A Numerical Simulation Method for Aerodynamic Noise of UAV Propellers

Abstract

The present invention discloses a numerical simulation method for the aerodynamic noise of an unmanned aerial vehicle (UAV) propeller. The method includes: for the UAV propeller model, dividing the grid according to the size of the grid quantity and adding a boundary layer to the propeller model to obtain a computational grid file; reading the computational grid file, establishing the control equations of the propeller flow field, determining the initial conditions and boundary conditions, discretizing the control equations, the initial conditions and boundary conditions after discretization, and setting the solution control parameters; decomposing the computational region and using an open-source computational fluid dynamics software for parallel computing to obtain the flow field data; discretizing the surface of the propeller blade, importing the flow field data into the sound field calculation program, calculating the sound pressure at the observation point by the integration method, and parallel computing the sound pressure at the same moment from different sound sources on the propeller blade to the observation point; for the time-domain variation of the sound pressure at the observation point, converting it into the frequency-domain variation through Fourier transform and performing post-processing to analyze the noise. The calculation process of the present invention is simple and the calculation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and more specifically, to a numerical simulation method for the aerodynamic noise of an unmanned aerial vehicle propeller. Background Art

[0002] As unmanned aerial vehicle (UAV)-like aircraft become increasingly common, the market for novel vertical takeoff and landing aircraft, including UAVs for applications such as package delivery, imaging, and surveillance, has developed rapidly. Moreover, many commercial UAVs have achieved stable hovering and maneuverable flight and are expected to be used in various fields. Considering the use of UAVs in urban or some special areas, their high-level noise may be a serious problem, so it is crucial to control the aerodynamic noise generated and propagated by such aircraft. Minimizing noise emissions is an integral part of the aircraft design process and must be considered from the very beginning to avoid costly redesign issues. For the rotorcraft manufacturing industry, acoustic comfort is an important issue, and obtaining noise data through wind tunnel experiments is not only time-consuming but also costly. Therefore, the development of fast and efficient numerical tools is the key to preventing and reducing noise in airframe components during the design stage. Due to the limited capabilities of theoretical analysis, high costs, and long experimental research times, numerical simulation has become an effective alternative tool for various industrial applications.

[0003] When designing and developing the propeller of a UAV, in addition to considering its aerodynamic performance, the noise level during its operation is also taken into account. In the prior art, for the numerical calculation of the aerodynamic noise of a propeller, the method of computational aeroacoustics is adopted. Computational aeroacoustics (CAA) is a complete computer simulation of noise, which includes two aspects, that is, first, the flow sound source is found by the method of computational fluid dynamics (CFD), and then the propagation of the noise is calculated by the CAA method. The former belongs to the CFD flow field simulation, and the latter is the acoustic simulation.

[0004] At present, there are mainly three numerical analysis methods for computational aeroacoustics: one is the direct calculation method of DNS (Direct Numerical Simulation), which directly solves the acoustic part by adding the wave operator equation of sound to the fluid calculation. This method is commonly used in the calculation of aeroacoustic noise in simple pipes, jet noise, and cavity noise, but it is less applied in engineering. The second is the hybrid method, that is, separating the sound source calculation and the acoustic propagation calculation. First, the transient flow field is calculated by CFD analysis, and the equivalent sound source is solved from the unsteady flow field and the acoustic propagation calculation is carried out. There are two types of methods for acoustic propagation calculation, one is the integral method, and the other is the acoustic analogy method. The third is the semi-empirical method, which reconstructs a sound source using some performance characteristics in CFD, such as turbulent kinetic energy, dissipation rate of turbulent kinetic energy, etc., and then calculates the aeroacoustic noise using formulas.

[0005] With the development of computer computing power, using CFD technology to solve practical engineering problems can significantly reduce the development cost and cycle, and also bring new development to computational aeroacoustics, which is of great significance to the design and research and development of new UAV propellers. However, most existing numerical simulation methods have the following disadvantages: relying on commercial software to implement, since commercial software is not open source, so problems or errors during the calculation process are unknown, and the algorithm cannot be optimized or changed in time; the calculation speed is slow. For complex propeller shapes, a large number of intensive calculations are required for both the flow field calculation and the acoustic calculation, and such a large amount of calculation is very time-consuming. Summary of the Invention

[0006] The object of the present invention is to overcome the defects of the above-mentioned existing technologies and provide a numerical simulation method for aeroacoustic noise of UAV propellers. The method includes the following steps:

[0007] For the established UAV propeller model, divide the grid according to the required grid size and add a boundary layer near the propeller model to calculate the flow field results, and then obtain the entire computational grid file;

[0008] Read the computational grid file, establish the control equation of the propeller flow field, determine the initial conditions and boundary conditions, control the discretization of the equation, the initial conditions and boundary conditions after discretization, and set the solution control parameters;

[0009] Decompose the computational domain, use open-source computational fluid dynamics software for parallel computing, obtain the flow field data and save it, where the flow field data includes the velocity and pressure at each location in the propeller flow field at each time step during the calculation period;

[0010] Discretize the surface of the propeller blade, import the corresponding flow field data at different times into the sound field calculation program, calculate the sound pressure at the observation point by the integration method, and simultaneously calculate in parallel the sound pressure from different sound sources on the propeller blade to the observation point at the same moment;

[0011] For the time-domain variation of the sound pressure at the obtained observation point, convert it into a frequency-domain variation through Fourier transform and perform post-processing, and then analyze the noise characteristics.

[0012] Compared with the prior art, the advantages of the present invention are that a fast numerical simulation method is proposed to quickly calculate and simulate the aerodynamic noise generated by the UAV propeller, which is beneficial to quickly verify the aerodynamic noise during the design and research and development process of the UAV propeller. The software used in the present invention is open-source and complete, and the algorithm can be changed and various customizations can be made according to the requirements of the calculation process. At the same time, through parallel calculation, large grids can be quickly calculated, which can quickly improve the calculation efficiency of the flow field and thus improve the overall calculation speed. In addition, when calculating the noise, the present invention can perform parallel calculation on the blade sound sources at different positions and different times, further improving the overall calculation speed.

[0013] Through the following detailed description of the exemplary embodiments of the present invention with reference to the accompanying drawings, other features and advantages of the present invention will become clear. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings incorporated in and constituting a part of this specification illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0015] Figure 1 is a flowchart of a numerical simulation method for the aerodynamic noise of a UAV propeller according to an embodiment of the present invention

[0016] Figure 2 is a schematic diagram of the process of a numerical simulation method for the aerodynamic noise of a UAV propeller according to an embodiment of the present invention;

[0017] Figure 3 is a schematic diagram of the propeller flow field calculation domain, an example model and a mesh according to an embodiment of the present invention;

[0018] Figure 4 is a schematic diagram of the rotating domain of the propeller flow field calculation according to an embodiment of the present invention;

[0019] Figure 5 is a schematic diagram of the discrete sound sources on the propeller blade relative to the observation point according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and values set forth in these embodiments do not limit the scope of the present invention.

[0021] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way a limitation on the present invention or its application or use.

[0022] Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies, methods, and devices should be regarded as part of the specification.

[0023] In all the examples shown and discussed herein, any specific values should be construed as merely exemplary and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.

[0024] It should be noted that: like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, further discussion thereof in subsequent drawings is not required.

[0025] See Figure 1 and Figure 2 As shown, the provided numerical simulation method for the aerodynamic noise of a drone propeller includes the following steps.

[0026] Step S110, establish a drone propeller model.

[0027] In practical applications, a three-dimensional modeling software can be used to establish a drone propeller model.

[0028] Step S120, for the established drone propeller model, divide the grid according to the required grid size and add a boundary layer near the propeller model to calculate the flow field results, and finally obtain the entire computational grid file.

[0029] Specifically, an open-source grid generation software can be used to divide the grid according to the required grid size. In order to obtain accurate calculation results, a finer grid needs to be divided, and the grid size is large, and a parallel method can be used to divide the grid. After the grid of the entire computational domain is divided, it is divided into a rotating domain and a stationary domain, where the rotating domain is a small cylinder wrapped outside the propeller model, and the stationary domain is a large cylindrical domain and wraps outside the rotating domain. Further, boundary layer grids are added to the edges of the propeller blades in the rotating domain. Since the structure of the propeller is irregular and contains many complex curved surfaces, an unstructured tetrahedral grid element with a wider adaptability range is used to divide the grid of the propeller model and ensure that the grid quality meets the requirements. See Figure 3 and Figure 4 As shown.

[0030] In one embodiment, the sliding mesh method is used to process the rotating domain, and the Arbitrary Mesh Interface (AMI) method is adopted in the sliding mesh method. For the setting of the computational fluid field grid, assuming D is the rotor diameter, the radial dimension of the fixed region can be set to 7.5*D, and the axial dimension can be set to 14*D to minimize the pressure influence at the far-field boundary. When using this far-field domain size, there is almost no pressure change near the inlet and outlet boundaries. For accurate calculation, a finer cylindrical grid can be constructed around the rotating domain. Then, the open boundary condition is applied to the fixed region boundary, and the pressure is fixed. The grid is stretched in the downstream direction to enable the flow to smoothly leave the boundary. The computational rotating domain of the propeller flow field is as Figure 4 shown.

[0031] Step S130: Read the computational grid file, establish the control equations of the propeller flow field, determine the initial conditions and boundary conditions, discretize the control equations, the discretized initial conditions and boundary conditions, and specify the solution control parameters.

[0032] For example, use open-source computational fluid dynamics software (such as OpenFOAM) to read the computational grid file, and then perform the establishment of control equations, determination of initial conditions and boundary conditions, discretization of control equations, discretized initial conditions and boundary conditions, and specification of solution control parameters, etc.

[0033] 1) Establishment of control equations

[0034] The propeller flow field is set as an unsteady, incompressible Newtonian fluid, and its control equations are described by the Navier-Stokes equations, expressed as:

[0035]

[0036] where ρ is the density, U is the velocity, p is the pressure, ν is the viscosity, is the derivative symbol, is the gradient.

[0037] The flow of air around the operating propeller is turbulent. Turbulence is a very random and instantaneous flow state, and the flow velocity and direction change every moment. And if one wants to directly and accurately simulate turbulence, it requires a huge computational cost. Therefore, a suitable turbulence model is introduced. For example, the k-omega SST turbulence model is selected. The k-omega SST turbulence model combines the k-epsilon in the free stream and the k-omega model near the wall. The k-omega SST turbulence model does not use the wall function, so it is the most accurate when solving the flow near the wall.

[0038] The settings of the k-omega SST turbulence model are as follows:

[0039] The eddy viscosity is expressed as:

[0040] μ T = ρk / ω (2)

[0041] The turbulent kinetic energy equation is expressed as:

[0042]

[0043] The ω equation is expressed as:

[0044]

[0045] The coefficients are set as:

[0046] α = 5 / 9, β = 3 / 40, β * = 9 / 100, σ = 1 / 2, σ * = 1 / 2 (5)

[0047] Auxiliary relation:

[0048] ε = β * ωk and l = k 1 / 2 / ω (6)

[0049] Among them, μ T is the eddy viscosity coefficient, ρ is the density, U is the velocity, t is the time, k is the pulsating kinetic energy, ω is the specific kinetic energy dissipation rate, x j is the spatial direction, the subscript j represents the coordinate axis, τ ij is the Reynolds stress, the subscript ij represents the direction, μ is the eddy viscosity, ε is the dissipation rate of the pulsating kinetic energy, l is the mixing length, α, β, β * , σ, σ * are all empirical coefficients.

[0050] 2), Determine the initial conditions and boundary conditions

[0051] Based on the calculation background, the velocity inlet condition is used at the inlet, the pressure boundary is at the outlet, and the k-omega SST turbulence model with the best effect is adopted. In addition, the surface part of the propeller model is set as a rotating solid wall, and the surface part of the remaining fixed domain is set as a stationary solid wall.

[0052] 3), Discretize the governing equations, initial conditions, and boundary conditions

[0053] In one embodiment, the finite volume method is used to discretize the governing equations.

[0054] First, perform the Euler fully implicit discretization of the time term in the equation with respect to the velocity U over time, and we have:

[0055]

[0056] Implicit discretization of the convective term:

[0057]

[0058] Implicit discretization of the Laplace term:

[0059]

[0060] Explicit discretization of the pressure term:

[0061]

[0062] Wherein, the superscript t represents the current time step (known), the superscript * represents the prediction step (to be solved), the subscript f represents the value on the grid cell face, V P represents the grid cell volume, S f represents the face vectors of each face of the grid cell, Δt represents the time step size, is the flux, and v is the dynamic viscosity. is the quantity defined at the cell center, that is, the velocity gradient at the grid cell center. is the quantity defined at the face center, that is, the velocity gradient at the grid face center. U is the velocity, V is the volume, and any variable with the subscript P attached represents the value on the grid cell.

[0063] 4), Given the solution control parameters

[0064] Set the control parameters according to the calculation boundary conditions, and set the initial conditions at the inlet, outlet, and propeller surface. Given the discretization format, such as the format of the first-order time derivative term (unsteady term), the gradient term format, the divergence term format, the Laplace term format, the interpolation format, the face normal gradient format, etc.

[0065] Step S140, After decomposing the obtained computational domain, perform parallel computing. Use open-source computational fluid dynamics software to perform computer calculations on a supercomputing platform with a large number of cores, and obtain the velocity, pressure, etc. at each location in the propeller flow field at each time step within the calculation period.

[0066] Specifically, the computational domain obtained from the above steps is decomposed by the software into multiple computational domains, and then each computational domain is distributed to independent processors on the supercomputer. Each independent processor on the supercomputer uses a copy of the solver to perform parallel computing on its respective computational domain, and information exchange is carried out during the computing process to improve the computing efficiency. After obtaining the results of the blood pump flow field at each time step within the calculation period for each computational domain, a merging process is performed, and finally the calculation results of the overall computational domain are obtained.

[0067] In summary, the open-source computing software is selected for the flow field calculation of the present invention, which can be well deployed in a multi-core environment and perform arbitrary multi-core calculations within a certain range, improving the calculation efficiency.

[0068] Step S150: Save the calculated flow field data with regular changes for subsequent sound field calculation.

[0069] After calculating the propeller flow field data according to the above steps, the flow field data of each moment on the propeller surface within the effective time step range, such as velocity, pressure, etc., are saved and output through post-processing software, and then output and saved for subsequent calculation programs to read. In this article, the effective time step is the time step range after the key point variables in the flow field show regular changes, which is beneficial to obtaining better noise calculation results.

[0070] Step S160: Discretize the propeller blade surface, import the corresponding flow field data at different moments into the sound field calculation program, and calculate the sound pressure at the observation point through the integration method. At this time, the sound pressure from different sound sources on the blade to the observation point at the same moment can be calculated in parallel.

[0071] For example, the calculated aerodynamic noise mainly includes load noise and thickness noise.

[0072] 1) Load noise

[0073] According to the FW-H (Ffowcs Williams Hawkings) equation, the acoustic wave equation of the load noise of the rotating blade is:

[0074]

[0075] In the formula, l i is the component of the load on a certain area element on the blade surface in the x-axis direction of the fixed coordinate system. The rotating blade can be divided into various blade element segments and chord segments along the radial and circumferential directions for each area element. i The retarded time formula for the time-domain solution is expressed as:

[0076] The retarded time formula for the time-domain solution is expressed as:

[0077]

[0078] □ 2 is the d'Alembert wave operator, p L is the load noise, p L (x, t) is the value of the load noise with respect to spatial position and time, δ() is the Dirac delta function, f = 0 represents the blade surface equation, r is the distance, M ar is the component of the Mach number in the distance direction, the subscript ret represents the retarded time, and ds represents the differential with respect to time.

[0079] In Equation (12), the derivative with respect to the spatial position is added, but it makes it difficult to describe the physical meaning of the integrand with respect to the derivative of the spatial position. Therefore, this form of solution is usually not directly used. The solution to this problem is to transform the derivative with respect to the spatial position into the derivative with respect to time, so that the integrand in the equation becomes a function with a time-varying meaning. That is to say, if the change of the integrand with time is known, then the sound field solution can be obtained. Regarding this transformation, as long as the Dirac functions δ(f) and δ(g) are integrated during the solution of the acoustic wave equation, using

[0080]

[0081] and

[0082]

[0083] we can obtain:

[0084]

[0085] The sound field solution can be written as:

[0086]

[0087] In the above sound field solution, l = e i l i is the force exerted by the load on the local fluid on the blade surface area element; l i is the component of the force l in the x i axis direction; is the projection of l in the direction of the receiving point; is the unit vector in the direction of radiation to the receiving point; is the component of the vector in the x i axis direction. x and y are the emission and receiving positions of the sound source respectively, g represents the retarded time equation, c0 is the speed of sound, the superscript ^ represents the unit vector of the vector, and the subscript r represents the component of the quantity in the distance direction.

[0088] Next, deal with the derivative with respect to time in the equation. Obviously, if the problem of taking the derivative of the load with respect to the receiving time is transformed into the problem of taking the derivative with respect to its emission time, then the following physical quantities with the meaning of describing the change of the moving sound source parameters with time can be obtained:

[0089]

[0090] Transform

[0091] The retarded time equation is expressed as: t = τ + |x - y(τ)| / c0 (18)

[0092]

[0093] After sorting and substituting, we can obtain:

[0094]

[0095] where i i is the load derivative with respect to time; the subscript i represents the component along the x-axis direction. The symbol V represents the surface velocity, and M a represents the Mach number.

[0096] 2), thickness noise

[0097] The acoustic wave equation for the thickness noise of a rotating blade is:

[0098]

[0099] The retarded time formula for predicting the load noise of a rotating blade by the time domain method:

[0100]

[0101] In the formula, V n is the surface normal motion velocity.

[0102] Similar to the description method of load noise, the time derivative is also moved inside the integral sign

[0103]

[0104] In the formula:

[0105] Usually in the thickness formula, this term is ignored, which actually means assuming that the rotor is in a steady motion. Thus, when the rotor is in a steady motion, the time domain calculation formula for its thickness noise can be written as:

[0106]

[0107] where p T represents the thickness noise, ρ0 represents the undisturbed density, and the superscript · represents differentiation.

[0108] Figure 5 is a schematic diagram of the discrete sound source on the propeller blade relative to the observation point.

[0109] Step S170, for the obtained time-domain variation of the sound pressure at the observation point, convert it into a frequency-domain variation through Fourier transform and perform post-processing, and then analyze the noise characteristics.

[0110] To further verify the effectiveness of the present invention, the results of preliminary numerical simulation calculations show that the predicted total sound pressure level of the propeller is basically consistent with the existing experimental results, with a small numerical difference and a high degree of coincidence.

[0111] In summary, in the present invention, the flow field calculation uses open-source software, and the calculation algorithm used is independent and clear, and can be freely changed according to the situation, making it easier to apply to different working conditions and obtaining more accurate results; in the flow field calculation and acoustic calculation, by decomposing the calculation area, the large calculation area is decomposed into independent small calculation areas, and the small calculation areas can be freely allocated to the calculation units with different numbers of cores. The calculation area and the processors required for calculation are independent of each other, improving the calculation efficiency; the integration method in the hybrid method of CAA is used for acoustic calculation, combined with the flow field calculation, and the calculation results can be obtained quickly and efficiently. The integration method selected in the aerodynamic noise calculation is based on the free-field Green's function, and in this case, it is suitable for free-field acoustic calculation. Compared with the acoustic analogy method in the hybrid method of acoustic calculation, the present invention does not require the establishment of an acoustic grid, and the calculation process is more concise and clear.

[0112] The present invention can be a system, a method, and / or a computer program product. The computer program product can include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0113] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device such as a punched card or raised structures in a groove having instructions stored thereon, and any suitable combination of the foregoing. The computer-readable storage medium used herein is not construed as an instantaneous signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0114] The computer-readable program instructions described herein can be downloaded to various computing / processing devices from a computer-readable storage medium or downloaded to an external computer or external storage device through a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0115] The computer program instructions for carrying out operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state-setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, Python, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider). In some embodiments, by using the state information of the computer-readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present invention.

[0116] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0117] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that the instructions, when executed by the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that causes a computer, a programmable data processing apparatus, and / or other devices to operate in a particular manner, such that the computer-readable medium storing the instructions comprises a manufacture, the instructions therein implementing various aspects of the functions / acts specified in one or more blocks of the flowchart and / or block diagram.

[0118] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, such that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, whereby the instructions executed on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in one or more blocks of the flowchart and / or block diagram.

[0119] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of code, or a portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or acts, or by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation via hardware, implementation via software, and implementation via a combination of software and hardware are equivalent.

[0120] The embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is also not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A numerical simulation method for the aerodynamic noise of an unmanned aerial vehicle (UAV) propeller, comprising the following steps: For the established UAV propeller model, divide the grid according to the required grid size, and add a boundary layer near the propeller model to calculate the flow field results, obtaining the entire computational grid file; Read the computational grid file, establish the control equations for the propeller flow field, determine the initial conditions and boundary conditions, control the discretization of the equations, the initial conditions and boundary conditions after discretization, and set the solution control parameters; Decompose the computational domain, perform parallel computing using open-source computational fluid dynamics software, obtain the flow field data and save it, where the flow field data includes the velocity and pressure at various locations in the propeller flow field at each time step within the computational period; Discretize the surface of the propeller blade, import the corresponding flow field data at different times into the acoustic field calculation program, and calculate the sound pressure at the observation point through the integration method. At the same time, parallelly calculate the sound pressure from different sound source locations on the propeller blade to the observation point at the same moment; For the time-domain variation of the sound pressure at the observation point obtained, convert it into the frequency-domain variation through Fourier transform and perform post-processing, and then analyze the noise characteristics.

2. The method according to claim 1, characterized in that, Use unstructured tetrahedral grid elements to divide the grid of the UAV propeller model. After the grid division of the entire computational domain, it is divided into a rotating domain and a stationary domain. The rotating domain is a small cylindrical body wrapped outside the UAV propeller model, and the stationary domain is a large cylindrical domain wrapped outside the rotating domain.

3. The method according to claim 1, wherein The control equations for the propeller flow field are expressed as: where ρ is the density, U is the velocity, p is the pressure, and v is the viscosity.

4. The method according to claim 3, wherein Use the k-omega SST turbulence model to simulate the flow of air around the UAV propeller, and set as follows: The eddy viscosity is expressed as: μ T = ρk / ω The turbulent kinetic energy equation is expressed as: The ω equation is expressed as: The coefficients are set as: α = 5 / 9, β = 3 / 40, β * = 9 / 100, σ = 1 / 2, σ * = 1 / 2 The auxiliary relationship is: ε = β * ωk and l = k 1 / 2 / ω Among them, μ T is the eddy viscosity coefficient, t is time, k is the turbulent kinetic energy, ω is the specific kinetic energy dissipation rate, x j is the spatial direction, the subscript j represents the coordinate axis, τ ij is the Reynolds stress, the subscript ij represents the direction, μ is the eddy viscosity, ε is the dissipation rate of the turbulent kinetic energy, l is the mixing length, α, β, β * , σ, σ * are all empirical coefficients.

5. The method according to claim 1, characterized in that, The determination of the initial conditions and boundary conditions includes: setting the inlet to use the velocity inlet condition, the outlet to be the pressure boundary, the turbulence model to be the k-omega SST turbulence model, and setting the surface part of the UAV propeller model to be a rotating solid wall, and the remaining surface part of the stationary domain to be a stationary solid wall.

6. The method according to claim 3, wherein Use the finite volume method to discretize the control equations for the propeller flow field, including: Perform Euler fully implicit discretization of the time term in the equation with respect to the velocity U over time, obtaining: Implicit discretization of the convection term: Implicit discretization of the Laplace term: Explicit discretization of the pressure term: Among them, the superscript \(t\) represents the current time step, the superscript \(*\) represents the value at the prediction step, the subscript \(f\) represents the value on the face of the grid cell, \(V\) P represents the grid cell volume, \(S\) f represents the face vectors of each face of the grid cell, \(\Delta t\) represents the time step size, is the flux, \(v\) is the dynamic viscosity, is the velocity gradient at the grid cell center, is the velocity gradient at the grid cell face center, \(V\) is the volume, and the subscript \(P\) of each variable represents the value on the grid cell.

7. The method according to claim 1, characterized in that, The setting of the solution control parameters includes: setting the initial conditions at the inlet, outlet, and the propeller surface, and specifying the discretization format.

8. The method according to claim 1, characterized in that, The decomposition of the computational domain and the use of open-source computational fluid dynamics software for parallel computing include: Decompose the overall computational domain into multiple sub-computational domains; Distribute each sub-computational domain to independent processors on a supercomputer, and each independent processor uses a copy of the solver to perform parallel computing on its respective sub-computational domain, and information exchange is carried out during the computing process; After obtaining the flow field results at each time step within the computational period for each sub-computational domain, perform a merging process to obtain the computational results for the overall computational domain.

9. The method according to claim 6, wherein The time-domain calculation formula for the load noise of the UAV propeller is expressed as: The time-domain calculation formula for the thickness noise is expressed as: where \(i\) i is the load derivative with respect to time, the subscript \(i\) represents the component along the \(x\)-axis direction, \(l\) i is the component of the acting force \(l\) in the \(x\) i -axis direction; is the projection of \(l\) in the direction of the receiving point, is the unit radius vector in the direction of radiation towards the receiving point, is the component in the \(x\) i -axis direction, \(x\) and \(y\) are the emission position and the receiving position of the sound source respectively, \(c_0\) is the speed of sound, the superscript \(\hat{}\) represents the unit vector of the vector, and the subscript \(r\) represents the component of the quantity in the distance direction, \(M\) a represents the Mach number, \(V\) n is the normal velocity of the surface movement, \(p\) T represents the thickness noise, \(\rho_0\) represents the undisturbed density, \(M\) ar is the component of the Mach number in the distance direction, and the subscript \(ret\) represents the retarded time.

10. A computer-readable storage medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

11. A computer device, comprising a memory and a processor, and a computer program capable of running on the processor is stored on the memory, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

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