A method and system for predicting the outflow interference of a vehicle in parallel

Abstract

The application discloses a kind of navigation body parallel synchronous water interference 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 multiple groups of working condition parameters, the initial interference prediction model is simulated to obtain the load in the parallel synchronous water process of each navigation body in target navigation body combination by target navigation body combination parallel synchronous water process;According to the load in the parallel synchronous water process of each navigation body in target navigation body combination, the lateral interference factor of each navigation body in target navigation body combination is calculated;Based on the lateral interference factor of each navigation body in target navigation body combination and corresponding working condition parameters, the interference prediction result of target navigation body combination parallel synchronous water is generated, can be through navigation body geometry and working condition parameters, combined with the prediction model of multiple physical field network, high-precision simulation double launch synchronous water process, quantification interference factor and define critical spacing, provide reliable data support for underwater equipment design.

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 synchronous water discharge of a vehicle. Background Technology

[0002] The underwater launch and surfacing process of submarines is a key technological aspect of the development of new underwater equipment, directly impacting its combat effectiveness and mission adaptability. With increasing demands for firepower density and penetration probability, the parallel synchronous surfacing launch mode of twin-engine submarines has become an important direction for underwater equipment development due to its significant enhancement of combat capabilities. In this mode, the two submarines must launch synchronously and in close proximity, involving complex multi-body interference dynamics problems. Their flow structure and load characteristics undergo fundamental changes compared to single-engine surfacing, posing higher requirements for engineering design and safety assessment.

[0003] Current numerical simulations of multi-focus single-body launch scenarios for aircraft carriers lack clarity regarding multi-body interference mechanisms and quantitative analysis methods, failing to accurately describe hydrodynamic interactions and load asymmetry. Furthermore, existing simulation and prediction technologies applied to dual-engine parallel launch scenarios rely on unidirectional or weakly coupled algorithms, which cannot meet the computational accuracy requirements of transient high-impact processes, resulting in insufficient prediction accuracy and reliability. This, in turn, restricts the engineering application of dual-engine parallel launch technology. 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 simultaneous launch of two engines in parallel operation. This method and system can accurately simulate the simultaneous launch process of two engines by combining the geometric and operational parameters of the aircraft with a prediction model based on a multiphysics network. It can also quantify interference factors and define critical spacing, providing reliable data support for the design of underwater equipment.

[0006] A first aspect of this application provides a method for predicting interference in parallel synchronous 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 first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operational parameters include the lateral spacing, the initial velocity, and the launch time, wherein the lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time;

[0008] Based on the multiple sets of operating parameters, the parallel synchronous water release process of the target ship combination is simulated through an initial interference prediction model to obtain the loads of each ship in the target ship combination during the parallel synchronous water release process; the initial interference prediction model is constructed based on the geometric parameters of the target ship combination and the multiple sets of operating parameters.

[0009] Based on the loads of each vessel in the target vessel assembly during the parallel synchronous water exit process, calculate the lateral interference factor of each vessel in the target vessel assembly.

[0010] Based on the lateral interference factors and corresponding operating parameters of each vessel in the target vessel combination, the interference prediction results for the parallel synchronous water discharge of the target vessel combination are generated.

[0011] In some embodiments of this application, before simulating the parallel synchronous water release process of the target vessel assembly based on the multiple sets of operating condition parameters using an initial disturbance prediction model to obtain the loads of each vessel in the target vessel assembly during the parallel synchronous water release process, the method further includes:

[0012] Based on the geometric parameters of the target vehicle assembly, a background computational domain is determined; the background computational domain covers the motion trajectory and flow field influence area of ​​each vehicle in the target vehicle assembly.

[0013] Based on the lateral spacing and the geometric parameters, overlapping grid regions are divided in the background computation domain, and the initial interference prediction model is constructed; the overlapping grid regions include the near-field grid sub-regions of each vehicle in the target vehicle assembly and the common flow field grid sub-regions.

[0014] In some embodiments of this application, the initial disturbance prediction model includes a motion model of the first vessel and a motion model of the second vessel. Before simulating the parallel and synchronous water discharge process of the target vessels based on the multiple sets of operating parameters using the initial disturbance prediction model to obtain the load during the parallel and synchronous water discharge process of the target vessels, the method further includes:

[0015] Based on the launch time, motion models of the first and second spacecraft are defined; both motion models of the first and second spacecraft are constructed based on a six-degree-of-freedom motion body and the Johnson-Cook plastic material model.

[0016] For the motion models of the first and second vehicles respectively, a fluid-structure interaction interface is constructed, and the simulation parameters of the initial interference prediction model are set.

[0017] In some embodiments of this application, the initial disturbance prediction model includes a multiphase flow field calculation subnetwork, a cavitation effect simulation subnetwork, and a fluid-structure interaction control subnetwork. The multiphase flow field calculation subnetwork is used to capture the dynamic evolution of the gas-liquid two-phase interface. The cavitation effect simulation subnetwork is used to calculate the generation and collapse process of surface cavitation bubbles of each vehicle in the target vehicle assembly. The fluid-structure interaction control subnetwork is used to realize the real-time interaction between the flow field load and the vehicle motion.

[0018] In some embodiments of this application, the formula for calculating the lateral interference factor is as follows:

[0019] ;

[0020] in, For the horizontal spacing is The diameter of each vessel in the target vessel assembly is correspond Lateral interference factor at launch time, The horizontal spacing is... The diameter of each vessel in the target vessel assembly is defined as the vessel diameter. Normalized position coordinates The first sailing body has an axial spacing of correspond Payload at launch time The second sailing body has an axial spacing of correspond The payload at launch time.

[0021] In some embodiments of this application, generating interference prediction results for the parallel synchronous water discharge of the target navigation body assembly based on the lateral interference factors and corresponding operating parameters of each navigation body in the target navigation body assembly includes:

[0022] The lateral interference factor and corresponding operating parameters of each vessel in the target vessel combination are analyzed to obtain the variation law of the lateral interference factor; the variation law of the lateral interference factor includes the variation trend of the lateral interference factor of each vessel in the target vessel combination with the lateral spacing in the operating parameters.

[0023] Based on the variation law of the lateral interference factor, the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters is determined, so as to generate the interference prediction result of the target vehicle assembly's parallel synchronous water discharge according to the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters.

[0024] In some embodiments of this application, determining the critical lateral spacing of the target vehicle assembly under corresponding operating parameters based on the variation law of the lateral interference factor, and generating interference prediction results for the parallel synchronous water discharge of the target vehicle assembly based on the critical lateral spacing of the target vehicle assembly under corresponding operating parameters, includes:

[0025] When the lateral interference factor changes in the manner that the lateral interference factor decreases to a preset threshold as the lateral spacing increases, the lateral spacing corresponding to the lateral interference factor change is taken as the critical lateral spacing of the target vehicle combination under the corresponding operating parameters.

[0026] The critical lateral spacing of the target vehicle assembly under the corresponding operating parameters is analyzed under the multiple sets of operating parameters. Based on the correlation between the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters and the initial motion velocity in the multiple sets of operating parameters, the interference prediction result of the target vehicle assembly's parallel synchronous water discharge is generated.

[0027] The first aspect of this application provides a method for predicting interference during the parallel synchronous launch of underwater vehicles. This method involves acquiring the geometric parameters and multiple sets of operating parameters of a target underwater vehicle assembly; simulating the parallel synchronous launch process of the target underwater vehicle assembly using an initial interference prediction model based on these operating parameters to obtain the loads on each vehicle in the assembly during the parallel synchronous launch process; calculating the lateral interference factor of each vehicle in the assembly based on the loads during the parallel synchronous launch process; and generating interference prediction results based on the lateral interference factors and corresponding operating parameters of each vehicle in the assembly. This method can accurately simulate the dual-engine synchronous launch process using the vehicle geometry and operating parameters, combined with a multiphysics network prediction model, quantifying the interference factor and defining the critical spacing, thus providing reliable data support for underwater equipment design.

[0028] To achieve the above objectives, a second aspect of the present invention provides a system for predicting interference in parallel synchronous water exit of a vessel, the system comprising:

[0029] The acquisition module is used to acquire the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; the target vehicle assembly includes at least a first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operating parameters include the lateral spacing, the initial velocity, and the launch time, wherein the lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time.

[0030] The simulation module is used to simulate the parallel and synchronous water release process of the target ship combination based on the multiple sets of operating condition parameters and through an initial disturbance prediction model, so as to obtain the load of each ship in the target ship combination during the parallel and synchronous water release process; the initial disturbance prediction model is constructed based on the geometric parameters of the target ship combination and the multiple sets of operating condition parameters.

[0031] The calculation module is used to calculate the lateral interference factor of each vehicle in the target vehicle assembly based on the load during the parallel synchronous water release process of each vehicle in the target vehicle assembly.

[0032] The generation module is used to generate interference prediction results for the parallel synchronous water discharge of the target navigation body combination based on the lateral interference factors and corresponding operating parameters of each navigation body in the target navigation body combination.

[0033] 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 navigation vehicle emergence.

[0034] 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 and synchronous water discharge of a navigation vessel.

[0035] 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

[0036] 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:

[0037] Figure 1 This is a flowchart illustrating a method for predicting interference in parallel synchronous water exit of a vessel, as provided in an embodiment of this application.

[0038] Figure 2 This is a schematic diagram of a parallel and synchronous launch of a watercraft provided in an embodiment of this application;

[0039] Figure 3 This is a schematic diagram of a mesh generation method provided in an embodiment of this application;

[0040] Figure 4 This is a schematic diagram of the phase distribution cloud map, pressure distribution cloud map, and cavitation three-dimensional morphology map of the two-body water effluent process provided in the embodiments of this application;

[0041] Figure 5 This is a schematic diagram showing the distribution of stress and elastic strain of the left-hand engine hull during the cavitation collapse stage, as provided in an embodiment of this application.

[0042] Figure 6 This is a schematic diagram provided in an embodiment of the present application, showing that the stress and strain at monitoring points in various orientations exhibit a periodic fluctuation trend during the cavitation development stage.

[0043] Figure 7 This is a schematic diagram of the structure of a parallel synchronous water exit interference prediction system for a navigation body provided in an embodiment of this application;

[0044] Figure 8 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application;

[0045] 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 based on multiple sets of operating condition parameters and uses an initial disturbance prediction model to simulate the parallel synchronous water discharge process of the target navigation body combination, so as to obtain the load of each navigation body in the target navigation body combination during the parallel synchronous water discharge process. Figure 1 S130 is to calculate the lateral interference factor of each vehicle in the target vehicle assembly based on the load during the parallel synchronous water release process of each vehicle in the target vehicle assembly; Figure 1 S140 is the interference prediction result of the parallel synchronous water discharge of the target navigation body combination based on the lateral interference factor of each navigation body in the target navigation body combination and the corresponding operating parameters. Figure 7 710 is the acquisition module; Figure 7 The 720 is an analog module; Figure 7 The 730 module is a computing module. Figure 7 740 is the generation module. Detailed Implementation

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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.

[0050] The underwater launch and surfacing process of submarines is a key technological aspect of the development of new underwater equipment, directly impacting its combat effectiveness and mission adaptability. With increasing demands for firepower density and penetration probability, the parallel synchronous surfacing launch mode of twin-engine submarines has become an important direction for underwater equipment development due to its significant enhancement of combat capabilities. In this mode, the two submarines must launch synchronously and in close proximity, involving complex multi-body interference dynamics problems. Their flow structure and load characteristics undergo fundamental changes compared to single-engine surfacing, posing higher requirements for engineering design and safety assessment.

[0051] Current numerical simulations of multi-focus single-body launch scenarios for aircraft carriers lack clarity regarding multi-body interference mechanisms and quantitative analysis methods, failing to accurately describe hydrodynamic interactions and load asymmetry. Furthermore, existing simulation and prediction technologies applied to dual-engine parallel launch scenarios rely on unidirectional or weakly coupled algorithms, which cannot meet the computational accuracy requirements of transient high-impact processes, resulting in insufficient prediction accuracy and reliability. This, in turn, restricts the engineering application of dual-engine parallel launch technology.

[0052] Based on this, the embodiments of this application provide a method and system for predicting interference in parallel synchronous launch of underwater vehicles. The aim is to simulate the synchronous launch process of two engines with high precision by combining the geometric and operating parameters of the underwater vehicle with the prediction model of a multiphysics network, quantify the interference factor and define the critical spacing, and provide reliable data support for the design of underwater equipment.

[0053] The method and system for predicting interference of parallel and synchronous water discharge of navigation bodies provided in this application are specifically described through the following embodiments. First, the method for predicting interference of parallel and synchronous water discharge of navigation bodies in this application is described.

[0054] 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.

[0055] 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.

[0056] The method for predicting interference from parallel synchronous water discharge of aircraft 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 synchronous water discharge of aircraft, but is not limited to the above forms.

[0057] 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.

[0058] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0059] Therefore, referring to Figure 1 This application provides a method for predicting interference in parallel synchronous 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.

[0060] Step S110: Obtain the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; the target vehicle assembly includes at least a first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operating parameters include the lateral spacing, the initial velocity, and the launch time. The lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time.

[0061] Step S120: Based on multiple sets of operating condition parameters, simulate the parallel synchronous water release process of the target ship combination through the initial disturbance prediction model to obtain the load of each ship in the target ship combination during the parallel synchronous water release process; the initial disturbance prediction model is constructed based on the geometric parameters of the target ship combination and multiple sets of operating condition parameters.

[0062] Step S130: Calculate the lateral interference factor of each vehicle in the target vehicle assembly based on the load during the parallel synchronous water release process of each vehicle in the target vehicle assembly.

[0063] Step S140: Based on the lateral interference factors and corresponding operating parameters of each vessel in the target vessel combination, generate the interference prediction results for the parallel synchronous water discharge of the target vessel combination.

[0064] In this step, the target vehicle assembly comprises at least two vehicles. By collecting geometric parameters such as the diameter of the first vehicle and the diameter of the second vehicle, the basic structural features of each vehicle are determined, providing a basis for subsequent geometric modeling. Furthermore, by combining operational parameters such as the lateral spacing (i.e., the initial horizontal distance between the axes of the two vehicles), initial velocity, and launch time, the layout and initial motion state of the dual-engine parallel synchronous launch are directly reflected, thus identifying key variables affecting the multi-body interference effect.

[0065] Furthermore, based on the geometric parameters and multiple sets of operating parameters of each aircraft, an initial disturbance prediction model adapted to the specific combination of aircraft and operating conditions is first constructed (this model integrates sub-networks such as multiphase flow field calculation, cavitation effect simulation, and fluid-structure interaction control, and includes overlapping grid regions to adapt to the synchronous motion of the two aircraft). Then, the entire process of the parallel synchronous water release of the two aircraft is dynamically reproduced through this initial disturbance prediction model.

[0066] During the simulation, the initial disturbance prediction model captures flow field characteristics such as gas-liquid interface evolution and cavitation generation and collapse in real time, and simultaneously outputs various loads (such as nose impact load and side surface pressure difference load) experienced by the two vehicles during motion, providing data support for subsequent quantitative analysis of disturbance effects. The initial disturbance prediction model includes motion models of the first and second vehicles.

[0067] Specifically, the initial disturbance prediction model also includes a multiphase flow field calculation subnetwork, a cavitation effect simulation subnetwork, and a fluid-structure interaction control subnetwork. The multiphase flow field calculation subnetwork is used to capture the dynamic evolution of the gas-liquid two-phase interface, the cavitation effect simulation subnetwork is used to calculate the generation and collapse process of surface cavitation bubbles of each vehicle in the target vehicle assembly, and the fluid-structure interaction control subnetwork is used to realize the real-time interaction between the flow field load and the vehicle motion.

[0068] Furthermore, by comparing and analyzing the load data of each aircraft under the dual-engine parallel operation condition with the benchmark load under the corresponding single-engine water-out operation condition, the lateral interference factor was calculated. The lateral interference factor can intuitively reflect the strength of the hydrodynamic interference between the two aircraft, thus realizing the transformation of complex flow field interference into a quantifiable index, laying the foundation for subsequent pattern analysis.

[0069] Specifically, the formula for calculating the lateral interference factor is as follows:

[0070] ;

[0071] in, For horizontal spacing of The diameter of each vehicle in the combination with the target vehicle is correspond Lateral interference factor at launch time, This refers to the horizontal spacing. The diameter of each vessel in the target vessel assembly. Normalized position coordinates The first sailing body has an axial spacing of correspond Payload at launch time The second sailing body has an axial spacing of correspond The payload at launch time.

[0072] Furthermore, by correlating the lateral interference factors of each aircraft with the corresponding operating parameters (such as lateral spacing and initial velocity), the law of variation of interference factors with operating parameters can be summarized (for example, the trend of lateral interference factors weakening as lateral spacing increases). This allows for the determination of key design parameters such as critical lateral spacing to ensure that interference is within an acceptable range, ultimately forming interference prediction results that guide engineering practice and realizing the transformation from data simulation to engineering application.

[0073] In one embodiment, based on the method for predicting interference from parallel and synchronous water discharge of aircraft, a four-in-one technical framework of "parametric modeling - dedicated mesh - tightly coupled solution - quantitative evaluation" is constructed to realize the systematic analysis and engineering design optimization of multi-body interference effects. The specific implementation steps are as follows:

[0074] Step 1: Geometric Modeling and Definition of Synchronous Motion Configuration

[0075] In this step, two airframe models with identical geometric properties are first created. Their spatial relative positions are defined using a parametric method, with the lateral spacing being the core variable. (i.e., the horizontal distance between the axes of the two aircraft carriers), and its preferred value is 1.3. ≤ ≤2.1 ( (where Z is the diameter of the aircraft). To focus on the lateral interference effect, the axial spacing Z is set to 0 to ensure that the two aircraft are in a strictly parallel and synchronous motion configuration. A sufficiently large background computational domain is created in computational fluid dynamics software (such as StarCCM+) to encompass the entire motion of the aircraft and eliminate boundary effects.

[0076] Step 2: Establishment of Multiphysics Control Model and Targeted Mesh Generation Strategy

[0077] In this step, the physical model is first established, specifically based on the following governing equations to construct the numerical calculation system. For fluid dynamics control, the volumetric fluid method (VOF) model is used to capture the water-gas-vapor three-phase interface, and its governing equations are phase fraction transport equations, expressed as follows:

[0078] ;

[0079] in, It represents the three phases: water, gas, and steam; that is, the phase representation. for The volume fraction of all phases at every point in space is equal to 1 (e.g., ...). This determines the position of the interface; It refers to the launch time, which is a time variable in transient simulation; Here, is the divergence operator, representing the net outflow of the vector field; The velocity vector is preferably obtained by solving the fluid momentum equation (Navier-Stokes equations) in a coupled solution with the volume fraction equation. for Mass source item - per unit volume per unit time The mass production rate is calculated using cavitation models (such as Schnerr-Sauer); for example, when the local pressure is below the saturated vapor pressure, water ( It will evaporate into steam. )at this time, , ; for The density.

[0080] Furthermore, a Realizable k-ε turbulence model is used to accurately simulate the complex shear flow and vortex structure around the vehicle, while a Schnerr-Sauer cavitation model is used to simulate the phase transition process of cavitation. For structural dynamics control, a Johnson-Cook plastic dynamic constitutive model is used to describe the dynamic response of the vehicle under impact loads such as cavitation collapse, and its constitutive relation expression is as follows:

[0081] ;

[0082] in, For flow stress; This represents the internal calculation results of the structural solver when calculating the elastic-plastic response of materials. This is the initial yield stress; The strain hardening coefficient; To control the strain rate sensitivity coefficient in the volume; The equivalent plastic strain is calculated based on the cumulative deformation history of the elements during the structural solution process; The strain hardening index; It is the natural logarithm of the dimensionless strain rate, which is calculated in real time by the structural solver based on the deformation rate of the model. Dimensionless temperature; This is the temperature softening index.

[0083] Specifically, the structural motion is governed by the equations of elastic dynamics, the expression of which is as follows:

[0084] ;

[0085] in, The divergence of the stress tensor; The Cauchy stress tensor is a second-order tensor that describes the stress state at various points inside a solid. It is determined by the constitutive model (the Johnson-Cook model above) and geometric deformation, and is one of the core solution variables of the structural solver. This is the volume force vector, which is the external force acting on a unit volume. It is set as a boundary condition before the simulation. The density is a solid density, which is preset as a material property at the start of the simulation. The displacement vector of the structure is the core variable that the structural solver ultimately needs to solve. After the displacement is solved, the strain and stress can be further calculated. It is a displacement vector.

[0086] Furthermore, a narrow, elongated volumetric mesh refinement region is created between the two vessels. The mesh size of this refinement region is significantly finer than the background mesh, specifically designed to analyze complex pressure waves and vortex interference caused by variations in lateral spacing. An overlapping mesh region is independently created for each vessel, endowing it with six degrees of freedom of motion to handle large displacements during synchronized water exit. The size of this volumetric mesh refinement region is related to the lateral spacing. It exhibits dynamic correlation to ensure consistent simulation accuracy across different spacing conditions.

[0087] Step 3: Bidirectional tightly coupled solution and synchronous monitoring of interference data:

[0088] In this step, symmetrical boundary conditions are used to handle the strictly symmetrical dual-engine model, which improves computational efficiency by approximately 100% while ensuring the accuracy of the calculation results. Furthermore, a tightly coupled bidirectional computation is achieved by coupling the fluid solver (StarCCM+) and the structural solver (Abaqus) through a co-simulation engine (such as SIMULIA).

[0089] Specifically, within each time step, the fluid domain transfers pressure and shear loads to the structural domain, while the structural domain feeds back the calculated deformations and displacements to the fluid domain. Implicit iteration ensures the synchronicity and convergence of data exchange. During the solution process, the motion parameters, surface loads, and flow field information between the two engines are monitored in parallel, providing a data foundation for subsequent disturbance analysis.

[0090] Step 4: Quantitative evaluation of interference effects based on lateral spacing:

[0091] In this step, the simulation results for different lateral spacing conditions are post-processed to achieve a quantitative assessment of the interference effect. Specifically, for load asymmetry analysis, a dimensionless lateral interference factor is defined. As a core evaluation indicator, it clearly characterizes the instantaneous intensity of interference at a specific lateral spacing. The formula for calculating the lateral interference factor is as follows:

[0092] ;

[0093] in, For horizontal spacing of The diameter of each vehicle in the combination with the target vehicle is correspond The transverse interference factor at launch time is a normalized relative difference—a metric used to quantify the relative difference between two quantities. This refers to the horizontal spacing; The diameter of each vessel in the target vessel assembly; These are normalized position coordinates, i.e., dimensionless position coordinates. The first sailing body has an axial spacing of correspond The payload at the moment of launch; The second sailing body has an axial spacing of correspond The payload at the moment of launch; , The corresponding loads of each vehicle at the same time, that is, the corresponding loads (such as lateral force, bending moment, etc.) experienced by the first and second vehicles at the same time.

[0094] Furthermore, the peak values ​​of the interference factors were analyzed. With lateral spacing The changing patterns of the interference factor are analyzed, and a relationship curve is plotted. The critical lateral spacing is defined as the spacing at which the interference factor significantly decreases to an acceptable level, providing a crucial "safety threshold" for engineering layout. Furthermore, the calculation results from all operating conditions are integrated to form a database indexed by lateral spacing, covering key performance parameters such as maximum outlet load, bending moment, and interference factor, providing direct and quantitative data support for optimized design. Specifically, the critical lateral spacing can be quantified as when... Descending to The spacing value when the corresponding peak value is 30%-50%.

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

[0096] Step a: Parametric geometric modeling and computational domain setting:

[0097] First, two identical airframe models are created, and their relative spatial positions are defined using a parametric method. For example... Figure 2 As shown, the coordinate system is defined with vertically upward as z and horizontally to the right as x. The water surface is the free surface. The left vehicle is called the first vehicle, and the right vehicle is called the second vehicle. The cavitation generated by the left vehicle is called the left cavity, and the cavitation generated by the right vehicle is called the right cavity. The lateral spacing is X. The axial spacing is set to zero to ensure that the heads of the two vehicles are aligned. The lateral spacing is the core variable, with a value range of 1.3D-2.1D (D is the diameter of the vehicle). A sufficiently large background computational domain is then created in the fluid to ensure that it can encompass the complete motion trajectory of the vehicles, and an independent cylindrical overlapping mesh region is created for each vehicle.

[0098] Step b: Physical model creation and dedicated mesh generation:

[0099] The physical continuum selects a three-dimensional implicit unsteady-state solver and activates the multiphase flow VOF model, the Realizable k-ε turbulence model, the Schnerr-Sauer cavitation model, and the overlapping mesh technique. It also assigns two vehicle regions to six-degree-of-freedom moving bodies and defines synchronous motion.

[0100] Furthermore, the background computational domain is divided using a cut volume mesh to create three core encrypted regions: a global flow encrypted region, a free surface encrypted region, and a transverse interference channel encrypted region (located between the two vehicles, using a fine volume mesh). Prism layer meshes are set on the surface of the vehicles to ensure near-wall flow resolution, and meshes are divided for overlapping mesh areas to ensure a smooth transition with the interference channel encrypted region.

[0101] like Figure 3As 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. The maximum velocity in the simulation study is 40 m / s, and the solution time step is 1e-4 s. Calculations show that the mesh generation strategy meets the CFL stability criterion, and the number of meshes in the simulated flow field is approximately 3 million.

[0102] Step c: Structural model and co-simulation configuration:

[0103] A hull model of the aircraft is created in the solids module, specifying the thickness parameter. A Johnson-Cook plastic material model is defined, with corresponding material constants input. A dynamic implicit analysis step is created, a suitable time step is set, and a finite element mesh is generated using S4R shell elements. The co-simulation function of the solids module is then initiated. Two independent fluid-structure interaction interfaces are established, and co-simulation parameters, including total time, time step, and data exchange frequency, are set.

[0104] Step d: Boundary condition setting and solution calculation:

[0105] First, the computational domain boundary conditions are set, with the outer boundary using pressure outlet conditions. Then, the flow field is initialized, defining the hydrostatic pressure gradient and water phase distribution, and setting the initial position and velocity of the vehicle. Further, the field output and historical output parameters are set, a real-time monitor is created to track key physical quantities, and co-simulation calculations are initiated.

[0106] Step e: Quantitative analysis of interference effects:

[0107] By extracting load time history data from corresponding positions of the two aircraft carriers, the variation of the lateral interference factor over time is calculated. Parametric analysis is then performed. Specifically, by changing the lateral spacing parameter, multi-condition calculations are conducted to analyze the trend of the peak interference factor with lateral spacing. Based on this trend, a design parameter database is constructed to establish a quantitative relationship between lateral spacing and interference effects.

[0108] Furthermore, the critical lateral spacing threshold is determined, and layout optimization suggestions are proposed to provide a basis for engineering design. This allows for a systematic numerical analysis of the fluid-structure interaction of parallel, synchronously launching twin-engine aircraft, providing quantitative guidance for launch system design and effectively solving the challenge of accurately predicting multi-body interference effects.

[0109] like Figure 4 As shown, Figure 4 The phase distribution cloud diagram, pressure distribution cloud diagram, and cavitation morphology diagram of the twin-engine launch process at a launch velocity σ=0.24 are presented. Specifically, observation of the pressure cloud diagram reveals that the pressure distribution around the twin-engine launchers is symmetrical along the centerline of the computational domain, and the high-pressure regions at the head and tail stagnation points of the left and right launchers, as well as the low-pressure regions at the shoulders, merge. For clarity, the two sides closest to each other in the middle of the twin-engine launchers are referred to as adjacent sides, and the other two sides as opposite sides. Due to the merging of the low-pressure regions at the shoulders, the low-pressure regions on the adjacent sides of the twin-engine launchers gradually expand, causing the pressure distribution on both sides of a single launcher to become asymmetrical, thus affecting the evolution of the cavitation morphology. The phase diagram and cavitation morphology diagram visually demonstrate that the cavitation length on the adjacent sides is significantly greater than that on the opposite sides, and the cavitation tip contour line is tilted. At T=160ms, the head of the vehicle reaches the water surface, so the motion process remains unchanged. At this time, the cavitation tip is gradually detached and collapses due to interference from the back jet. From 160 to 210ms, the cavitation collapses under the influence of the water surface. It can be seen that at 190ms, due to the deflection of the vehicle, the contact line between the water surface and the cavitation is no longer straight. At T=210ms, the cavitation on the opposite side has completely collapsed, leaving only the adjacent cavitation to collapse as a whole, generating a significant high-pressure peak. This shows that in a catamaran... Under flow disturbance, the evolution morphology and process of cavitation changed. The cavitation morphology changed from uniform distribution to asymmetrical distribution, with adjacent side cavitation being longer. At the same time, the overall collapse time of adjacent and opposite side cavitation was no longer consistent, with the opposite side cavitation collapsing earlier. This indicates that the development of adjacent side cavitation was more stable, and also suggests that the forces on both sides of the vehicle were not synchronized, and the degree of water exit deflection was aggravated. In addition, the time for the completion of cavitation collapse throughout the entire process was delayed from 195ms to 210ms, indicating that the cavitation evolution time during the two-body water exit process was longer.

[0110] like Figure 5 As shown, Figure 5The cloud map reflects the distribution of stress and elastic strain in the left-hand engine hull during the cavitation collapse stage. It can be observed that the stress and strain distribution in the cavitation collapse zone changes from a ring-like pattern to a single point, similar to the situation of a single-unit hull emerging from the water under crossflow conditions, and this point is located on the adjacent side of the twin-engine hull. This is because the cavitation distribution on both sides of the hull is asymmetrical, and the hull deflects significantly during the water emergence process, resulting in asynchronous cavitation collapse on both sides. Therefore, it is known that only the adjacent side cavitation collapses completely in the later stage of the water emergence phase. Furthermore, the figure shows that the peak values ​​of stress and elastic strain under typical twin-hull water emergence conditions are 107.80 MPa and 0.9096 × 10⁻⁶ MPa, respectively. -3 The stress values ​​were 1.76 times and 1.65 times those of the typical single-unit effluent condition, respectively. The collapse time was 221ms, and the collapse axial position was 2.120m, which was consistent with the position of the cavitation end on the adjacent side. Compared with the typical single-unit effluent condition, the stress peak increased, time lag occurred, and the location shifted backward.

[0111] like Figure 6 As shown, during the cavitation development stage, the stress and strain at each monitoring point exhibited a periodic fluctuation trend. With the increased randomness of stress and strain development during cavitation collapse, the magnitude, location, and timing of peak values ​​varied across different locations. The right side of the vehicle exhibited the largest stress and strain peak, similar to the pressure distribution, further illustrating the strong correlation between pressure and stress.

[0112] In some embodiments, before step S120, which simulates the parallel synchronous water release process of the target vessel assembly based on multiple sets of operating condition parameters using an initial disturbance prediction model to obtain the loads of each vessel in the target vessel assembly during the parallel synchronous water release process, the following steps S210 to S220 are further included:

[0113] Step S210: Determine the background computational domain based on the geometric parameters of the target vehicle assembly; the background computational domain covers the motion trajectory and flow field influence area of ​​each vehicle in the target vehicle assembly.

[0114] Step S220: Based on the lateral spacing and geometric parameters, divide the overlapping grid region in the background computational domain and construct the initial interference prediction model; the overlapping grid region includes the near-field grid sub-region of each vehicle in the target vehicle combination and the common grid sub-region of the flow field.

[0115] In this embodiment, the computational space is defined based on the geometric parameters of the vehicles (such as diameter and length) to ensure that the computational domain can fully cover the entire motion trajectory of the two vehicles during the synchronous water exit process, as well as the area of ​​the flow field affected by the disturbance of the vehicles. This provides a basic spatial boundary for subsequent simulations of flow field evolution and load transfer, and is a prerequisite for ensuring the authenticity of the flow field calculation.

[0116] Furthermore, through mesh generation and model construction, the background computational domain is transformed into a digital carrier capable of performing simulations. Based on the lateral spacing (the horizontal distance between the initial axes of the two vessels) and geometric parameters (such as the diameter of each vessel), overlapping mesh regions are divided in the background computational domain. This achieves both adaptability to the relative positional changes during the synchronous movement of the two vessels, avoiding interference problems of traditional meshing techniques, and balancing computational accuracy and efficiency through differentiated mesh density.

[0117] Among them, the near-field grid sub-region is set up separately for each vehicle, and a high-density grid is used to accurately capture the details of the flow field on the surface of the vehicle (such as cavitation generation and pressure distribution); the flow field common grid sub-region covers the flow field space affected by the overlap of two vehicles, and is used to transmit the flow field interference information between multiple vehicles.

[0118] In some embodiments, before step S120, which simulates the parallel synchronous water release process of the target vessel combination based on multiple sets of operating condition parameters using an initial disturbance prediction model to obtain the load during the parallel synchronous water release process of the target vessel combination, the following steps S310 to S320 are further included:

[0119] Step S310: Based on the launch time, define the motion model of the first spacecraft and the motion model of the second spacecraft; both the motion models of the first spacecraft and the motion models of the second spacecraft are constructed based on the six-degree-of-freedom motion body and the Johnson-Cook plastic material model;

[0120] Step S320: Construct fluid-structure interaction interfaces for the motion models of the first and second vehicles, respectively, and set the simulation parameters of the initial interference prediction model.

[0121] In this embodiment, the launch time is used as the time reference. By coordinating the starting points of the first and second vehicles, the "synchronization" characteristic is ensured in the model. At the same time, the motion model adopts a six-degree-of-freedom motion body model, which can comprehensively describe the translation (forward and backward, left and right, up and down) and rotation (pitch, yaw, roll) motions of the vehicles during the water exit process, covering complex attitude changes.

[0122] Furthermore, the Johnson-Cook plastic material model was introduced to specifically adapt to the scenario of the vehicle being subjected to transient high impact loads when it emerges from the water at high speed. This accurately reflects the plastic deformation behavior of the material under high strain rate and high pressure, avoids structural response deviations caused by simplification of material properties, and provides a real structural mechanics basis for subsequent load calculations.

[0123] Furthermore, by constructing fluid-structure interaction interfaces for the motion models of the two vehicles, the paths through which fluid loads (such as pressure and viscous forces) are transmitted to the vehicles, as well as the feedback channels of vehicle motion (position and attitude changes) to the flow field boundary, are clarified, ensuring that the bidirectional coupling effect of "flow field influencing motion and motion reacting to flow field" is accurately captured. At the same time, simulation parameters (such as time step, iteration convergence conditions, and calculation accuracy level) are set, and the calculation efficiency and result reliability are balanced through parameter optimization, laying a core foundation for high-precision simulation of the parallel synchronous water release process of the two-engine vehicles.

[0124] In some embodiments, in step S140, based on the lateral interference factors and corresponding operating parameters of each vessel in the target vessel assembly, an interference prediction result for the parallel synchronous water discharge of the target vessel assembly is generated, including the following steps S410 to S420:

[0125] Step S410: Analyze the lateral interference factor and corresponding operating parameters of each vehicle in the target vehicle assembly to obtain the variation law of the lateral interference factor; the variation law of the lateral interference factor includes the variation trend of the lateral interference factor of each vehicle in the target vehicle assembly with the lateral spacing in the operating parameters.

[0126] Step S420: Based on the variation law of the lateral interference factor, determine the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters, so as to generate the interference prediction result of the target vehicle assembly's parallel synchronous water discharge according to the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters.

[0127] In this embodiment, by comparing multiple sets of working condition data with different lateral spacing, the core law that the interference factor gradually weakens as the lateral spacing increases is clarified. At the same time, the influence of other working condition parameters such as initial motion speed is taken into account, and the scattered simulation data is transformed into quantifiable and traceable change laws, providing data support for subsequent threshold determination.

[0128] Furthermore, based on the above-mentioned variation pattern, the critical lateral spacing required for engineering design is further defined, and the lateral spacing corresponding to when the lateral interference factor drops to a preset reasonable range (such as 30%-50% of the peak value of a single unit) is clarified. This spacing is the critical value that can balance the compactness of the launch layout and the interference safety.

[0129] Furthermore, based on the critical lateral spacing, the generated interference prediction results are integrated with the variation spectrum of interference factors with various operating parameters, providing a quantitative basis for the layout optimization and spacing design of the parallel synchronous launch system of twin-engine aircraft, thus solving the problem of traditional design relying on conservative experience or high-cost experiments.

[0130] In some embodiments, in step S420, the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters is determined based on the variation law of the lateral interference factor. Based on the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters, interference prediction results for the parallel synchronous water discharge of the target vehicle assembly are generated, including the following steps S510 to S520:

[0131] Step S510: When the lateral interference factor changes in the manner that the lateral interference factor decreases to a preset threshold after the lateral spacing increases, the lateral spacing corresponding to the lateral interference factor change is taken as the critical lateral spacing of the target vehicle assembly under the corresponding working parameters.

[0132] Step S520: Analyze the critical lateral spacing of the target vehicle assembly under multiple sets of operating parameters, and generate the interference prediction results of the target vehicle assembly's parallel synchronous water discharge based on the correlation between the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters and the initial motion velocity in multiple sets of operating parameters.

[0133] In this embodiment, when the interference factor drops to a preset acceptable threshold, the corresponding lateral spacing is determined as the critical lateral spacing under the current working condition, thereby transforming the abstract interference level into a clear spatial size threshold and solving the problem of no quantitative standard for spacing selection in traditional design.

[0134] Furthermore, since the initial velocity affects the disturbance intensity of the airborne vehicle on the flow field, by analyzing multiple sets of critical lateral spacing under different operating conditions, we focus on exploring its correlation with the initial velocity, and then change the value of the critical lateral spacing (for example, a larger critical spacing is required to control interference during high-speed launch).

[0135] Furthermore, by integrating these related data, the final interference prediction results not only include the critical spacing for a single operating condition, but also form a correlation curve of "initial motion velocity - critical lateral spacing" and a multi-operating condition interference map. This can directly provide accurate guidance for the layout design of twin-engine aircraft under different launch speeds, realize the upgrade from "single operating condition analysis" to "multi-scenario general design", and give full play to the engineering value of parametric analysis.

[0136] like Figure 7 As shown in some embodiments of this application, a system for predicting interference in parallel synchronous water emergence of a vessel is provided. The system includes an acquisition module 710, a simulation module 720, a calculation module 730, and a generation module 740. Specifically:

[0137] The acquisition module 710 is used to acquire the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; the target vehicle assembly includes at least a first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operating parameters include the lateral spacing, the initial velocity, and the launch time. The lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time.

[0138] The simulation module 720 is used to simulate the parallel synchronous water release process of the target ship combination based on multiple sets of operating condition parameters and an initial disturbance prediction model, so as to obtain the loads of each ship in the target ship combination during the parallel synchronous water release process; the initial disturbance prediction model is constructed based on the geometric parameters of the target ship combination and multiple sets of operating condition parameters.

[0139] The calculation module 730 is used to calculate the lateral interference factor of each vehicle in the target vehicle assembly based on the load during the parallel synchronous water release process of each vehicle in the target vehicle assembly.

[0140] The generation module 740 is used to generate interference prediction results for the parallel synchronous water discharge of the target navigation body combination based on the lateral interference factors and corresponding operating parameters of each navigation body in the target navigation body combination.

[0141] It should be noted that the parallel synchronous water discharge interference prediction system for ships provided in this embodiment is based on the same inventive concept as the above-mentioned parallel synchronous water discharge interference prediction method for ships. Therefore, the relevant content of the above-mentioned parallel synchronous water discharge interference prediction method for ships also applies to the content of the parallel synchronous water discharge interference prediction system for ships. Therefore, it will not be repeated here.

[0142] To this end, the system acquires the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; based on these parameters, it simulates the parallel synchronous launch process of the target vehicle assembly using an initial interference prediction model to obtain the loads on each vehicle in the assembly during the parallel synchronous launch process; based on the loads on each vehicle in the assembly, it calculates the lateral interference factor of each vehicle; and based on the lateral interference factor and corresponding operating parameters of each vehicle, it generates the interference prediction results for the parallel synchronous launch of the target vehicle assembly. In this way, it can achieve high-precision simulation of the dual-engine synchronous launch process using vehicle geometry and operating parameters combined with a multiphysics network prediction model, quantify the interference factor, and define the critical spacing, providing reliable data support for underwater equipment design.

[0143] 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 and synchronous water discharge of the navigation body.

[0144] 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 and synchronous water discharge of a vessel.

[0145] 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.

[0146] 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 8 The 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.

[0147] 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.

[0148] 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 synchronous water exit of aircraft, 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 first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operational parameters include the lateral spacing, the initial velocity, and the launch time, wherein the lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time; Based on the multiple sets of operating parameters, the parallel synchronous water release process of the target ship combination is simulated through an initial interference prediction model to obtain the loads of each ship in the target ship combination during the parallel synchronous water release process; the initial interference prediction model is constructed based on the geometric parameters of the target ship combination and the multiple sets of operating parameters. Based on the loads of each vessel in the target vessel assembly during the parallel synchronous water exit process, calculate the lateral interference factor of each vessel in the target vessel assembly. The lateral interference factor and corresponding operating parameters of each vessel in the target vessel combination are analyzed to obtain the variation law of the lateral interference factor; the variation law of the lateral interference factor includes the variation trend of the lateral interference factor of each vessel in the target vessel combination with the lateral spacing in the operating parameters. When the lateral interference factor changes in the manner that the lateral interference factor decreases to a preset threshold as the lateral spacing increases, the lateral spacing corresponding to the lateral interference factor change is taken as the critical lateral spacing of the target vehicle combination under the corresponding operating parameters. The critical lateral spacing of the target vehicle assembly under the corresponding operating parameters is analyzed under the multiple sets of operating parameters. Based on the correlation between the critical lateral spacing of the target vehicle assembly under the corresponding operating parameters and the initial motion velocity in the multiple sets of operating parameters, the interference prediction result of the target vehicle assembly's parallel synchronous water discharge is generated.

2. The method for predicting interference from parallel synchronous water exit of a vessel according to claim 1, characterized in that, Before simulating the parallel and synchronous water release process of the target vessel assembly based on the multiple sets of operating parameters using an initial disturbance prediction model to obtain the loads of each vessel in the target vessel assembly during the parallel and synchronous water release process, the method further includes: Based on the geometric parameters of the target vehicle assembly, a background computational domain is determined; the background computational domain covers the motion trajectory and flow field influence area of ​​each vehicle in the target vehicle assembly. Based on the lateral spacing and the geometric parameters, overlapping grid regions are divided in the background computation domain, and the initial interference prediction model is constructed; the overlapping grid regions include the near-field grid sub-regions of each vehicle in the target vehicle assembly and the common flow field grid sub-regions.

3. The method for predicting interference during parallel synchronous water exit of a vessel according to claim 1, characterized in that, The initial disturbance prediction model includes a motion model of the first vessel and a motion model of the second vessel. Before simulating the parallel and synchronous water discharge process of the target vessels based on the multiple sets of operating parameters using the initial disturbance prediction model to obtain the load during the parallel and synchronous water discharge process of the target vessels, the method further includes: Based on the launch time, motion models of the first and second spacecraft are defined; both motion models of the first and second spacecraft are constructed based on a six-degree-of-freedom motion body and the Johnson-Cook plastic material model. For the motion models of the first and second vehicles respectively, a fluid-structure interaction interface is constructed, and the simulation parameters of the initial interference prediction model are set.

4. The method for predicting interference from parallel synchronous water exit of a vessel according to claim 1, characterized in that, The initial disturbance prediction model includes a multiphase flow field calculation subnetwork, a cavitation effect simulation subnetwork, and a fluid-structure interaction control subnetwork. The multiphase flow field calculation subnetwork is used to capture the dynamic evolution of the gas-liquid two-phase interface. The cavitation effect simulation subnetwork is used to calculate the generation and collapse process of surface cavitation bubbles of each vehicle in the target vehicle assembly. The fluid-structure interaction control subnetwork is used to realize the real-time interaction between the flow field load and the vehicle motion.

5. The method for predicting interference during parallel synchronous water exit of a vessel according to claim 1, characterized in that, The formula for calculating the lateral interference factor is as follows: ； in, For the horizontal spacing is The diameter of each vessel in the target vessel assembly is correspond Lateral interference factor at launch time, The horizontal spacing is... The diameter of each vessel in the target vessel assembly is defined as the vessel diameter. Normalized position coordinates The first sailing body has an axial spacing of correspond Payload at launch time The second sailing body has an axial spacing of correspond The payload at launch time.

6. A system for predicting interference during parallel synchronous water exit of a vessel, characterized in that, The system includes: The acquisition module is used to acquire the geometric parameters and multiple sets of operating parameters of the target vehicle assembly; the target vehicle assembly includes at least a first vehicle and a second vehicle, the geometric parameters include at least the diameter of the first vehicle and the diameter of the second vehicle, and the operating parameters include the lateral spacing, the initial velocity, and the launch time, wherein the lateral spacing is the horizontal distance between the axes of the first vehicle and the second vehicle at the initial time. The simulation module is used to simulate the parallel and synchronous water release process of the target ship combination based on the multiple sets of operating condition parameters and through an initial disturbance prediction model, so as to obtain the load of each ship in the target ship combination during the parallel and synchronous water release process; the initial disturbance prediction model is constructed based on the geometric parameters of the target ship combination and the multiple sets of operating condition parameters. The calculation module is used to calculate the lateral interference factor of each vehicle in the target vehicle assembly based on the load during the parallel synchronous water release process of each vehicle in the target vehicle assembly. The generation module is used to analyze the lateral interference factors and corresponding operating parameters of each vessel in the target vessel assembly, and to obtain the variation law of the lateral interference factors. The variation law of the lateral interference factors includes the variation trend of the lateral interference factors of each vessel in the target vessel assembly with the lateral spacing in the operating parameters. When the variation law of the lateral interference factors is that the lateral interference factors decrease to a preset threshold after the lateral spacing increases, the lateral spacing corresponding to the variation law of the lateral interference factors is taken as the critical lateral spacing of the target vessel assembly under the corresponding operating parameters. The module analyzes the critical lateral spacing of the target vessel assembly under the corresponding operating parameters under multiple sets of operating parameters, and generates the interference prediction result of the target vessel assembly's parallel synchronous water release based on the correlation between the critical lateral spacing of the target vessel assembly under the corresponding operating parameters and the initial motion speed in the multiple sets of operating parameters.

7. 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 the method for predicting interference in parallel synchronous water exit of a vehicle as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to execute the method for predicting interference in parallel synchronous water discharge of a vehicle as described in any one of claims 1 to 5.

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