A method and system for predicting wall surface fluctuating pressure and vibration response of an underwater vehicle

Abstract

This invention discloses a method and system for predicting the pulsating pressure and vibration response of an underwater vehicle's wall. The method uses the obtained potential flow solution as the initial value for the RANS solution, and then uses the obtained RANS solution as the initial value for the LES solution to obtain the LES solution, thereby accelerating iteration and reducing computation time and scale. A fast Fourier transform is performed on the time-varying pulsating pressure obtained from the LES solution to convert it from the time domain to the frequency domain. Finally, this frequency domain excitation is applied to the underwater vehicle to obtain its vibration response, including displacement, velocity, and acceleration. This invention uses the finite element method (FEM) for the solution process, rather than the finite volume method commonly used in CFD calculations, thus facilitating multi-physics coupled calculations. This results in higher simulation efficiency for underwater vehicles with coupled flow fields, structures, and acoustic fields, avoiding the cumbersome process of using multiple simulation software programs for joint simulation.

Description

Technical Field

[0001] This invention belongs to the technical field of underwater vehicle vibration characteristics research, and relates to a method and system for predicting the wall pulsation pressure and vibration response of an underwater vehicle. Background Technology

[0002] During navigation, underwater vehicles generate flow noise due to disturbances within the surrounding turbulent boundary layer and pulsating pressure on the walls. Velocity disturbances within the turbulent boundary layer are equivalent to quadrupole sound sources, while pulsating pressure on the walls is equivalent to dipole sound sources. Because the noise generated by quadrupoles is negligible at low Mach numbers, the dipole sound source formed by pulsating pressure on the walls is the main component of flow noise. When underwater vehicles are excited by flow noise, their hulls vibrate under forced vibration, generating noise that affects two crucial performance indicators: detection capability and stealth. Noise is divided into self-noise and radiated noise. Self-noise refers to the noise transmitted to the transducer from the underwater vehicle. Excessive self-noise reduces the sensitivity of the detection system, decreases the detection range, and may even cause malfunctions. A 4dB reduction in self-noise increases the active acoustic detection range by approximately 19.1% and the passive acoustic detection range by approximately 34.3%. Radiated noise refers to the noise radiated into the surrounding water environment from the underwater vehicle. Radiated noise is directly related to the stealth capability of underwater vehicles. Excessive radiated noise can reveal the location of the underwater vehicle. Reducing radiated noise by 5 dB can increase the hit rate of unmanned underwater vehicles by approximately 25%. Therefore, simulating the pulsating pressure on the wall of an underwater vehicle and its vibration response under such pressure is of significant engineering importance.

[0003] In current technology, most CFD software on the market uses the finite volume method for fluid calculations, while structural analysis and acoustic field analysis mostly use the finite element method. When dealing with multiphysics coupling problems, multiple software programs are often required for joint simulation, which is quite cumbersome. The response problem of underwater vehicles under fluid excitation is a typical multiphysics coupling problem, involving the coupling of physical fields such as flow field, acoustic field, and structure. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a method and system for predicting the fluctuating pressure and vibration response of an underwater vehicle wall. The finite element method (FEM) is used for simulation in both the CFD calculation of the flow field and the vibration response calculation of the structure. The transient fluctuating pressure acting on the underwater vehicle wall is solved using the LES (Liquidity-Oriented System) method. The time-domain fluctuating pressure excitation is then converted to the frequency domain using a Fast Fourier Transform (FFT) and applied to the underwater vehicle structure. The vibration response of the underwater vehicle under this fluctuating pressure excitation is then solved, thus achieving fluid-structure interaction (FSI) analysis. This method facilitates the calculation of fluid-structure interaction between the flow field and the structure, and is also more conducive to multi-physics coupled simulation, avoiding the need for joint simulation using multiple simulation software programs and improving simulation efficiency.

[0005] This invention is achieved through the following technical solution:

[0006] A method for predicting the wall-mounted pulsating pressure and vibration response of an underwater vehicle includes the following steps:

[0007] S1. Establish a three-dimensional model of the underwater vehicle and the fluid domain to obtain the finite element model of the underwater vehicle and the fluid domain.

[0008] S2. Based on the finite element model of the underwater vehicle and the fluid domain, the potential flow under the irrotational condition is solved to obtain the potential flow solution. The potential flow solution is used as the initial value for the RANS solution. When the vorticity is not zero, the Reynolds-averaged Navier-Stokes equations are solved under the time-averaged condition for the physical quantities in the Navier-Stokes equations to obtain the RANS solution.

[0009] S3. Based on the finite element model of the underwater vehicle and the fluid domain and the RANS solution, perform large eddy simulation to directly simulate the large-scale eddies in the turbulence and obtain the LES solution; perform fast Fourier transform on the LES solution to obtain the excitation of the fluid on the underwater vehicle in the frequency domain.

[0010] S4. Based on the excitation of the underwater vehicle by the fluid in the frequency domain and the forces acting on the underwater vehicle, perform fluid-structure interaction analysis on the underwater vehicle to obtain the vibration response of the underwater vehicle in terms of displacement, velocity and acceleration.

[0011] Preferably, the specific process for establishing the three-dimensional model of the underwater vehicle and the fluid domain as described in S1 is as follows:

[0012] Based on the actual operating conditions of the underwater vehicle during navigation, material properties are assigned to it, and the basic properties of the fluid in the fluid domain are determined. In this way, a three-dimensional model of the underwater vehicle and the fluid domain is established, and the three-dimensional model is meshed to obtain the finite element model of the underwater vehicle and the fluid domain.

[0013] Preferably, the material properties include the density, damping, Young's modulus, and Poisson's ratio of the underwater vehicle material, as well as the density and dynamic viscosity of the fluid in the fluid domain;

[0014] Determining the basic properties of a fluid in a fluid domain specifically involves: calculating the Reynolds number and Mach number of the fluid; using the Reynolds number to determine whether the fluid's flow state is Stokes flow, laminar flow, or turbulent flow; and using the Mach number to determine whether the fluid's flow state is incompressible or compressible flow.

[0015] Preferably, the 3D model is meshed at least twice, once for potential flow and RANS solution, and once for LES solution.

[0016] Preferably, the solution for the potential flow in the irrotational case of S2 is as follows:

[0017] Set the boundary conditions for the potential flow solution, select an appropriate solver based on the actual problem and the computer's memory size, set the relative tolerance of the solver, perform steady-state analysis on the finite element model, and calculate the potential flow solution;

[0018] Specifically, the boundary conditions for solving the potential flow are as follows:

[0019] The upper base of the fluid domain is set as the fluid inlet, and the flux at the inlet is set as the fluid velocity. The lower base of the fluid domain is set as the fluid outlet, and the Dirichlet boundary condition at the outlet is set to 0. The walls of the underwater vehicle are set as non-slip walls, i.e., the velocity of particles on the wall is 0. The walls of the fluid domain are set as slip walls, i.e., the normal velocity of particles on the wall is 0.

[0020] Preferably, the RANS solution described in S2 is specifically performed as follows:

[0021] Select a suitable RANS turbulence model, set the boundary conditions for the RANS solution, use the potential flow solution as the initial value for the RANS solution, perform steady-state analysis on the finite element model, and obtain the RANS solution;

[0022] Specifically, the boundary conditions for RANS solving are set as follows:

[0023] Set the normal inflow velocity of the fluid inlet of the fluid domain to the fluid velocity, and set the static pressure of the fluid outlet of the fluid domain to 0; set the wall of the underwater vehicle to a non-slip wall, and the wall of the fluid domain to a slip wall.

[0024] Preferably, the LES solution described in S3 is specifically performed as follows:

[0025] Set the boundary conditions for LES solution, use the RANS solution as the initial value for LES solution, perform transient analysis on the finite element model, and obtain the LES solution; the boundary conditions for LES solution are the same as those for RANS solution.

[0026] Preferably, the Fast Fourier Transform described in S4 is performed as follows:

[0027] By setting the start time, end time, and output frequency of the Fast Fourier Transform (FFT), the excitation of the underwater vehicle by the fluid in the time domain is converted to the frequency domain. The excitation of the underwater vehicle by the fluid in the frequency domain is obtained, and the force on the underwater vehicle is obtained by performing an area integral on the surface of the underwater vehicle.

[0028] Preferably, the fluid-structure interaction analysis described in S5 specifically involves the following process:

[0029] The excitation of the underwater vehicle by the fluid in the frequency domain is applied to the structure of the underwater vehicle. Constraints are imposed on the underwater vehicle according to the actual working conditions, and the displacement, velocity and acceleration vibration response of the underwater vehicle are solved.

[0030] A system for predicting surface pulsating pressure and vibration response of an underwater vehicle, comprising,

[0031] The model building module is used to build three-dimensional models of underwater vehicles and fluid domains, and obtain finite element models of underwater vehicles and fluid domains.

[0032] The computation module is used to solve for potential flow solutions, RANS solutions, and LES solutions;

[0033] The analysis module is used to perform fluid-structure interaction analysis on underwater vehicles to obtain the vibration response of the underwater vehicles in terms of displacement, velocity, and acceleration.

[0034] Compared with the prior art, the present invention has the following beneficial technical effects:

[0035] This invention provides a method and system for predicting the wall-mounted pulsating pressure and vibration response of an underwater vehicle. Specifically, it relates to a method based on Fast Fourier Transform (LES) for solving the wall-mounted pulsating pressure of an underwater vehicle in turbulent flow, and for solving the vibration response of the underwater vehicle under this wall-mounted pulsating pressure excitation. By solving for the potential flow solution, the obtained potential flow solution is used as the initial value for the RANS solution, and then the RANS solution is solved again. The obtained RANS solution is then used as the initial value for the LES solution to obtain the LES solution, thereby accelerating the iteration and reducing the computation time and computational scale. The transient pulsating pressure of the fluid acting on the underwater vehicle wall is solved using LES. The time-domain pulsating pressure excitation is transformed into the frequency domain using Fast Fourier Transform (FFT) and applied to the underwater vehicle structure, thereby achieving fluid-structure interaction analysis and obtaining the vibration response of the underwater vehicle under this excitation, including displacement, velocity, and acceleration. This invention uses the finite element method for simulation in both the CFD calculation of the flow field and the vibration response calculation of the structure, without involving the finite volume method commonly used in CFD calculations. This facilitates multiphysics coupling calculations and fluid-structure interaction calculations of the flow field and structure. It offers higher simulation efficiency for situations involving the coupling of multiple physical quantities such as flow field, structure, and acoustic field in underwater vehicles, avoiding the cumbersome process of using multiple simulation software for joint simulation and improving overall simulation efficiency.

[0036] Furthermore, this invention employs the finite element method in the solution process. In the flow field calculation, by first calculating the potential flow solution and the RANS solution, and using the RANS solution as the initial value for the LES solution, the computational cost of the LES solution is reduced. Attached Figure Description

[0037] Figure 1 This is the technical approach for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to the present invention;

[0038] Figure 2 This is a three-dimensional model of an underwater vehicle in the embodiment;

[0039] Figure 3 This is a model of the underwater vehicle and its external fluid domain in the embodiment;

[0040] Figure 4 This is the mesh generated during the potential flow and RANS solution in the embodiment;

[0041] Figure 5 The velocity amplitude of the potential flow solution in the embodiment;

[0042] Figure 6 The velocity amplitude of the RANS solution in the example;

[0043] Figure 7 This is a diagram showing the wall pressure distribution of the RANS solution in the example;

[0044] Figure 8 The velocity amplitude of the LES solution at t = 0.7 in the embodiment is shown.

[0045] Figure 9 The diagram shows the wall pressure distribution at t = 0.7 for the LES solution in the example.

[0046] Figure 10 This is a three-dimensional model of the underwater vehicle's head shell in the embodiment;

[0047] Figure 11 The force on the head shell of the underwater vehicle in the 0 to 500 Hz frequency band is shown in the embodiment.

[0048] Figure 12 The displacement response of the underwater vehicle's head shell at 20Hz is shown in the example.

[0049] Figure 13 The speed response of the underwater vehicle's head shell at 20Hz is shown in the example.

[0050] Figure 14 The acceleration response of the underwater vehicle's head shell at 20Hz is shown in the example. Detailed Implementation

[0051] The present invention will be further described in detail below with reference to specific embodiments. These descriptions are for explanation purposes only and are not intended to limit the scope of the invention.

[0052] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0053] refer to Figure 1 This is the overall implementation scheme and technical route of the present invention.

[0054] This invention provides a method for predicting the wall-fluid pressure and vibration response of an underwater vehicle. Specifically, it relates to a method based on Fast Fourier Transform (FFT) to solve for the wall-fluid pressure applied by a fluid to an underwater vehicle in turbulent flow, and a method for solving the vibration response of the underwater vehicle under this wall-fluid pressure excitation. By solving for the potential flow solution, the obtained potential flow solution is used as the initial value for the RANS solution. The RANS solution is then solved, and the obtained RANS solution is used as the initial value for the LES solution to obtain the LES solution, thereby accelerating the iteration and reducing the computation time and computational scale. The time-varying fluctuating pressure obtained from the LES solution is subjected to a Fast Fourier Transform (FFT) to transform it from the time domain to the frequency domain. Finally, this frequency domain excitation is applied to the underwater vehicle, and the vibration response of the underwater vehicle under this excitation, such as displacement, velocity, and acceleration, is obtained. This invention uses the finite element method for the solution process, without involving the finite volume method commonly used in CFD calculations. This makes it easier to perform multi-physics coupling calculations. It has higher simulation efficiency for situations involving the coupling of multiple physical quantities such as flow fields, structures, and sound fields in underwater vehicles, and avoids the cumbersome process of using multiple simulation software for joint simulation.

[0055] The present invention proposes a method for predicting the wall-mounted pulsating pressure and vibration response of an underwater vehicle, which is implemented according to the following specific steps:

[0056] S1. Establish a three-dimensional model of the underwater vehicle and the fluid domain to obtain the finite element model of the underwater vehicle and the fluid domain.

[0057] S2. Based on the finite element model of the underwater vehicle and fluid domain described in S1, the potential flow solution is obtained by considering the irrotational case.

[0058] S3. Based on the finite element model of the underwater vehicle and fluid domain described in S1 and the potential flow solution described in S2, considering that the vorticity is not zero, solve the Reynolds-averaged Navier–Stokes equations (hereinafter referred to as RANS) for the physical quantities in the Navier-Stokes equations under the time-averaged case to obtain the RANS solution.

[0059] S4. Based on the finite element model of the underwater vehicle and fluid domain described in S1 and the RANS solution described in S3, consider solving the Large Eddy Simulation (LES) to directly simulate large-scale eddies in turbulence, and obtain the LES solution.

[0060] S5. Based on the finite element model of the underwater vehicle and fluid domain described in S1 and the LES solution described in S4, perform a fast Fourier transform on the LES transient solution to obtain the excitation of the underwater vehicle by the fluid in the frequency domain.

[0061] S6. Based on the finite element model of the underwater vehicle and fluid domain described in S1 and the excitation of the underwater vehicle by the fluid in the frequency domain described in S5, perform fluid-structure interaction analysis on the underwater vehicle to obtain the vibration response of the underwater vehicle, such as displacement, velocity, and acceleration.

[0062] (1) Mapping of underwater vehicles and fluid domains

[0063] Create a 3D model of an underwater vehicle, such as Figure 2 As shown. Figure 3 As shown, the fluid domain is drawn as a cylinder. The size of the fluid domain is determined empirically. Generally, the distance from the upper bottom of the fluid domain to the front end of the underwater vehicle is 2 to 3 times the length of the underwater vehicle, and the distance from the lower bottom to the tail end of the underwater vehicle is 5 to 10 times the length of the underwater vehicle. The radius is 5 to 15 times the maximum radius of the underwater vehicle.

[0064] (2) Assignment of material properties

[0065] Assigning material properties to fluid domains and underwater vehicles typically requires specifying the density, damping, Young's modulus, and Poisson's ratio of the underwater vehicle material, as well as the density and dynamic viscosity of the fluid.

[0066] (3) Determination of basic fluid properties

[0067] The Reynolds number and Mach number of a fluid are calculated. The Reynolds number determines whether the fluid is in a Stokes flow, laminar flow, or turbulent flow. This method is only applicable to turbulent flow. The Mach number determines whether the fluid is incompressible or compressible flow.

[0068] (4) Grid generation

[0069] like Figure 4 As shown, mesh generation is performed on the fluid domain and underwater vehicle. During mesh generation, the mesh needs to be refined in certain sensitive areas. In CFD calculations, boundary layers are often used to achieve this. Furthermore, since LES is more sensitive to mesh size than potential flow and RANS solutions, at least two meshing operations should be performed: one for potential flow and RANS solutions, and another for LES solutions. The mesh used for LES solutions should be more refined than that used for potential flow and RANS solutions, and should also meet the mesh size requirements for LES solutions.

[0070] (5) Solving for potential flow

[0071] like Figure 5 As shown, the potential flow is irrotational, and solving for the potential flow is equivalent to solving the Laplace equation. In this method, by solving for the potential flow, initial values ​​are provided for the RANS solution, thereby accelerating iteration and reducing the simulation's computation time and scale. The specific steps are as follows:

[0072] First, set the boundary conditions for the potential flow solution. The boundary conditions are as follows:

[0073] (a) The upper bottom of the fluid domain is the fluid inlet, and the flux at the inlet is set to the fluid velocity;

[0074] (b) The lower base of the fluid domain is the fluid outlet. Set the Dirichlet boundary condition of the outlet to 0, that is, specify that the solution of the Laplace equation at the boundary is 0.

[0075] (c) The walls of the underwater vehicle are set as non-slip walls, that is, the velocity of the particles on the wall is 0; the walls of the fluid domain are set as slip walls, that is, the normal velocity of the particles on the wall is 0.

[0076] Then, a suitable solver is selected based on the actual problem and the computer's memory capacity. Fully coupled solvers solve all unknowns in each iteration, requiring fewer iterations and exhibiting better convergence. Separate solvers, on the other hand, break down the solution process into multiple steps in each iteration, solving them sequentially, thus consuming less memory. In practical applications, separate solvers are often used for solving 3D models, while fully coupled solvers are more commonly used for solving 2D models. Direct solvers offer better robustness, while iterative solvers are faster and consume less memory. The relative tolerance of the steady-state solver is then set to perform steady-state analysis on the finite element model, calculating the potential flow solution.

[0077] Finally, the potential flow solution is post-processed. For example... Figure 5 As shown, a velocity amplitude diagram of the potential flow solution is plotted. This diagram illustrates the specific fluid motion around the underwater vehicle, and its values ​​will serve as the initial velocity values ​​for iteration during RANS solving. The post-processing of the potential flow solution involves outputting graphs of the physical quantities of interest based on the solution obtained by the solver. Here, the physical quantities of interest are the fluid velocity around the underwater vehicle and the pressure distribution on the underwater vehicle wall caused by fluid excitation. Therefore, a velocity amplitude diagram and a wall pressure distribution diagram are plotted. The velocity amplitude and pressure distribution obtained from the potential flow solution will be used as initial values ​​for iterative RANS solving.

[0078] (6) Solving RANS

[0079] RANS significantly reduces the computational cost of turbulence simulation by averaging the physical quantities in the Navier-Stokes equations over time. In this method, solving the RANS solution provides initial values ​​for the LES solution, accelerating iteration and reducing the simulation's computation time and scale. The specific steps are as follows:

[0080] First, a suitable RANS turbulence model is selected for calculation. Commonly used turbulence models include the standard k-ε model, the Realizable k-ε model, the k-ω model, and the SST model. The standard k-ε model is the most widely used. The Realizable k-ε model incorporates realizability constraints on top of the standard k-ε model. The k-ω model has higher computational accuracy than the standard k-ε model, but its robustness is not as good. The SST model combines the robustness of the standard k-ε model with the accuracy of the k-ω model.

[0081] Secondly, set the boundary conditions for the RANS solution. The boundary conditions are as follows:

[0082] (a) Set the normal inflow velocity at the inlet to the fluid velocity, or set it to other velocity fields according to the actual needs of the project;

[0083] (b) Set the static pressure at the outlet to 0;

[0084] (c) The walls of the underwater vehicle are configured as non-slip walls, while the walls of the fluid domain are configured as slip walls.

[0085] Next, set the initial values ​​for the RANS solution. Use the potential flow solution as the initial value for the RANS solution.

[0086] Next, select a suitable solver, using a method similar to that used for potential flow solving. Set the relative tolerance of the steady-state solver and perform steady-state analysis on the finite element model to obtain the RANS solution.

[0087] Finally, the RANS solution is post-processed, such as... Figure 6 As shown, velocity amplitude and wall pressure distribution maps of the RANS solution are plotted. The velocity amplitude map illustrates the specific fluid motion around the underwater vehicle, and the wall pressure distribution map shows the distribution and magnitude of the fluid excitation on the underwater vehicle wall. These values ​​will serve as the initial values ​​for velocity and pressure during the LES solution iteration. Post-processing of the RANS solution involves outputting graphs of the physical quantities of interest based on the solution obtained by the solver. Here, the physical quantities of interest are the fluid velocity around the underwater vehicle and the pressure distribution of the underwater vehicle wall under fluid excitation, as shown... Figure 7 As shown, the velocity amplitude diagram and wall pressure distribution diagram of the fluid were plotted. The velocity amplitude and pressure distribution obtained by RANS will be used as the initial values ​​for LES solution during iteration.

[0088] (7) Solving LES

[0089] LES (Liquid Evolution) is a method between direct numerical simulation and solving RANS (Related Aspects of Arrays). LES separates small-scale eddies through spatial filtering, then directly simulates large-scale eddies numerically, establishing a mathematical model to consider the feedback effect of small-scale eddies on large-scale eddies. By solving LES, the time-varying pulsating pressure excitation of fluid acting on the wall of an underwater vehicle is obtained. The specific steps are as follows:

[0090] First, set the boundary conditions for LES solution. The boundary conditions for LES solution are the same as those for RANS solution.

[0091] Secondly, set the initial values ​​for the LES solution. Use the RANS solution as the initial values ​​for the LES solution.

[0092] Then, select a suitable solver, using a method similar to that used for potential flow solutions. Perform transient analysis on the model and set the output time step and other solver parameters appropriately. In the time step, you should generally set the solution method, the step size used by the solver, the initial step size, the maximum step size constraint, and other step parameters to achieve better convergence, capture the details of turbulence, and calculate the LES solution.

[0093] Transient analysis specifically involves selecting an appropriate solver based on the specific problem and the computer's memory capacity. Fully coupled solvers solve all unknowns in each iteration, requiring fewer iterations and exhibiting better convergence. Separate solvers, on the other hand, break down the solution process into multiple steps within each iteration, solving them sequentially and requiring less memory. In practical applications, separate solvers are often used for solving 3D models, while fully coupled solvers are more commonly used for solving 2D models. Direct solvers offer better robustness, while iterative solvers are faster and require less memory. Setting the transient solver's output parameters, such as time step, time increment, and maximum step size, can improve convergence and capture turbulent details.

[0094] Finally, the LES solution is post-processed to plot the velocity amplitude map and wall pressure distribution map. The velocity amplitude map shows the specific fluid motion around the underwater vehicle, and the wall pressure distribution map shows the distribution and magnitude of the fluid excitation on the wall of the underwater vehicle. The velocity amplitude map and wall pressure distribution map obtained by LES are more accurate than those obtained by RANS and can more accurately show the flow field around the underwater vehicle.

[0095] (8) Fast Fourier Transform and Surface Integration of Wall

[0096] A Fast Fourier Transform (FFT) is performed on the LES solution to transform the fluid excitation on the underwater vehicle from the time domain to the frequency domain, enabling fluid-structure interaction (FSI) analysis. The FFT should be performed after the fluid flow has stabilized, rather than starting at 0s. The start time, end time, and output frequency of the FFT are set to obtain the fluid excitation on the underwater vehicle in the transformed frequency domain. A surface integral is then applied to the underwater vehicle's wall to obtain the forces acting on it.

[0097] (9) Fluid-structure interaction analysis

[0098] The excitation of the underwater vehicle by the fluid in the frequency domain obtained in the previous step is applied to the structure of the underwater vehicle. Constraints are applied to the underwater vehicle according to the actual working conditions, and the vibration response of the underwater vehicle, such as displacement, velocity and acceleration, is solved.

[0099] The following is a specific application example. In this example, we solve for the wall pulsation pressure and vibration response of an underwater vehicle traveling at 40 knots in seawater:

[0100] Design an underwater vehicle, such as Figure 5 As shown. The underwater vehicle is 4m long and made of 2A12 aluminum alloy with a density ρ = 2800 g / m³. 3 The model has a Young's modulus E = 66, Poisson's ratio v = 0.33, and isotropic structured loss factor η = 0.005. A fluid domain is drawn, which is cylindrical, with its axis coinciding with the axis of the underwater vehicle. The upper base of the fluid domain is 8m from the front of the underwater vehicle (equivalent to two underwater vehicle lengths), and the lower base is 20m from the rear (equivalent to five underwater vehicle lengths). The radius of the fluid domain is 4m, approximately 14 times the maximum radius of the underwater vehicle. The fluid domain is filled with seawater, and the underwater vehicle is filled with air. The entire model consists of the sea area outside the underwater vehicle, the solid domain of the underwater vehicle, and the air domain inside the underwater vehicle. Figure 6 As shown. The underwater vehicle is traveling in the fluid at a speed of 40 knots, v = 40 = 20.578 / kJ.

[0101] Determine the fundamental properties of the fluid. Calculate the Reynolds number and Mach number:

[0102]

[0103]

[0104] Under these conditions, the Reynolds number is greater than 13800, and the fluid flow is turbulent; the Mach number is less than 0.3, which is a low Mach number. At this time, the pressure on the fluid is insufficient to compress the fluid, and it will only cause the fluid to flow. The fluid density will not change with the pressure, and the flow field can be regarded as an incompressible flow field.

[0105] Mesh generation. A coarser mesh is used for the fluid domain; a finer mesh is used for the underwater vehicle wall. Boundary layer mesh is set with 5 layers, a stretching factor of 1.2, and a thickness adjustment factor of 2.5. The mesh generated for solving the potential flow and RANS is as follows. Figure 6 As shown. When solving LES, a more refined mesh should be used than that used in RANS to meet the mesh requirements of LES.

[0106] Solve for the potential flow solution. The upper base of the fluid domain is the fluid inlet, with an inlet flux of -20.578 m / s; the lower base of the fluid domain is the fluid outlet, with the Dirichlet boundary condition at the outlet set to 0. A smooth aggregated multigrid (SA-AMG) solver is used, which improves CFD computation speed and reduces memory usage. The relative tolerance of the steady-state solver is set to 0.001. The velocity amplitude solved using potential flow theory is as follows: Figure 5 As shown, since the potential flow is irrotational, the velocity field of the potential flow solution differs significantly from the velocity field under actual operating conditions.

[0107] Solve for the RANS solution. Set the normal inflow velocity at the inlet to 20.578 m / s to simulate the underwater vehicle traveling at 40 knots in the sea; set the static pressure at the outlet to 0; and set the underwater vehicle wall as a no-slip wall and the fluid domain wall as a slip wall. Use the k-ε turbulence model for simulation. The velocity amplitudes of the RANS solution are as follows: Figure 6 As shown, the wall pressure distribution diagram is as follows: Figure 7 As shown. Because the vorticity of the flow is taken into account, the RANS solution is closer to the actual operating conditions than the potential flow solution; however, RANS averages the physical quantities in the Navier-Stokes equations over time, neglecting many pulsating details of the flow, and cannot well reflect the time-varying characteristics of the pulsating pressure and height of the fluid acting on the wall of the underwater vehicle. Therefore, there is still a certain gap between the results and the actual operating conditions.

[0108] Solve for the LES solution. The boundary conditions for the LES solution are the same as those for the RANS solution. Re-mesh the mesh to make it more refined than the RANS solution, satisfying the requirements of the LES solution. Set the transient solver output time step to output a result every 0.1s from 0 to 0.6s, and every 0.002s from 0.6 to 0.7s. The velocity amplitude of the LES solution at t = 0.7 is as follows... Figure 8 As shown, the wall pressure distribution diagram is as follows: Figure 9 As shown. Because large-scale eddies were directly simulated, the LES solution is closer to the results under actual working conditions than the RANS solution.

[0109] This section only performs fluid-structure interaction analysis on the nose shell of the underwater vehicle. The nose shell of the underwater vehicle is as follows: Figure 10 As shown. After solving for the pulsating pressure on the underwater vehicle's wall surface, only the pulsating pressure excitation of the underwater vehicle's nose shell wall is retained, and the vibration response of the shell under this excitation is solved. A Fast Fourier Transform is performed on the LES solution within 0.6 to 0.7 s to transform the time-domain excitation to the frequency domain. Integrating over the underwater vehicle's nose shell wall, the forces acting on the underwater vehicle's nose shell are obtained, as shown... Figure 11 As shown, the force is mainly concentrated in the 0 to 300 Hz frequency band, and the force shows an overall trend of decreasing with increasing frequency.

[0110] The pulsating pressure excitation of the fluid in the frequency domain on the underwater vehicle's nose hull is applied to the hull, and a fixed constraint is applied to the bottom of the hull. The displacement response of the hull under this excitation is obtained by solving the problem. The displacement response of the hull at frequency f = 20 is analyzed as follows: Figure 12 As shown, the velocity response is as follows Figure 13 As shown, the acceleration response is as follows Figure 14 As shown.

[0111] Although the embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, and not restrictive. Any modifications, alterations, and variations made by those skilled in the art based on the description, without departing from the scope of the present invention, using the disclosed technical content, are equivalent embodiments of the present invention. Furthermore, any equivalent modifications, alterations, and variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. A method for predicting the wall pulsating pressure and vibration response of an underwater vehicle, characterized in that, Includes the following steps: S1. Establish a three-dimensional model of the underwater vehicle and the fluid domain to obtain the finite element model of the underwater vehicle and the fluid domain. S2. Based on the finite element model of the underwater vehicle and the fluid domain, the potential flow under the irrotational condition is solved to obtain the potential flow solution. The potential flow solution is used as the initial value for the RANS solution. When the vorticity is not zero, the Reynolds-averaged Navier-Stokes equations are solved under the time-averaged condition for the physical quantities in the Navier-Stokes equations to obtain the RANS solution. S3. Based on the finite element model of the underwater vehicle and the fluid domain and the RANS solution, the large eddy simulation of the large-scale eddy in the turbulence is directly performed to obtain the LES solution. A fast Fourier transform is performed on the LES solution to obtain the excitation of the underwater vehicle by the fluid in the frequency domain. S4. Based on the excitation of the underwater vehicle by the fluid in the frequency domain and the force on the underwater vehicle, perform fluid-structure interaction analysis on the underwater vehicle to obtain the vibration response of the underwater vehicle in terms of displacement, velocity and acceleration. When meshing the 3D model, it should be done at least twice, once for potential flow and RANS solution, and once for LES solution; The specific process for establishing the three-dimensional model of the underwater vehicle and the fluid domain as described in S1 is as follows: Based on the actual operating conditions of the underwater vehicle during navigation, material properties are assigned to it, and the basic properties of the fluid in the fluid domain are determined. In this way, a three-dimensional model of the underwater vehicle and the fluid domain is established, and the three-dimensional model is meshed to obtain the finite element model of the underwater vehicle and the fluid domain.

2. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The material properties include the density, damping, Young's modulus, and Poisson's ratio of the underwater vehicle material, as well as the density and dynamic viscosity of the fluid in the fluid domain. Determining the basic properties of a fluid in a fluid domain involves: calculating the Reynolds number and Mach number of the fluid; using the Reynolds number to determine whether the fluid's flow state is Stokes flow, laminar flow, or turbulent flow; and using the Mach number to determine whether the fluid's flow state is incompressible or compressible flow.

3. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The solution for the potential flow in the irrotational case of S2 is as follows: By setting boundary conditions for the potential flow solution and performing steady-state analysis on the finite element model, the potential flow solution is obtained. Specifically, the boundary conditions for solving the potential flow are as follows: The upper base of the fluid domain is set as the fluid inlet, and the flux at the inlet is set as the fluid velocity. The lower base of the fluid domain is set as the fluid outlet, and the Dirichlet boundary condition at the outlet is set to 0. The walls of the underwater vehicle are set as non-slip walls, i.e., the velocity of particles on the wall is 0. The walls of the fluid domain are set as slip walls, i.e., the normal velocity of particles on the wall is 0.

4. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The specific process of solving RANS as described in S2 is as follows: Select a suitable RANS turbulence model, set the boundary conditions for the RANS solution, use the potential flow solution as the initial value for the RANS solution, perform steady-state analysis on the finite element model, and obtain the RANS solution; Specifically, the boundary conditions for RANS solving are set as follows: Set the normal inflow velocity of the fluid inlet of the fluid domain to the fluid velocity, and set the static pressure of the fluid outlet of the fluid domain to 0; set the wall of the underwater vehicle to a non-slip wall, and the wall of the fluid domain to a slip wall.

5. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The LES solution described in S3 is as follows: Set the boundary conditions for the LES solution, use the RANS solution as the initial values ​​for the LES solution, perform transient analysis on the finite element model, and obtain the LES solution; the boundary conditions for the LES solution are the same as those for the RANS solution.

6. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The Fast Fourier Transform described in S4 is as follows: By setting the start time, end time, and output frequency of the Fast Fourier Transform (FFT), the excitation of the underwater vehicle by the fluid in the time domain is converted to the frequency domain. The excitation of the underwater vehicle by the fluid in the frequency domain is obtained, and the force on the underwater vehicle is obtained by performing an area integral on the surface of the underwater vehicle.

7. The method for predicting the wall pulsation pressure and vibration response of an underwater vehicle according to claim 1, characterized in that, The fluid-structure interaction analysis described in S5 is specifically performed as follows: The excitation of the underwater vehicle by the fluid in the frequency domain is applied to the structure of the underwater vehicle. Constraints are imposed on the underwater vehicle according to the actual working conditions, and the displacement, velocity and acceleration vibration response of the underwater vehicle are solved.

8. A system for predicting the surface pulsating pressure and vibration response of an underwater vehicle, based on the method for predicting the surface pulsating pressure and vibration response of an underwater vehicle according to any one of claims 1-7, characterized in that, include, The model building module is used to build three-dimensional models of underwater vehicles and fluid domains, and obtain finite element models of underwater vehicles and fluid domains. The computation module is used to solve for potential flow solutions, RANS solutions, and LES solutions; The analysis module is used to perform fluid-structure interaction analysis on underwater vehicles to obtain the vibration response of the underwater vehicles in terms of displacement, velocity, and acceleration.

Images