameters include at least the vehicle length, and the operational parameters include axial spacing, initial velocity and launch time interval. The axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle, and the launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle.

[0062] Step S120: Based on the geometric parameters of the target vehicle combination, construct a flow field calculation model; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water.

[0063] Step S130: Through the simulation of multiple sets of working parameters using the flow field calculation model, obtain the load of the preceding and subsequent vessels under the corresponding working parameters;

[0064] Step S140: Calculate the axial interference factor of the corresponding operating condition parameters based on multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel; the axial interference factor characterizes the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters.

[0065] Step S150: Based on the interference factors of each axis, generate the prediction results of the parallel asynchronous water discharge interference of the target vehicle combination.

[0066] In this step, the geometric parameters and multiple sets of operational parameters of the target vehicle assembly are first obtained. The geometric parameters determine the structural characteristics of the vehicle, and the operational parameters indicate the asynchronous launch state of the two vehicles in space and time, providing input conditions for subsequent simulations. The target vehicle assembly includes at least a preceding vehicle and a following vehicle. The geometric parameters include at least the vehicle length, and the operational parameters include axial spacing, initial velocity, and launch time interval. The axial spacing is defined as the axial distance between the heads of the preceding and following vehicles, and the launch time interval refers to the time difference between the launch times of the preceding and following vehicles.

[0067] Furthermore, a flow field calculation model is constructed, and the fluid-structure interaction interface of the preceding and subsequent navigation bodies is constructed respectively. The flow field calculation model restores the structure of the navigation body based on geometric parameters, and specifically simulates the dynamic process of the preceding and subsequent navigation bodies being arranged in parallel in space and exiting water asynchronously in time. It can accurately capture the flow field changes such as cavitation evolution and free liquid surface deformation caused by the exit of the preceding navigation body.

[0068] Furthermore, simulations were conducted using a flow field calculation model under multiple sets of operating parameters. By real-time monitoring, load data on the preceding and subsequent vessels under different operating conditions were obtained. This load data directly reflects the stress state of the two vessels during the asynchronous water discharge process, providing a key basis for quantifying the interference effect.

[0069] Specifically, after simulating multiple sets of operating parameters using the flow field calculation model, the simulation process of the dynamic densification region of cavitation in the flow field calculation model corresponding to multiple sets of operating parameters is monitored to determine the cavitation interaction mode of the dynamic densification region of cavitation in the flow field calculation model; wherein, the cavitation interaction mode includes at least one of the following: encapsulation effect, edge effect, collapse effect and wake effect.

[0070] Furthermore, the axial interference factor is calculated to clarify the degree of deviation of the subsequent launch vehicle load relative to the preceding launch vehicle load under specific operating conditions by correlating operating condition parameters and load data, thereby achieving a quantitative characterization of the interference effect of parameters such as axial spacing. Then, based on the axial interference factors of multiple operating conditions, parallel asynchronous launch interference prediction results are integrated to provide an intuitive and quantitative reference for assessing interference risks under different launch parameters and optimizing launch timing.

[0071] Specifically, the formula for calculating the axial disturbance factor is as follows:

[0072] ;

[0073] in, For an axial spacing of and the length of the subsequent navigation body correspond Axial interference factor of transmission time interval, This refers to the axial spacing. The length of the subsequent navigation body. For normalized axial spacing, The axial spacing of the subsequent navigation bodies is correspond Payload during launch intervals For the preceding navigation body in The payload for the launch interval.

[0074] In one embodiment, based on the parallel asynchronous water discharge interference prediction method of the aircraft body, a four-in-one technical framework of "parametric modeling - dynamic mesh - asynchronous coupling - quantitative evaluation" is established to overcome the problem of accurate prediction of the axial spacing time series effect and provide a complete solution for engineering practice. The specific implementation steps are as follows:

[0075] Step 1: Definition of Asynchronous Motion Configuration and Spatiotemporal Parameters:

[0076] First, a parallel geometric model of the twin-engine aircraft is established, focusing on defining its spatiotemporal correlation parameters. Specifically, such as... Figure 2 The diagram shows a twin-engine vehicle system. The coordinate system is defined with vertical upward as z, horizontal to the right as x, and the water surface as a free surface. The first vehicle launched is called the first vehicle, and the vehicles launched after a certain interval are called the second vehicles. The axial spacing between the vehicles is Z, and the lateral spacing is X (a fixed lateral spacing reference is then set (preferably X = 1.5D) to eliminate the influence of lateral interference on the axial effect study). The axial spacing is then... The delay distance between the posterior head and the anterior head in the direction of water exit is used as the core research variable, with a value range of 0.25L ≤ ≤1.0L (L is the length of the hull). Finally, establish the axial spacing. Relationship with launch delay time Δt: ,in, The initial velocity, It characterizes the dynamic changes in spacing during motion.

[0077] Step 2: Physical Modeling and Dynamic Mesh Strategy for Spatiotemporal Evolution

[0078] First, fluid control equations are constructed based on unsteady Reynolds-averaged Navier-Stokes equations, VOF multiphase flow model, Realizable k-ε turbulence model, and Schnerr-Sauer cavitation model. Then, structural control equations are constructed by combining Johnson-Cook plastic dynamic constitutive model. Finally, an asynchronous coupled solution architecture is adopted to implement dynamic cavitation channel densification technology.

[0079] Specifically, the dynamic cavitation channel densification technology is implemented by establishing a cylindrical dynamic densification region centered on the trajectory of the preceding body (the mesh size of the densification region is 20%-40% of the background mesh), and the diameter of this cylindrical dynamic densification region is [missing information]. The length of the cylindrical dynamic encryption region is .in, , The coefficient of thermal expansion is 1 / 3. The cavitation expansion rate is... The time interval is the launch interval. The encrypted region is dynamically optimized based on the cavitation volume fraction gradient using a mesh adaptive technique.

[0080] like Figure 3 As shown, the flow field domain employs a volume mesh generation and overlapping mesh calculation method, while the structural domain uses a surface mesh generation and shell element solution strategy. Specifically, the background and overlapping domains of the flow field are generated with sparser and more precise cut volume elements respectively using STAR-CCM+ software. To ensure stable mesh interpolation calculations between the dynamic and static domains and good capture of free surface dynamics, local refinement was applied to the background and water surface. The refinement areas for the background and water surface are 4D×4D×5L and 20D×20D×0.25L cuboids, respectively, with a mesh size of 12.5%D for both. To simulate boundary layer flow, a prismatic layer mesh with a total thickness of 5%D, 25 layers, and an elongation of 1.25 was set near the vehicle wall, with a surface y+ mean value within the range of 40~100, meeting the calculation requirements of the selected turbulence model. Simultaneously, local refinement was applied around the vehicle to ensure a uniform transition between the boundary layer and overlapping domain meshes, with a refinement mesh size of 2.5%D, i.e., a mesh size of 0.02m on the vehicle surface. In this embodiment, the maximum speed in the simulation study is 40 m / s, the solution time step is 1e-4 s, and the calculation shows that the mesh generation strategy meets the CFL stability criterion. The number of meshes in the simulated flow field is about 3 million.

[0081] Furthermore, a dual-coupling interface independent solution strategy is adopted, establishing fluid-structure interaction interfaces for both the preceding and subsequent vehicles, and setting adaptive time steps to meet preset stability conditions. Additionally, a phase change source term correction is introduced to accurately simulate mass transport during cavitation collapse.

[0082] Step 3: Temporal Interference Feature Extraction and Quantitative Evaluation

[0083] First, based on simulation results, a quantitative evaluation system for the asynchronous water discharge interference effect is established. Frequency analysis is introduced to identify the characteristic load frequencies under different axial spacings. Specifically, the core index in the quantitative evaluation system—the axial interference factor—is defined, and its calculation formula is as follows:

[0084] ;

[0085] in, For an axial spacing of and the length of the subsequent navigation body correspond The axial interference factor of the launch interval is a dimensionless percentage value that represents the percentage deviation of the load on the aft body relative to the reference load at a specific axial spacing and a specific launch interval. For normalized axial spacing, The axial spacing of the subsequent navigation bodies is correspond Payload during launch intervals For the preceding navigation body in The payload for the launch interval.

[0086] Furthermore, cavitation interactions are categorized into envelopment effect, edge effect, collapse effect, and wake effect. Specifically, the envelopment effect occurs when the following vehicle is completely inside the cavitation bubble of the preceding vehicle; the edge effect occurs when the following vehicle is located in the cavitation interface region; the collapse effect occurs when the following vehicle encounters the cavitation collapse region of the preceding vehicle; and the wake effect occurs when the following vehicle is located in the wake influence zone of the preceding vehicle.

[0087] like Figure 4 As shown, when the axial spacing is 0.25L, the low-pressure area on the shoulder of the left-hand preceding vehicle exhibits an asymmetrical distribution, larger on the left and smaller on the right, due to the influence of the high-pressure area at the head of the right-hand following vehicle. This results in cavitation development exhibiting a left-long, right-short shape, while the cavitation on the shoulder of the right-hand following vehicle shows obvious symmetry. Simultaneously, this influence further disrupts the lateral force balance of the left-hand preceding vehicle, causing it to gradually deflect to the left. At T=120ms, the head of the left-hand preceding vehicle reaches the water surface. Its right-hand cavitation, being shorter, collapses earlier, exacerbating the leftward deflection. At T=160ms, the left-hand cavitation collapses completely, creating a high-pressure peak area on the left. At this point, the head of the right-hand following vehicle reaches the water surface. Subsequently, the cavitation on the shoulder of the right-hand following vehicle undergoes propulsive collapse under the influence of the water surface, completely collapsing at T=205ms, and a high-pressure peak area appears on the left. Because the lateral force generated by the collapse of the cavitation bubble at the tail of the left-hand lead vehicle will cause the right-hand follow vehicle to deflect to the left, and the lateral force generated by the collapse of the cavitation bubble at the shoulder of the twin-engine vehicle will cause the right-hand follow vehicle to deflect to the right, the deflection of the right-hand follow vehicle is not significant under their combined effect.

[0088] like Figure 5 As shown, Figure 5 Stress distribution cloud maps of the left-side preceding spacecraft during the cavitation collapse stage, characterizing axial spacing of 0.25L (left) and 0.50L (right). From Figure 5As can be seen, when the axial spacing is 0.25L and 0.50L, the stress peak point appears on the opposite side of the vehicle; when the axial spacing is 0.75L, the stress peak point appears on the adjacent side of the vehicle, both consistent with the location of cavitation collapse at the corresponding axial spacing. Furthermore, as the axial spacing increases, the preceding vehicle on the left will reach the water surface earlier and experience cavitation collapse, thus the stress peak occurs earlier.

[0089] like Figure 6 As shown, Figure 6 Time-varying curves representing the maximum surface pressure of the left preceding (left) and right following (right) vehicles under different axial spacings. Figure 6 The time-varying curves of the maximum surface pressure of the twin-engine hulls under different axial spacings are presented, with the peak value representing the maximum pressure of cavitation collapse. As shown in the figure, when the axial spacing increases from 0.25L to 0.75L, the time to occurrence of the maximum collapse pressure of the left-hand preceding hull decreases from 160ms to 90ms, and the peak value increases from 7.98MPa to 11.62MPa, mainly due to the decrease in cavitation number. For the right-hand following hull, the maximum cavitation collapse pressure is reached at an axial spacing of 0.50L, approximately 11.65MPa, which is 2.05 times that of the salvo firing state, further indicating the severe stress conditions during the twin-engine emergence process under these conditions.

[0090] Furthermore, a safe operating domain is constructed, specifically based on axial spacing. and interference intensity The area is divided into sections. The danger zone is defined as | |>30%, transition zone is 10%<| |≤30%, the safe zone is| ≤10%.

[0091] Step 4: Engineering Design Guidelines and Optimization Suggestions

[0092] In this step, based on the quantitative analysis results, engineering design criteria are proposed. Specifically, this includes recommending the optimal axial spacing as follows: When the absolute value is at its smallest Range, when When extreme values ​​occur The interval provides early warning of hazardous operating conditions, and the launch timing is optimized based on the safe operating domain. Recommended value.

[0093] Step 4: Intelligent Design Decision Support System

[0094] In this step, practical engineering design criteria are established based on the results of multi-dimensional quantitative analysis. Specifically, automatic parameter optimization is achieved using machine learning algorithms to recommend optimal timing strategies, and preventative measures are generated based on the safe operating domain. Hazardous operating conditions are intelligently identified and warned of to achieve dynamic risk assessment and early warning.

[0095] In one embodiment of this invention, the parallel asynchronous launch process of a dual-engine hull is used as an example to illustrate the implementation method. The specific implementation steps are as follows:

[0096] Step a: Defining and setting asynchronous operating conditions:

[0097] First, a geometric model of the twin-engine aircraft was established, and a suitable lateral spacing benchmark was set. The axial spacing was used as the core research variable. Several typical operating conditions were selected, and a suitable initial immersion depth for the aircraft was set. Then, a suitable initial velocity for the preceding aircraft was set, and the corresponding launch delay time for the following aircraft was set according to the axial spacing under study. Kinematic correlation was established to ensure that the axial spacing remained stable during the study.

[0098] Step b: Computational model and mesh generation:

[0099] First, a suitable 3D unsteady-state solver is selected, and a multiphase flow model is activated, including water, air, and steam phases. Appropriate turbulence and cavitation models are employed, and overlapping mesh technology is enabled to handle the large displacement motion of the vehicle. Then, for the background computational domain, a cavitation channel refinement region centered on the trajectory of the preceding vehicle is created using an appropriate mesh type and base size. By setting a suitable mesh size for the refinement region, the resolution of the cavitation interface is ensured, creating an independent overlapping mesh region for each vehicle. The diameter of this cylindrical dynamic refinement region is [missing information]. The length of the cylindrical dynamic encryption region is .in, , The coefficient of thermal expansion is 1 / 3. The cavitation expansion rate is... This is the launch time interval.

[0100] Step c: Fluid-structure interaction solution setup:

[0101] In this step, a suitable finite element model is established, the corresponding material model parameters are defined, the dynamic analysis step and a suitable time step are set, and an independent fluid-structure interaction interface is established for the twin-engine aircraft. Data exchange parameters and output settings are configured, and physical quantity monitoring points are set.

[0102] Step d: Solving and monitoring:

[0103] In this step, appropriate computational domain boundary conditions are set, flow field parameters are initialized, a monitoring system is configured, and an appropriate time step control strategy is adopted to monitor the changes in key physical quantities in real time, ensuring the stability of the computation process.

[0104] Step e: Results Analysis and Security Domain Construction

[0105] In this step, load time history data under various operating conditions are extracted, the axial disturbance factor is calculated, and then the load characteristics and frequency features are analyzed. Specifically, the formula for calculating the axial disturbance factor is as follows:

[0106] ;

[0107] in, For an axial spacing of and the length of the subsequent navigation body correspond The axial interference factor of the launch interval is a dimensionless percentage value that represents the percentage deviation of the load on the aft body relative to the reference load at a specific axial spacing and a specific launch interval. For normalized axial spacing, The axial spacing of the subsequent navigation bodies is correspond Payload during launch intervals For the preceding navigation body in The payload for the launch interval.

[0108] Furthermore, safe zones are defined based on interference factors. Specifically, | |>30% is designated as a danger zone, and 10%<| |≤30% is classified as a transition region, and| | ≤10% is designated as a safe zone. Then, the relationship between axial spacing and disturbance intensity is established to determine the optimal parameter range, generating a safe operating domain map, providing parameter optimization suggestions, and offering guidance for engineering applications.

[0109] In some embodiments, in step S120, a flow field calculation model is constructed based on the geometric parameters of the target vehicle assembly, including the following steps S210 to S230:

[0110] Step S210: Based on the unsteady fluid motion equations, multiphase flow model, turbulence model and cavitation model, construct a fluid control model by combining the geometric parameters of the target vehicle assembly;

[0111] Step S220: Set up a dynamic cavitation densification region in the fluid control model; the dynamic cavitation densification region is used to characterize the cavitation evolution details generated during the water exit process of the preceding vehicle.

[0112] Step S230: Couple the fluid control model with the preset structural control model to form a flow field calculation model; the structural control model is constructed based on the plastic dynamic constitutive relation of the target vehicle assembly and is used to calculate the structural force response of the target vehicle assembly during the water exit process.

[0113] In this embodiment, a fluid control model is constructed by integrating unsteady fluid motion equations, multiphase flow models, turbulence models, and cavitation models, combined with the geometric parameters of the target vehicle assembly (such as vehicle length), thereby laying the physical foundation for flow field simulation and ensuring the reproduction of complex flow field environments. Specifically, the unsteady equations adapt to the dynamic characteristics of the water exit process, the multiphase flow model handles the interaction of the gas, liquid, and vapor three-phase media, the turbulence model captures the turbulent state of the flow field, and the cavitation model specifically addresses the cavitation phenomenon during the exit of the preceding vehicle.

[0114] Furthermore, since the generation, development, and collapse of cavitation bubbles in preceding vehicles have strong transient and localized interference with subsequent vehicles, this embodiment sets up a dynamic densification region for cavitation bubbles in the fluid control model to focus on the space where the cavitation bubbles are located. By refining the mesh, the accuracy of capturing details such as cavitation bubble morphology changes, collapse locations, and intensities is improved, avoiding the loss of key interference information due to coarse global mesh.

[0115] Furthermore, the fluid control model is coupled with the pre-set structural control model to form a complete flow field calculation model. This achieves a dynamic interactive simulation of "flow field loads affecting structural response and structural motion reacting to the flow field," thus more realistically reflecting the complex coupling process when the two-engine aircraft launch asynchronously. This provides reliable model support for subsequent load acquisition and disturbance prediction. The structural control model is constructed based on the plastic dynamic constitutive relation of the aircraft material, enabling accurate calculation of the structural stress and deformation response of the aircraft under loads such as water flow impact and cavitation collapse.

[0116] In some embodiments, in step S130, based on each axial interference factor, a parallel asynchronous water exit interference prediction result for the target vehicle combination is generated, including the following steps S310 to S320:

[0117] Step S310: Based on each axial interference factor, divide the safe operation area for the target vehicle combination to exit the water in parallel and asynchronously; the safe operation area includes at least a safe area, a transition area and a dangerous area. The safe area is the area where the absolute value of the axial interference factor is less than or equal to the first preset threshold, the transition area is the area where the absolute value of the axial interference factor is greater than the first preset threshold and less than the second preset threshold, and the dangerous area is the area where the absolute value of the axial interference factor is greater than or equal to the second preset threshold.

[0118] Step S320: Based on the safe operating area and the corresponding operating condition parameters of the safe operating area, generate the prediction results of the parallel asynchronous water discharge interference of the target navigation body combination.

[0119] In this embodiment, the degree of interference is visualized by preset thresholds. Specifically, the safe zone corresponds to an axial interference factor absolute value less than or equal to the first preset threshold, indicating that the interference of the preceding vehicle on the following vehicle is weak, the load deviation of the following vehicle is within an acceptable range, and the stability of the vehicle can be guaranteed. The transition zone is where the interference factor absolute value is between the first and second preset thresholds, indicating a moderate degree of interference, and the adaptability of the operating parameters needs to be carefully evaluated. The danger zone corresponds to an interference factor absolute value greater than or equal to the second preset threshold, meaning that the interference is severe and may cause abnormal load or attitude instability of the following vehicle, and must be strictly avoided.

[0120] Furthermore, by associating the safe operating area with corresponding operating parameters (such as axial spacing, launch time interval, etc.), a complete interference prediction result is generated. This not only clarifies the parameter range corresponding to different interference levels, but also transforms abstract interference factors into specific operational guidelines. This facilitates engineers in quickly identifying safe launch conditions and selecting optimal operating parameters, effectively solving the limitations of traditional methods that rely on experience or high-cost experiments. It provides a quantitative basis for the timing optimization and safety assessment of parallel asynchronous launch of dual-engine aircraft.

[0121] In some embodiments, after generating the parallel asynchronous water exit interference prediction results of the target vehicle combination based on each axial interference factor in step S130, the method further includes the following steps S410 to S420:

[0122] Step S410: Based on the prediction results of the parallel asynchronous water discharge interference of the target navigation body combination and the target navigation requirements of the target navigation body combination, determine the optimal axial spacing range; the optimal axial spacing range is the axial spacing interval corresponding to the working condition parameter with the smallest absolute value of the axial interference factor.

[0123] Step S420: Generate emission parameter optimization suggestions based on the optimal axial spacing range; the emission parameter optimization suggestions shall include at least the optimal axial spacing range and the corresponding emission time interval.

[0124] In this embodiment, based on the generated parallel asynchronous water discharge interference prediction results (including the axial interference factor and safe operating area for each operating condition), and combined with the actual navigation requirements of the target vehicle combination (such as attitude stability, load tolerance limit, penetration efficiency, etc.), the axial spacing range corresponding to the operating condition parameter with the smallest absolute value of the axial interference factor is selected and determined as the optimal axial spacing range. Thus, by using the optimal axial spacing range, the dynamic interference of the preceding vehicle to the following vehicle can be reduced to the maximum extent, while also meeting the performance requirements in actual combat or testing.

[0125] Furthermore, based on the optimal axial spacing range, the corresponding launch time interval is further matched to form a complete launch parameter optimization suggestion. Thus, by associating the optimal axial spacing with the suitable launch time interval, the suggestion becomes operable, solving the problem of relying on experience estimation or high-cost experiments to determine launch parameters in traditional designs. This provides a precise and quantitative technical basis for the timing planning of parallel asynchronous launch of twin-engine hulls, effectively improving the safety and efficiency of the launch scheme.

[0126] like Figure 7 As shown in some embodiments of this application, a parallel asynchronous water emergence interference prediction system for aerospace vehicles is provided. The system includes an acquisition module 710, a construction module 720, a simulation module 730, a calculation module 740, and a prediction module 750. Specifically:

[0127] The acquisition module 710 is used to acquire the geometric parameters and multiple sets of operational parameters of the target vehicle assembly. The target vehicle assembly includes at least a preceding vehicle and a following vehicle. The geometric parameters include at least the vehicle length. The operational parameters include the axial spacing, the initial velocity, and the launch time interval. The axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle. The launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle.

[0128] Module 720 is used to construct a flow field calculation model based on the geometric parameters of the target vehicle combination; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water.

[0129] The simulation module 730 is used to simulate multiple sets of operating parameters through a flow field calculation model, and to obtain the loads of the preceding and subsequent vehicles under the corresponding operating parameters.

[0130] The calculation module 740 is used to calculate the axial disturbance factor of the corresponding operating condition parameters based on multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel. The axial disturbance factor represents the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters.

[0131] The prediction module 750 is used to generate parallel asynchronous water discharge interference prediction results for the target vehicle combination based on the interference factors of each axis.

[0132] It should be noted that the parallel asynchronous water discharge interference prediction system for ships provided in this embodiment is based on the same inventive concept as the above-mentioned parallel asynchronous water discharge interference prediction method for ships. Therefore, the relevant content of the above-mentioned parallel asynchronous water discharge interference prediction method for ships also applies to the content of the parallel asynchronous water discharge interference prediction system for ships. Therefore, it will not be repeated here.

[0133] To this end, the system acquires the geometric parameters and multiple sets of operating parameters of the target launch vehicle assembly; based on the geometric parameters of the target launch vehicle assembly, it constructs a flow field calculation model; through the simulation of the flow field calculation model under multiple sets of operating parameters, it obtains the loads of the preceding and following launch vehicles corresponding to the operating parameters; based on the multiple sets of operating parameters, the loads of the preceding and following launch vehicles corresponding to the operating parameters, it calculates the axial interference factors of the corresponding operating parameters; based on each axial interference factor, it generates the prediction results of the parallel asynchronous water discharge interference of the target launch vehicle assembly. In this way, it can achieve accurate simulation of cavitation evolution and load transfer through independent solution via dual-coupling interfaces, adaptive time step, and phase change source term correction, improving the prediction accuracy and computational stability of parallel asynchronous water discharge interference of dual-launch vehicles, and providing reliable support for launch parameter optimization.

[0134] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-mentioned method for predicting interference in parallel asynchronous water launch of a vessel.

[0135] This disclosure also provides a storage medium, which is a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the above-described method for predicting interference in parallel asynchronous water launch of a vessel.

[0136] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, 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, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0137] like Figure 8 The diagram shows the internal structure of a computer device in one embodiment. This computer device can specifically be a terminal or a server. Please refer to... Figure 8The computer device includes a processor, memory, etc., connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program causes the processor to implement the method described in this embodiment. The internal memory may also store a computer program, which, when executed by the processor, causes the processor to perform the method described in this embodiment. Those skilled in the art will understand that... Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0138] The above embodiments merely illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

[0139] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for predicting interference from parallel asynchronous water exit of a vessel, characterized in that, The method includes: Obtain the geometric parameters and multiple sets of operational parameters of the target vehicle assembly; the target vehicle assembly includes at least a preceding vehicle and a following vehicle, the geometric parameters include at least the vehicle length, the operational parameters include axial spacing, initial velocity, and launch time interval, the axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle, and the launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle; Based on the geometric parameters of the target vehicle combination, a flow field calculation model is constructed; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water. By simulating multiple sets of operating parameters using the flow field calculation model, the loads of the preceding and subsequent vehicles under the corresponding operating parameters are obtained. Based on the multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel, the axial interference factor of the corresponding operating condition parameters is calculated; the axial interference factor represents the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters. Based on the axial interference factors, the safe operating area for the parallel asynchronous water discharge of the target vehicle combination is divided; the safe operating area includes at least a safe area, a transition area, and a danger area. The safe area is the area where the absolute value of the axial interference factor is less than or equal to a first preset threshold, the transition area is the area where the absolute value of the axial interference factor is greater than the first preset threshold and less than a second preset threshold, and the danger area is the area where the absolute value of the axial interference factor is greater than or equal to the second preset threshold. Based on the safe operating area and the corresponding operating condition parameters, the interference prediction result for the parallel asynchronous water discharge of the target vehicle combination is generated.

2. The method for predicting interference from parallel asynchronous water exit of a vessel according to claim 1, characterized in that, The flow field calculation model is constructed based on the geometric parameters of the target vehicle assembly, including: A fluid control model is constructed based on unsteady fluid motion equations, multiphase flow models, turbulence models, and cavitation models, combined with the geometric parameters of the target vehicle assembly. A cavitation dynamic encryption region is set in the fluid control model; the cavitation dynamic encryption region is used to characterize the cavitation evolution details generated during the water exit process of the preceding vehicle. The fluid control model is coupled with a preset structural control model to form the flow field calculation model; the structural control model is constructed based on the plastic dynamic constitutive relation of the target vehicle assembly and is used to calculate the structural stress response of the target vehicle assembly during the water exit process.

3. The method for predicting interference from parallel asynchronous water exit of a vessel according to claim 1, characterized in that, Before simulating the multiple sets of operating parameters using the flow field calculation model, the method further includes: constructing the fluid-structure interaction interface between the preceding and subsequent navigation bodies, respectively.

4. The method for predicting interference from parallel asynchronous water exit of a vessel according to claim 1, characterized in that, After obtaining the loads of the preceding and following vehicles under the corresponding operating conditions through the simulation of multiple sets of operating parameters using the flow field calculation model, the method further includes: The simulation process of the dynamic densification region of cavitation in the flow field calculation model corresponding to the multiple sets of operating parameters is monitored to determine the cavitation interaction mode of the dynamic densification region of cavitation in the flow field calculation model; the cavitation interaction mode includes at least one of the following: encapsulation effect, edge effect, collapse effect and wake effect.

5. The method for predicting interference from parallel asynchronous water exit of a vessel according to claim 1, characterized in that, The formula for calculating the axial interference factor is as follows: ； in, For the axial spacing is and the length of the subsequent navigation body correspond Axial interference factor of transmission time interval, This refers to the axial spacing. The length of the subsequent navigation body. For normalized axial spacing, The axial spacing of the subsequent navigation bodies is correspond Payload during launch intervals For the preceding navigation body in The payload for the launch interval.

6. The method for predicting interference from parallel asynchronous water exit of a vessel according to claim 1, characterized in that, After generating the parallel asynchronous water-emergence interference prediction results for the target vehicle combination, the method further includes: Based on the prediction results of the parallel asynchronous water discharge interference of the target navigation body combination and the target navigation requirements of the target navigation body combination, the optimal axial spacing range is determined; the optimal axial spacing range is the axial spacing interval corresponding to the working condition parameter with the smallest absolute value of the axial interference factor. Based on the optimal axial spacing range, a suggested emission parameter is generated; the suggested emission parameter is at least the optimal axial spacing range and the corresponding emission time interval.

7. A parallel asynchronous water emergence interference prediction system for aerospace vehicles, characterized in that, The system includes: The acquisition module is used to acquire the geometric parameters and multiple sets of operational parameters of the target vehicle assembly; the target vehicle assembly includes at least a preceding vehicle and a following vehicle, the geometric parameters include at least the vehicle length, the operational parameters include axial spacing, initial velocity, and launch time interval, the axial spacing is the axial distance between the head of the preceding vehicle and the head of the following vehicle, and the launch time interval is the time difference between the launch time of the preceding vehicle and the launch time of the target following vehicle; A construction module is used to construct a flow field calculation model based on the geometric parameters of the target vehicle combination; the flow field calculation model is used to simulate the process of the preceding and subsequent vehicles being arranged in parallel in space but not synchronously in time when they emerge from the water. The simulation module is used to obtain the loads of the preceding and subsequent vehicles under the corresponding operating conditions by simulating the multiple sets of operating conditions through the flow field calculation model. The calculation module is used to calculate the axial interference factor of the corresponding operating condition parameters based on the multiple sets of operating condition parameters, the load of the preceding vessel corresponding to the operating condition parameters, and the load of the following vessel; the axial interference factor represents the deviation value of the load of the following vessel relative to the load diameter of the preceding vessel under the operating condition parameters. The prediction module is used to divide the safe operating area of ​​the target vehicle combination for parallel asynchronous water discharge according to each of the axial interference factors. The safe operating area includes at least a safe area, a transition area, and a danger area. The safe area is the area where the absolute value of the axial interference factor is less than or equal to a first preset threshold. The transition area is the area where the absolute value of the axial interference factor is greater than the first preset threshold and less than a second preset threshold. The danger area is the area where the absolute value of the axial interference factor is greater than or equal to the second preset threshold. Based on the safe operating area and the corresponding operating condition parameters, the module generates the interference prediction result for the parallel asynchronous water discharge of the target vehicle combination.

8. An electronic device, characterized in that, It includes at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, which, when executed by the at least one control processor, enables the at least one control processor to perform a method for predicting interference in parallel asynchronous water launch of a vehicle as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform a method for predicting interference in parallel asynchronous water emergence of a vessel, as described in any one of claims 1 to 6.

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