A method and equipment for optimizing the shape of a tiltrotor multi-rotor with high efficiency and low noise

Abstract

This application discloses a method and apparatus for optimizing the shape of a high-efficiency, low-noise tiltrotor rotor for tiltrotor aircraft, relating to the field of tiltrotor aircraft design. The method includes: formulating rotor optimization objectives based on the design requirements of the tiltrotor aircraft; parameterizing the original blades and constructing multiple tiltrotor aircraft models; selecting a target tiltrotor aircraft model, and using methods such as full-aircraft flow field solution and aerodynamic noise assessment to obtain the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor aircraft model under multi-rotor aerodynamic interference, and then outputting the target blade based on the rotor comprehensive performance design evaluation index. This application considers the influence of complex aerodynamic interference between multi-rotor aircraft blades, obtains accurate rotor comprehensive performance design evaluation indexes, and selects a target tiltrotor aircraft model that exceeds the rotor comprehensive performance design evaluation indexes as the target blades, thus obtaining target blades that are closer to actual aerodynamic performance.

Description

Technical Field

[0001] This application relates to the field of tiltrotor aircraft design, and in particular to a method and equipment for optimizing the shape of a high-efficiency, low-noise rotor for tiltrotor aircraft. Background Technology

[0002] Tiltrotor multirotors are currently a research hotspot in the field of tiltrotor aircraft both domestically and internationally. The aerodynamic design of the rotor is crucial, as its aerodynamic performance directly determines the overall aerodynamic performance of the tiltrotor multirotor. To improve rotor aerodynamic performance, advanced rotor designs often employ a three-dimensional combined blade tip design concept. This involves using rotor tips with forward / backward sweep and anhedral characteristics to reduce tip vortex intensity, improve rotor surface pressure distribution, and enhance overall aircraft flight performance.

[0003] Currently, conventional helicopter rotor shape optimization design mainly relies on momentum blade element theory and lift line method to theoretically design rotor negative torque distribution, chord length distribution, and airfoil distribution. The expected rotor blade aerodynamic performance is obtained through theoretical formulas, and then the rotor performance parameters are verified through wind tunnel testing. While these theoretical methods can quickly predict rotor design performance, their accuracy is insufficient for the increasingly complex three-dimensional rotor aerodynamic performance, and they cannot account for the complex aerodynamic interference phenomena of tiltrotor aircraft. This results in a significant discrepancy between the theoretically designed tiltrotor performance and the actual aerodynamic performance. Summary of the Invention

[0004] The purpose of this application is to provide a method and equipment for optimizing the shape of a tiltrotor with high efficiency and low noise, which can obtain accurate evaluation indicators for the overall performance of the rotor, and thus obtain a target blade that is closer to the actual aerodynamic performance.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] Firstly, this application provides a method for optimizing the shape of a high-efficiency, low-noise rotor for a tiltrotor aircraft. The method includes: formulating rotor optimization objectives based on the design requirements of the tiltrotor aircraft; the optimization objectives are rotor comprehensive performance design evaluation indicators; the rotor comprehensive performance design evaluation indicators are obtained by weighting the aerodynamic performance and noise level of the tiltrotor aircraft; parameterizing the original blades and constructing multiple tiltrotor aircraft models; selecting one of the multiple tiltrotor aircraft models as the target tiltrotor aircraft model; and based on the target tiltrotor aircraft model, The aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor aircraft model under multi-rotor aerodynamic interference are obtained by solving the flow field of the entire aircraft and evaluating aerodynamic noise. The rotor comprehensive performance design evaluation index of the target tiltrotor aircraft model is calculated. It is determined whether the rotor comprehensive performance design evaluation index of the target tiltrotor aircraft model is greater than the target threshold. If it is, the blade parameters of the target tiltrotor aircraft model are output as the target blade parameters. If not, the system returns "Select one of the multiple tiltrotor aircraft models as the target tiltrotor aircraft model".

[0007] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the tiltrotor aircraft high-efficiency low-noise rotor shape optimization design method described above.

[0008] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0009] This application formulates rotor optimization objectives based on the design requirements of tiltrotor aircraft; it parameterizes the original blades and constructs multiple tiltrotor aircraft models; it selects a target tiltrotor aircraft model and uses the whole-aircraft flow field solution and aerodynamic noise assessment methods to obtain the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor aircraft model under multi-rotor aerodynamic interference, and calculates the rotor comprehensive performance design evaluation index of the target tiltrotor aircraft model; this application considers the influence of complex aerodynamic interference between multi-rotor aircraft blades, obtains accurate rotor comprehensive performance design evaluation index, and selects a target tiltrotor aircraft model that exceeds the rotor comprehensive performance design evaluation index as the target blade, thus obtaining a target blade that is closer to the actual aerodynamic performance. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a method for optimizing the shape of a tiltrotor rotor that is efficient and low-noise, as provided in an embodiment of this application.

[0012] Figure 2 This is a top view of a tilting quadcopter model provided in an embodiment of this application.

[0013] Figure 3 This is a front view of a tilting quadrotor model provided in an embodiment of this application.

[0014] Figure 4 This is a side view of a tilting quadrotor model provided in an embodiment of this application.

[0015] Figure 5 This is a schematic diagram of the computational grid for a tiltrotor in helicopter mode provided in an embodiment of this application.

[0016] Figure 6 This is a schematic diagram of the computational grid for a tiltrotor in fixed-wing mode provided in an embodiment of this application.

[0017] Figure 7 A schematic diagram of the parameterization and design variables of the propeller tip xy plane shape provided in the embodiments of this application.

[0018] Figure 8 A schematic diagram of the parameterization and design variables of the propeller tip xz plane shape provided in the embodiments of this application.

[0019] Figure 9 The diagram shows the optimized planar shape of the front rotor tip provided in the embodiments of this application.

[0020] Figure 10 The diagram shows the optimized planar shape of the rear rotor tip provided in the embodiments of this application.

[0021] Figure 11 Pressure cloud map of the original blade surface of the front rotor in helicopter mode provided in this application embodiment.

[0022] Figure 12 Pressure cloud map of the upper surface of the front rotor blade in helicopter mode provided in this application embodiment.

[0023] Figure 13 Pressure cloud map of the upper surface of the original rotor blade in helicopter mode provided in this application embodiment.

[0024] Figure 14 Pressure cloud map of the upper surface of the rear rotor blade in helicopter mode provided in this application embodiment.

[0025] Figure 15A comparison chart of front rotor hovering efficiency optimization results provided in the embodiments of this application.

[0026] Figure 16 A comparison chart of the optimized rear rotor hovering efficiency provided in the embodiments of this application.

[0027] Figure 17 Pressure cloud map of the upper surface of the initial blade of the front rotor in fixed-wing mode provided in the embodiments of this application.

[0028] Figure 18 Pressure cloud map of the upper surface of the front rotor blade in fixed-wing mode provided in this application embodiment.

[0029] Figure 19 Pressure cloud map of the upper surface of the initial blade of the rear rotor in fixed-wing mode provided in the embodiments of this application.

[0030] Figure 20 Pressure cloud map of the upper surface of the rear rotor blade in fixed-wing mode provided in this application embodiment.

[0031] Figure 21 This is a schematic diagram of the observation point optimization of the rotor blades and the initial rotor blade sound pressure time history provided in the embodiments of this application under helicopter mode.

[0032] Figure 22 A schematic diagram comparing the horizontal propagation characteristics of the optimized blade and the initial blade in helicopter mode, as provided in the embodiments of this application.

[0033] Figure 23 This is a schematic diagram comparing the sound pressure levels of the optimized blade and the initial blade at the observation point in the fixed-wing mode provided in this application embodiment.

[0034] Figure 24 A schematic diagram comparing the horizontal propagation characteristics of the optimized blade and the initial blade in the fixed-wing mode provided in the embodiments of this application.

[0035] Figure 25 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] Example 1, such as Figure 1 As shown in the figure, this embodiment provides a method for optimizing the shape of a tiltrotor aircraft's high-efficiency, low-noise rotor. The method includes:

[0039] S1. Formulate rotor optimization objectives based on the design requirements of the tiltrotor multirotor; the optimization objectives are rotor comprehensive performance design evaluation indicators; the rotor comprehensive performance design evaluation indicators are obtained by weighting the aerodynamic performance and noise level of the tiltrotor multirotor.

[0040] Furthermore, the calculation formula for the rotor's overall performance design evaluation index is as follows:

[0041] P = a*FM + b*η + 1 / SPL;

[0042] SPL = (a*SPL1 + b*SPL2) / 2;

[0043]

[0044] η = μ n ×C T / C Q ;

[0045] In the formula, P is the rotor comprehensive performance design evaluation index, FM is the hovering efficiency of the tiltrotor in helicopter mode, η is the cruise efficiency of the tiltrotor in fixed-wing mode, SPL is the aerodynamic noise level of the tiltrotor, SPL1 is the noise level of the tiltrotor in fixed-wing mode (forward flight state), SPL2 is the noise level of the tiltrotor in helicopter mode (hovering state), and μ n For the advance ratio of the tilt rotor, C T For the thrust coefficient of the tilt rotor, C Q denoted as the power coefficient of the tilt rotor, and a and b as weighting coefficients.

[0046] Furthermore, a = 0.6; b = 0.4.

[0047] In practical applications, the aerodynamic layout parameters of each basic blade (sample point) and the fuselage and wing parameters are used to obtain the mesh of each basic blade and the mesh of each fuselage and wing. The aerodynamic performance parameters are obtained by solving the flow field of the whole aircraft using the CFD method based on the RANS master control equation. Aerodynamic noise is evaluated using aerodynamic information as input to obtain the noise level of the whole aircraft. The objective function value of each individual in the population is then obtained.

[0048] The tiltrotor model used is as follows: Figure 2 , Figure 3 and Figure 4 As shown in Table 1, the main parameters of the fuselage are as follows:

[0049] Table 1. Main Parameters of Tilting Quadrotor

[0050] parameter numerical values Length / m 4.7 Machine height / m 1.3 Forward wingspan / m 3.0 Rear wingspan / m 3.8 Forward wing installation angle / ° 3.3 Aft wing installation angle / ° 3.0 Wing sweep angle / ° 0 Wing dihedral / ° 0 Maximum takeoff weight / kg 700 Airfoil CLARKYM15

[0051] The main parameters of the tiltrotor rotor are shown in Table 2 below:

[0052] Table 2. Main parameters of the tiltrotor rotor of a quadcopter.

[0053] parameter numerical values Rotor airfoil XV-15 rotor airfoil rotor radius / m 1.0 Rotor root cut 10％ Tip speed / m / s 210 Number of blades / rotor / blades 3 Rotor longitudinal spacing / m 1.9 Rotor vertical spacing / m 0.25 Rotor lateral spacing / m 0.4

[0054] The computational meshes for the tiltrotor in hover and forward flight states are as follows: Figure 5 and Figure 6 As shown.

[0055] The noise level of the tiltrotor aircraft is a weighted average of the noise levels in helicopter mode and fixed-wing mode: in helicopter mode, the sound radiation is strongest directly behind the fuselage, so the observation point is selected as a point 10R away from the center of the nose on the fuselage plane in the forward direction; in fixed-wing mode, the sound radiation is strongest directly in front of the fuselage, so the observation point is selected as a point 10R away from the center of the rotor hub on the fuselage plane in the forward direction.

[0056] S2. Parameterize the original blades and construct multiple tiltrotor models.

[0057] Step S2 specifically includes:

[0058] S21. Parameterize the original blade to obtain the design parameter range of the blade feature points; the blade feature points include: forward sweep feature points, backward sweep feature points, and downward reflection feature points.

[0059] Step S21 specifically includes:

[0060] Step S211. Design the aerodynamic layout parameters of the original blade model with forward sweep-back sweep-downward reflection, and determine the blade feature points.

[0061] Step S212. Parameterize the blade feature points to obtain the design parameter range of the blade feature points.

[0062] In practical applications, the XV-15 was first selected as the reference blade, and four blade shape parameters were selected for optimization design. A schematic diagram of the design parameters is shown below. Figure 7 and Figure 8As shown, R represents the rotor radius, c represents the reference chord length, h represents the reference airfoil height, x represents the spanwise position, y represents the chordwise position, and z represents the airfoil height. The dashed lines in the figure represent quarter-chord lines. P1, P2, and P3 are three points on the leading edge of the blade planform. var1, var2, var3, and var4 are four design parameters used in the optimization process. The chord length of the section from the rotor blade root to 0.80R spanwise is the reference chord length.

[0063] The leading edge shape between points P1 and P2 is parameterized, and the curve between points P1 and P2 is a cubic function curve; point P2 is located at the leading edge tip, and the leading edge shape curve between P2 and P3 is a parabola; the trailing edge shape of the blade at points P1 and P2 is similar to the leading edge shape, and a straight line transition is used between the trailing edges of points P2 and P3 to achieve a smooth transition deformation effect of the blade tip shape.

[0064] The leading edge portion when 0.8R < x ≤ var1:

[0065] y = a1(x - 0.8R) 3 +b1(x-0.8R) 2 +c;

[0066]

[0067] Leading edge portion when var1 < x < R:

[0068]

[0069] The ranges of the four design parameters var1, var2, var3, and var4 are as follows:

[0070]

[0071] S22. Select different parameters within the design parameter range of the blade feature points to construct multiple basic blade shapes.

[0072] Step S22 specifically includes:

[0073] Step S221. Within the design parameter range of the blade feature points, different parameters are selected according to the number of rotors using the Latin hypercube method, and multiple basic rotor shapes are constructed based on the different parameters.

[0074] The process after step S22 also includes: using a BP neural network approximation model optimized by a genetic algorithm to perform preliminary optimization on multiple basic propeller shapes.

[0075] In practical applications, a combination of a BP neural network approximation model and a genetic algorithm is used to encode, select, and crossover / mutate sample points. Encoding refers to encoding the obtained curve representation of the basic propeller. Since the genetic algorithm cannot directly process parameters in the problem space, it is necessary to represent the problem to be solved as chromosomes or individuals in the genetic space through encoding. In other words, the encoding process maps the phenotype (curve representation of the basic propeller) to the genotype. The combination of BP neural network and genetic algorithm is an intelligent optimization strategy, in which the genetic algorithm is used to optimize the parameters of the BP neural network to improve the network's learning ability and generalization performance. This method combines the powerful function approximation ability of the BP neural network with the advantages of the genetic algorithm in global search and optimization. Through iterative search and fitness evaluation by the genetic algorithm, a better network parameter configuration can be found, thereby improving the training efficiency and prediction accuracy of the neural network.

[0076] S23. Multiple tiltrotor aircraft models were constructed based on multiple basic rotor designs.

[0077] S3. Select one tiltrotor aircraft model from among the multiple tiltrotor aircraft models as the target tiltrotor aircraft model.

[0078] S4. Based on the target tiltrotor model, the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor model under multi-rotor aerodynamic interference are obtained by solving the flow field of the whole aircraft and evaluating aerodynamic noise, respectively. The rotor comprehensive performance design evaluation index of the target tiltrotor model is then calculated.

[0079] Furthermore, the flow field solution for the entire machine is obtained using a CFD method based on the RANS master control equations.

[0080] Step S4 specifically includes:

[0081] S41. Based on the fuselage and wing parameters and the aerodynamic layout parameters of multiple blades in the target tiltrotor model, construct the fuselage and wing meshes and blade meshes of the multi-rotor target tiltrotor model respectively.

[0082] S42. Solve the flow field of the entire aircraft based on the fuselage, wing, and blade meshes of the target tiltrotor model to obtain the aerodynamic performance parameters of the target tiltrotor model under multi-rotor aerodynamic disturbance.

[0083] S43. Perform aerodynamic noise assessment on the target tiltrotor model to obtain the aerodynamic noise level of the target tiltrotor model under multi-rotor aerodynamic interference.

[0084] S44. The comprehensive performance design evaluation index of the rotor of the target tiltrotor aircraft model is calculated based on aerodynamic performance parameters and aerodynamic noise level.

[0085] S5. Determine whether the rotor comprehensive performance design evaluation index of the target tiltrotor model is greater than the target threshold. If yes, output the blade parameters of the target tiltrotor model as the target blade parameters. If no, return to step S3 "Select one from multiple tiltrotor models as the target tiltrotor model".

[0086] In practical applications, the rotor optimization results for tiltrotor aircraft considering the overall aerodynamic interference environment are as follows: Figure 9 and Figure 10 As shown, the forward sweep angle of the front rotor is 12.3°, the backward sweep angle is 40°, and the dihedral angle is 5.3°, with the dihedral and sweep positions starting from 0.95R. The backward sweep angle of the rear rotor is 8.3°, the backward sweep angle is 25.4°, and the dihedral angle is 13.2°, with the dihedral and sweep positions starting from 0.9R. It can be seen that the optimized forward and backward sweep angles of the front rotor are both greater than those of the rear rotor, while the dihedral angle of the rear rotor is greater than that of the front rotor. This is because in forward flight, the forward sweep-back angle improves the cruise efficiency of the front rotor more than the rear rotor, while the dihedral angle improves the cruise efficiency of the rear rotor more than the front rotor. Furthermore, the forward sweep-back sweep-dihedral angle has limited effect on the hovering efficiency of both the front and rear rotors in hovering mode.

[0087] The comparative analysis results of the optimized rotor's aerodynamic and noise characteristics in this embodiment are as follows:

[0088] First, optimize the pressure cloud map of the upper surface of the front / rear rotor in hovering mode (helicopter mode) as follows: Figure 11 , Figure 12 , Figure 13 and Figure 14 As shown, the peak negative pressure region on the upper surface of the rotor blades before and after optimization is significantly smaller than that of the initial blades, and the peak negative pressure region at the blade tip is also significantly reduced and shrinks towards the interior of the blade. This will effectively reduce blade tip aerodynamic drag. In addition, the reduction in the peak negative pressure on the blades helps to reduce rotor load noise.

[0089] Second, a comparison of the optimization results for front / rear rotor hovering efficiency is shown in the figure below. Figure 15 and Figure 16 As shown, the optimized hovering performance of both the front and rear rotors is improved across the entire thrust range compared to the initial blades. The front rotor's hovering efficiency is improved by a maximum of 1.5%, while the rear rotor's hovering efficiency is improved by a maximum of 1.0%. The front rotor's improvement is more significant because it is located within the back rotor's downwash flow range, resulting in a more complex working flow field. Using a high-performance blade tip shape can significantly improve its hovering performance. In contrast, the rear rotor is less affected by the front rotor and has a lower blade tip Mach number, thus its hovering performance improvement is smaller.

[0090] Table 3 compares the aerodynamic efficiency of the initial and optimized blades at cruise speed (360 km / h). It shows that the front rotor's cruise efficiency is improved by 10.3%, while the rear rotor's is improved by 8.9%. This is because in forward flight (fixed-wing mode), the rear rotor is almost entirely within the wake region of the front rotor. The front rotor's wake has a greater impact on the rear rotor than the rotor tip shape. Since the front rotor's operating flow field is simpler, its cruise efficiency improvement is greater than that of the rear rotor.

[0091] Table 3 Comparison of Cruise Efficiency between Initial and Optimized Propellers

[0092] Serial Number cruise efficiency of the front rotor Rear rotor cruise efficiency Initial blade 0.4535 0.5702 Optimize blades 0.4992 0.6213

[0093] Fourth, the optimization results of the pressure coefficient cloud map on the upper surface of the front / rear rotor in forward flight state are as follows: Figure 17 , Figure 18 , Figure 19 and Figure 20 As shown, the peak negative pressure region on the upper surface of the rotor blades before and after optimization is significantly smaller than that of the initial blades. Reducing the peak negative pressure region helps lower blade aerodynamic drag, further reducing torque and improving cruise efficiency. Furthermore, the reduced blade negative pressure intensity helps decrease rotor load noise.

[0094] Fifth, the sound pressure time history of the optimized rotor blades and the initial blade hovering state at the observation point is compared as follows: Figure 21 As shown, the peak value of the initial blade at the observation point is 4.71 Pa, while the peak value of the optimized blade at the same position is 3.74 Pa. The negative pressure peak value of the optimized blade is reduced by 20.5%. The reduction in sound pressure level intensity of the optimized blade at the above observation point indicates that the aerodynamic noise control level of the optimized blade is better than that of the initial blade.

[0095] Sixth, a comparison of the horizontal propagation characteristics of the hovering state optimized blade and the initial blade in the hovering state is shown below. Figure 22 As shown, it can be seen that the maximum sound pressure level of both the optimized blade and the initial blade appears at the rear of the fuselage horizontal plane. The sound pressure level of the optimized blade is generally lower than that of the initial blade within the horizontal range of the fuselage, with the largest decrease in sound radiation intensity in the middle and rear of the fuselage, and the maximum noise level can be reduced by 1.8 dB.

[0096] Seventh, a comparison of the sound pressure time history of the optimized propeller blades and the initial propeller blades at an observation point 10R (R is the rotor radius) directly in front of the nose on the horizontal plane of the fuselage during forward flight. Figure 23 As shown, the peak negative pressure of the initial blade is 5.306 Pa, while the peak negative pressure of the optimized blade at the same position is 4.149 Pa. The peak negative pressure of the optimized blade is 21.8% lower than that of the initial blade, which indicates that the optimized blade has a better aerodynamic noise control level than the initial blade in forward flight.

[0097] Eighth, optimize the horizontal propagation characteristics of the propeller blades and the initial blades during forward flight, such as... Figure 24 As shown, the maximum sound pressure level appears directly in front of the nose. The optimized blades generally reduce the sound pressure level intensity within the horizontal range of the fuselage compared to the initial blades, with the largest reduction occurring in the middle and rear of the fuselage, where the sound pressure level can be reduced by up to 2.2 dB.

[0098] The technical effects of this application are as follows:

[0099] First, this application formulates rotor optimization objectives based on the design requirements of tiltrotor aircraft; it parameterizes the original blades and constructs multiple tiltrotor aircraft models; it selects a target tiltrotor aircraft model and uses the whole-aircraft flow field solution and aerodynamic noise assessment methods to obtain the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor aircraft model under multi-rotor aerodynamic interference, and calculates the rotor comprehensive performance design evaluation index of the target tiltrotor aircraft model; this application considers the influence of complex aerodynamic interference between multi-rotor aircraft blades, obtains accurate rotor comprehensive performance design evaluation index, and selects the blade parameters of the target tiltrotor aircraft model that exceed the rotor comprehensive performance design evaluation index as the target blade parameter output, thus obtaining target blade parameters that are closer to the actual aerodynamic performance.

[0100] Secondly, this application conducts collaborative optimization of rotor noise / aerodynamic characteristics and multi-flight state performance under the aerodynamic disturbance environment of a tiltrotor multirotor. The optimization objective can be dynamically adjusted according to the application scenario of the tiltrotor multirotor through weighting factors. A surrogate model method based on Latin hypercube and BP neural network effectively reduces CFD calculation examples and improves computational efficiency while ensuring computational accuracy. Simultaneously, a combined optimization algorithm integrating the surrogate model and genetic algorithm solves the complex optimal numerical solution problem involving multiple parameters, multiple design variables, and multiple choices in the rotor aerodynamic shape optimization process. This promotes the application of global optimization algorithms based on surrogate models and genetic algorithms to complex engineering problems and has significant practical engineering value.

[0101] Example 2: This application also provides a computer device, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 25As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores video tag processing data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements the methods described above.

[0102] Those skilled in the art will understand that Figure 25 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.

[0103] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0104] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0105] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for optimizing the shape of a tiltrotor aircraft's high-efficiency, low-noise rotor, characterized in that... The method for optimizing the shape of the tiltrotor aircraft's high-efficiency, low-noise rotor includes: Based on the design requirements of the tiltrotor multirotor, rotor optimization objectives are formulated; these objectives are rotor comprehensive performance design evaluation indicators; these indicators are obtained by weighting the aerodynamic performance and noise level of the tiltrotor multirotor; the calculation formula for these indicators is as follows: ； ； ； ； In the formula, P is the overall performance design evaluation index of the rotor. This refers to the hovering efficiency of a tiltrotor aircraft in helicopter mode. SPL represents the cruise efficiency of the tiltrotor aircraft in fixed-wing mode; SPL represents the aerodynamic noise level of the tiltrotor aircraft; SPL1 represents the noise level of the tiltrotor aircraft in fixed-wing mode; and SPL2 represents the noise level of the tiltrotor aircraft in helicopter mode. For the advance ratio of the tilt rotor, For the thrust coefficient of the tilt rotor, is the power coefficient of the tilt rotor, and a and b are weighting coefficients; The original blades were parameterized, and multiple tiltrotor models were constructed. Select one tiltrotor aircraft model from among multiple tiltrotor aircraft models as the target tiltrotor aircraft model; Based on the target tiltrotor model, the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor model under multi-rotor aerodynamic interference are obtained by solving the flow field of the whole aircraft and evaluating aerodynamic noise, respectively. The rotor comprehensive performance design evaluation index of the target tiltrotor model is also calculated. Determine whether the rotor comprehensive performance design evaluation index of the target tiltrotor aircraft model is greater than the target threshold. If so, output the blade parameters of the target tiltrotor aircraft model as the target blade parameters; otherwise, return "Select one from multiple tiltrotor aircraft models as the target tiltrotor aircraft model".

2. The method for optimizing the shape of a tiltrotor multirotor with high efficiency and low noise according to claim 1, characterized in that, The original blades were parameterized, and multiple tiltrotor models were constructed, including: The original blade is parameterized to obtain the design parameter range of the blade feature points; the blade feature points include: forward sweep feature points, backward sweep feature points, and downward reflection feature points; By selecting different parameters within the design parameter range of the blade feature points, multiple basic propeller shapes can be constructed. Multiple tiltrotor aircraft models were constructed based on multiple basic rotor designs.

3. The method for optimizing the shape of a tiltrotor multirotor with high efficiency and low noise according to claim 2, characterized in that, The original blades are parameterized to obtain the design parameter range for the blade feature points, specifically including: The aerodynamic layout parameters of the original blade model were designed by forward sweep, backward sweep, and downward reflection, and the characteristic points of the blade were determined. The blade feature points are parameterized to obtain the design parameter range for the blade feature points.

4. The method for optimizing the shape of a tiltrotor multirotor with high efficiency and low noise according to claim 2, characterized in that, By selecting different parameters within the design parameter range of the blade feature points, multiple basic propeller profiles are constructed, including: Within the design parameter range of the blade feature points, different parameters are selected according to the number of rotors using the Latin hypercube method, and multiple basic rotor shapes are constructed based on these different parameters.

5. The method for optimizing the shape of a tiltrotor multirotor with high efficiency and low noise according to claim 2, characterized in that, By selecting different parameters within the design parameter range of the blade feature points, multiple basic propeller shapes are constructed. The subsequent steps also include: using a BP neural network approximation model optimized by a genetic algorithm to perform preliminary optimization on the multiple basic propeller shapes.

6. The method for optimizing the shape of a high-efficiency, low-noise tiltrotor aircraft according to claim 1, characterized in that, Based on the target tiltrotor aircraft model, the aerodynamic performance parameters and aerodynamic noise level of the target tiltrotor aircraft model were obtained by solving the whole-aircraft flow field and evaluating aerodynamic noise, respectively. The comprehensive rotor performance design evaluation index of the target tiltrotor aircraft model was then calculated, specifically including: Based on the fuselage and wing parameters and the aerodynamic layout parameters of multiple blades in the target tiltrotor aircraft model, the fuselage and wing meshes and blade meshes of the multi-rotor target tiltrotor aircraft model are constructed respectively. The flow field of the entire aircraft is solved based on the fuselage, wing and blade meshes of the target tiltrotor aircraft model, and the aerodynamic performance parameters of the target tiltrotor aircraft model under multi-rotor aerodynamic disturbance are obtained. Aerodynamic noise was evaluated on the target tiltrotor aircraft model to obtain the aerodynamic noise level of the target tiltrotor aircraft model under multi-rotor aerodynamic interference. The comprehensive rotor performance design evaluation index of the target tiltrotor model is obtained based on aerodynamic performance parameters and aerodynamic noise level calculations.

7. The method for optimizing the shape of a tiltrotor multirotor with high efficiency and low noise according to claim 1, characterized in that, a=0.6; b=0.

4.

8. The method for optimizing the shape of a high-efficiency, low-noise tiltrotor aircraft according to claim 1, characterized in that, The flow field solution for the entire machine is obtained using a CFD method based on the RANS master control equations.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for optimizing the shape of a tiltrotor rotor with high efficiency and low noise, as described in any one of claims 1-8.

Images