Aerodynamic and structural optimization method for high-altitude adaptive deformation composite propeller

Abstract

The present application belongs to the field of structural optimization design, and specifically discloses an aerodynamic and structural optimization method for high-altitude adaptive deformation composite propellers, including establishing a composite propeller ply optimization model and initializing the model's design variables; establishing a serialized regional fiber sub-model of the composite propeller ply optimization model, and performing optimization operations in the serialized regional fiber sub-model; reading the output data of the composite propeller ply optimization model through simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional plies; using the optimization objective function set by the serialized regional fiber sub-model for the allowable strain, the pitch angle at the design point, and the minimum number of regional plies, iteratively optimize the algorithm according to the set number of individuals in the population and the number of iterations, until the iteration is completed and the optimal individual for ply optimization is output. The structural optimization of high-altitude propellers can be achieved through the present application.

Description

Technical Field

[0001] The present application belongs to the field of structural optimization design, and more specifically, relates to an aerodynamic and structural optimization method for a high-altitude adaptive deformable composite propeller. Background Art

[0002] Near-space refers to the airspace between 20 and 100 kilometers, known as the "air-space transition zone." This area not only impacts satellite activities but also carries the burden of monitoring, jamming, and defending against enemy space assets. Solar-powered drones with a flight time of 20 to 30 kilometers, due to their high efficiency, energy efficiency, and theoretically unlimited cruising capabilities, have become a key focus and hot topic in the development of low-dynamic aircraft. Their unique design specifications and mission characteristics place high demands on various key technologies.

[0003] The propulsion system for solar-powered drones primarily consists of motors and propellers, requiring lightweight construction, high propulsion efficiency, and excellent propeller-motor matching. The performance of a propeller propulsion system is not simply the sum of the individual performance of the propeller and motor, but rather a comprehensive approach within matching constraints. The most critical factor is the matching of power with propeller speed, chord length, and pitch angle. For a highly matched propulsion system, the propeller and motor should reach their maximum efficiency under a given flight regime (design point). Solar-powered drones must adjust their operating altitude and flight speed throughout their flight envelope based on mission requirements and energy balance, with a wide range of altitudes and speeds. The wide range of atmospheric density and forward ratio adjustments results in drastic fluctuations in propeller shaft power and torque, leading to poor propeller-motor matching when operating conditions deviate from the design point. To achieve wide-range propeller-motor matching, commonly used solutions include using motors with higher rated power, dual propellers, or variable pitch mechanisms. These inevitably come at a weight penalty, and the reliability of the variable pitch mechanism can also impact the drone's long-endurance performance.

[0004] For cross-altitude near-space propeller propulsion systems, the adaptability to wide operating conditions is similar to that faced by wind turbine blades and marine propellers, that is, both need to solve the problem of poor propeller-machine matching when deviating from the design point, but they also face new challenges, such as more complex operating conditions, a wide speed variation range of near-space aircraft, and a large flight altitude span.

[0005] Adaptive deformation technology is primarily used in wind turbine blades and composite propeller blades. Adaptive deformation enables dynamic matching between blades and operating conditions, effectively improving blade performance and overall system efficiency.

[0006] However, the structural optimization in the current existing technologies has the following main defects: (1) Compared with wind turbine blades and marine propeller blades, the rotation speed of high-altitude propellers is higher, and the centrifugal force caused by the rotation will also cause the structure itself to produce a deformation coupling effect. Therefore, the design goals and deformation requirements of the adaptive deformation of high-altitude propellers are different. (2) The optimization algorithm plays a key role in the aerodynamic performance and structural optimization of the propeller, but the existing basic algorithms often face problems such as high computational cost, slow convergence speed, and easy to fall into local optimal solutions. Especially when facing complex engineering problems, the efficiency and accuracy still need to be improved. (3) Composite materials provide new possibilities in propeller design, especially in terms of improving strength and reducing weight. However, balancing design requirements and material properties to improve structural performance is still one of the main challenges currently faced.

[0007] Therefore, how to solve the defects of poor structural optimization effect of high-altitude propellers caused by the propeller's own demand characteristics, poor efficiency and accuracy of optimization algorithms, and material selection is a technical problem that needs to be solved urgently. Summary of the Invention

[0008] In response to the defects of the existing technology, the purpose of this application is to provide an aerodynamic and structural optimization method for high-altitude adaptive deformable composite propellers, aiming to solve the defects of poor structural optimization effect of high-altitude propellers caused by the propeller's own demand characteristics, poor efficiency and accuracy of the optimization algorithm, and material selection.

[0009] To achieve the above objectives, the present application provides a method for aerodynamic and structural optimization of a high-altitude adaptive deformable composite propeller, comprising:

[0010] Establish a composite propeller layup optimization model and initialize the model's design variables;

[0011] Establishing a serialized regional fiber sub-model of the composite propeller layup optimization model, and performing optimization calculations in the serialized regional fiber sub-model;

[0012] The output data of the composite propeller layup optimization model is read by simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups;

[0013] The allowable strain, the pitch angle at the design point and the minimum number of regional plies are used to set the optimization objective function of the serialized regional fiber sub-model. According to the set number of algorithm population individuals and the number of iterations, the guide layer ply angle, guide layer coverage length and regional sequence of the composite material are iteratively optimized until the iteration is completed and the optimal individual for ply optimization is output.

[0014] In some embodiments, establishing a serialized regional fiber sub-model of the composite propeller layup optimization model and performing an optimization operation in the serialized regional fiber sub-model includes:

[0015] Constructing a sequenced regional fiber sub-model, wherein the sequenced regional fiber sub-model is determined based on the GBBM guide layer parameters and in combination with the regional sequence, the guide layer layup angle, and the guide layer cover length factor;

[0016] Selecting the guide layer laying angle, the guide layer coverage length, and the region sequence, determining the individual code corresponding to each angle, and determining the angle sequence corresponding to the guide layer laying angle according to the individual code;

[0017] determining a guide layer coverage length corresponding to each angle, and paving regions of the region sequence according to the guide layer coverage length;

[0018] The OX operator is used to perform sequence crossover in the plying region, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated genes to obtain a new offspring individual.

[0019] In some embodiments, the method of performing ply region sequence crossover using the OX operator, selecting a split position from two parent generations and inheriting the intermediate gene of the first parent generation individual, rotating the second parent generation individual and filling in non-repeated genes to obtain a new offspring individual, comprises:

[0020] Performing position segmentation on the first parent individual and the second parent individual to determine a first segmentation position and a second segmentation position of the first parent individual, and a third segmentation position and a fourth segmentation position of the second parent individual;

[0021] Determining an intermediate gene between the first cleavage position and the second cleavage position, so that the first offspring individual inherits the intermediate gene;

[0022] Rotating the second parent individual at the third split position to obtain a rotated gene;

[0023] screening the rotated genes for genes that are repeated in the first offspring individual to obtain remaining genes;

[0024] filling the remaining genes into the empty genes after the second split position of the first progeny individual in order to obtain an optimized first progeny;

[0025] The positions of the first parent individual and the second parent individual are exchanged, and the crossover operation is repeated to obtain the second offspring.

[0026] In some embodiments, establishing a composite propeller layup optimization model includes:

[0027] Establishing a geometric model of the propeller in the target software, meshing the propeller using mesh units, setting the propeller radius, and determining the composite material of each region of the propeller;

[0028] Calculate the aerodynamic load process of the propeller airfoil and obtain the pressure at the pressure point of the propeller;

[0029] The aerodynamic node loads in the propeller airfoil structure are converted into finite element node loads using the four-point row distribution method.

[0030] The composite propeller layup optimization model is determined based on the propeller radius, composite material, pressure point pressure and finite element node load.

[0031] In some embodiments, the process of calculating the aerodynamic load of the propeller airfoil to obtain the pressure at the pressure point of the propeller includes:

[0032] Calculating and interpolating the propeller using a fast propagation algorithm to obtain a tension coefficient of each cross section of the propeller and a pressure coefficient of each pressure point of the cross section;

[0033] The pressure at infinity of the propeller is obtained according to the local atmospheric density and the total velocity of each cross section of the propeller in combination with the tension coefficient and the pressure coefficient of each cross section;

[0034] The local pressure is obtained according to the altitude and the atmospheric parameters, and the pressure at the pressure point of the propeller is obtained according to the pressure at infinity and the local pressure.

[0035] In some embodiments, converting the aerodynamic nodal loads in the propeller airfoil structure into finite element nodal loads using a four-point row distribution method includes:

[0036] Distributing the aerodynamic node load to four adjacent structural points according to the energy equivalence principle, and forming a quadrilateral through the four structural points;

[0037] Based on the aerodynamic nodes, equal percentage lines are drawn for the quadrilateral to obtain four small quadrilaterals;

[0038] The finite element node loads allocated to each small quadrilateral are obtained according to the area ratio between each small quadrilateral deformation and the quadrilateral and the aerodynamic node load.

[0039] In some embodiments, the optimization objective function is as shown in the following formula:

[0040] minf(x)=max(β1-β2)

[0041]

[0042] Where β1 represents the profile pitch after deformation under non-design conditions; β2 represents the optimal profile pitch; RF represents the ratio of the maximum strain of the propeller to the allowable strain of the composite material; ε i Indicates the maximum strain of the propeller in any direction of x, y, xy; β real Indicates the pitch angle of each section of the propeller after deformation; β obj Indicates optimized paddle; Panel ply Indicates the number of plies in each area.

[0043] In a second aspect, the present application also provides an aerodynamic and structural optimization device for a high-altitude adaptive deformable composite propeller, comprising:

[0044] Model building module, used to establish composite propeller layup optimization model and initialize the model's design variables;

[0045] a sub-model establishment module, configured to establish a serialized regional fiber sub-model of the composite propeller layup optimization model and perform optimization calculations in the serialized regional fiber sub-model;

[0046] A simulation module is used to read the output data of the composite propeller layup optimization model through simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups;

[0047] The iterative optimization module is used to use the optimization objective function set by the serialized regional fiber sub-model for the allowable strain, the pitch angle at the design point and the minimum number of regional plies, and iteratively optimize the guide layer ply angle, guide layer coverage length and regional sequence of the composite material according to the set number of algorithm population individuals and the number of iterations until the iteration is completed and the optimal individual for ply optimization is output.

[0048] In a third aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0049] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0050] In a fifth aspect, the present application provides a computer program product, which, when executed on a processor, enables the processor to execute the method described in the first aspect or any possible implementation of the first aspect.

[0051] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0052] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the existing technologies:

[0053] (1) This application uses simulation software to read the output data of the layup optimization model, the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of plies in the region, which can ensure the accuracy and reliability of the data. By optimizing the propeller design through composite layup, the matching of the propeller and the motor is improved, and the propeller's adaptive deformation under cross-height conditions is achieved, which improves the propeller-motor matching and enhances the propeller's aerodynamic performance.

[0054] (2) This application performs iterative optimization based on the number of individuals in the algorithm population and the number of iterations, which can effectively explore the design space and improve optimization efficiency. The use of optimization algorithms can avoid falling into local optimal solution problems and improve the overall optimization effect. Through iterative optimization until the optimal individual for ply optimization is obtained, it can ensure that the final design achieves optimal performance on a global scale, which helps to improve the aerodynamic performance, structural performance and material utilization efficiency of the propeller.

[0055] (3) This application utilizes the allowable strain of composite materials and the minimum number of regional plies for optimized design, which can maximize the strength and weight advantages of composite materials, thereby improving the overall performance of the propeller. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is one of the flow charts of the aerodynamic and structural optimization method for a high-altitude adaptive deformable composite propeller provided in an embodiment of the present application;

[0057] Figure 2 This is a finite element model diagram of the propeller in the embodiment of this application;

[0058] Figure 3 This is a schematic diagram of a continuous fiber model of a serialized region in an embodiment of the present application;

[0059] Figure 4 This is an individual schematic diagram of a serialized region continuous fiber layup model in an embodiment of the present application;

[0060] Figure 5 This is a schematic diagram of the crossover of regional sequences in the embodiments of this application;

[0061] Figure 6 This is a schematic diagram of a four-point arrangement in an embodiment of the present application;

[0062] Figure 7This is a schematic diagram of the optimization interaction process in the embodiment of this application;

[0063] Figure 8 The second flow chart of the aerodynamic and structural optimization method for a high-altitude adaptive deformable composite propeller provided in an embodiment of the present application;

[0064] Figure 9 This is a schematic structural diagram of a high-altitude adaptive deformable composite propeller aerodynamic and structural optimization device provided in an embodiment of the present application;

[0065] Figure 10 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0067] The term "and / or" as used herein describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. The symbol " / " as used herein indicates that the related objects are in an "or" relationship, for example, A / B means either A or B.

[0068] The terms "first" and "second" in this specification and claims are used to distinguish different objects rather than to describe a specific order of objects. For example, "first response message" and "second response message" are used to distinguish different response messages rather than to describe a specific order of response messages.

[0069] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0070] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more, for example, multiple processing units means two or more processing units, etc.; multiple elements means two or more elements, etc.

[0071] Next, the technical solutions provided in the embodiments of this application are introduced.

[0072] Reference Figure 1The present application provides a method for aerodynamic and structural optimization of a high-altitude adaptive deformable composite propeller, comprising:

[0073] S101. Establish a composite propeller layup optimization model and initialize the model's design variables;

[0074] S102. Establishing a serialized regional fiber sub-model of the composite propeller layup optimization model, and performing optimization calculations in the serialized regional fiber sub-model;

[0075] S103. Reading the output data of the composite propeller layup optimization model through simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups;

[0076] S104. The allowable strain, the pitch angle at the design point, and the minimum number of regional plies are used as the optimization objective function set by the serialized regional fiber sub-model. According to the set number of algorithm population individuals and the number of iterations, the guide layer ply angle, guide layer coverage length, and regional sequence of the composite material are iteratively optimized until the iteration is completed and the optimal individual for ply optimization is output.

[0077] First, refer to Figure 2 , Figure 2 This is a diagram of the propeller finite element model. Build a composite propeller layup optimization model and initialize the design variables. These variables can include propeller radius, material type, propeller point pressure, and other parameters, which are set according to design requirements.

[0078] Specifically, a geometric model of the propeller is established in the target software, the propeller is meshed using mesh units, the propeller radius is set, and the composite material of each area of ​​the propeller is determined;

[0079] Calculate the aerodynamic load process of the propeller airfoil and obtain the pressure at the pressure point of the propeller;

[0080] The aerodynamic node loads in the propeller airfoil structure are converted into finite element node loads using the four-point row distribution method.

[0081] The composite propeller layup optimization model is determined based on the propeller radius, composite material, pressure point pressure and finite element node load.

[0082] Secondly, the composite propeller structure is divided into multiple sub-regions, and a sequenced regional fiber sub-model is established for each sub-region. By performing detailed optimization calculations within each sub-region, the optimization accuracy can be improved.

[0083] The output data of the composite propeller layup optimization model, including the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of plies in the region, is read using the simulation software MATLAB. This output data serves as the constraints or objective function in the optimization process.

[0084] The optimization objective function set in the sequenced regional fiber sub-model is used to clarify the optimization direction. The objective function can be to minimize the allowable strain of the composite material, maximize the pitch angle at the design point, or meet the minimum ply requirement in the region.

[0085] The optimization objective function is shown in the following formula:

[0086] minf(x)=max(β1-β2)

[0087]

[0088] Where β1 represents the profile pitch after deformation under non-design conditions; β2 represents the optimal profile pitch; RF represents the ratio of the maximum strain of the propeller to the allowable strain of the composite material; ε i Indicates the maximum strain of the propeller in any direction of x, y, xy; β real Indicates the pitch angle of each section of the propeller after deformation; β obj Indicates optimized paddle; Panel ply Indicates the number of plies in each area.

[0089] Finally, based on the set number of algorithm population individuals and the number of iterations, iterative optimization is performed for the composite material's allowable strain, pitch angle at the design point, and minimum regional ply number. The optimization algorithm can employ methods such as genetic algorithms and particle swarm optimization to find the optimal layup solution. After the iterative optimization is complete, the optimal individual for the layup optimization is obtained. This optimal individual will produce the optimal composite propeller layup solution, meeting design requirements and improving overall performance. This automates the composite propeller layup optimization process, improving design efficiency and performance, and fully leveraging the advantages of composite materials in propeller design.

[0090] In some embodiments, establishing a serialized regional fiber sub-model of the composite propeller layup optimization model and performing an optimization operation in the serialized regional fiber sub-model includes:

[0091] Constructing a sequenced regional fiber sub-model, wherein the sequenced regional fiber sub-model is determined based on the GBBM guide layer parameters and in combination with the regional sequence, the guide layer layup angle, and the guide layer cover length factor;

[0092] Selecting the guide layer laying angle, the guide layer coverage length, and the region sequence, determining the individual code corresponding to each angle, and determining the angle sequence corresponding to the guide layer laying angle according to the individual code;

[0093] determining a guide layer coverage length corresponding to each angle, and paving regions of the region sequence according to the guide layer coverage length;

[0094] The OX operator is used to perform sequence crossover in the plying region, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated genes to obtain a new offspring individual.

[0095] Furthermore, the iterative process between parent individuals and child individuals is as follows:

[0096] Performing position segmentation on the first parent individual and the second parent individual to determine a first segmentation position and a second segmentation position of the first parent individual, and a third segmentation position and a fourth segmentation position of the second parent individual;

[0097] Determining an intermediate gene between the first cleavage position and the second cleavage position, so that the first offspring individual inherits the intermediate gene;

[0098] Rotating the second parent individual at the third split position to obtain a rotated gene;

[0099] screening the rotated genes for genes that are repeated in the first offspring individual to obtain remaining genes;

[0100] filling the remaining genes into the empty genes after the second split position of the first progeny individual in order to obtain an optimized first progeny;

[0101] The positions of the first parent individual and the second parent individual are exchanged, and the crossover operation is repeated to obtain the second offspring.

[0102] Specifically, refer to Figure 3 In this embodiment, the regional sequence, the guide layer laying angle, and the guide layer coverage length factor are combined with the GBBM guide layer parameters to establish a sequenced regional fiber sub-model, and then the model optimization operation is performed, as follows:

[0103] First, a continuous fiber layup model with sequenced regions was constructed. Based on the GBBM guide layer parameters, this model introduced design variables for the region sequence and the guide layer coverage length factor. The region sequence allows the model to handle the layup requirements of multiple critical regional structures, and the guide layer coverage length broadens the feasible space for layup design. For example, the layup parameters are (P1 P2 P3 P4 P5, 3 5 5 4 3, 4 2 3 5 1), and the meaning of each parameter is as follows:

[0104] 1. The guide layer laying angle is: P1 P2 P3 P4 P5;

[0105] 2. (3 5 5 4 3) is the factor for the number of areas covered by the guide layer. The first number 3 means that 3 areas are laid for the first single layer P1 of the guide laminate.

[0106] 3. (4 2 3 5 1) The sequence factor represents the order of the regional pavement. For example, P1 corresponds to 3 paving areas. According to the regional sequence, the paving areas 4, 2, and 3 are laid.

[0107] Reference Figure 4 Second, set up encoding and decoding. To better meet manufacturing requirements, ply angles are selected from 0°, ±45°, and 90°. The corresponding individual codes are: 2 for 90°, 1 for 45°, 0 for 0°, and -1 for -45°. The second array represents the length of each guide layer. The third array represents the region sequence. The guide layer angles of the individual shown are (0 / -45 / 45 / 90 / 45). According to the guide layer laying angle sequence: (0 / -1 / 1 / 2 / 1), 0° corresponds to a laying length of 3, and according to the area sequence (3 / 1 / 5 / 2 / 4), three areas 3, 1, and 5 are laid; -45° corresponds to a laying length of 5, and according to the area sequence, five areas 3, 1, 5, 2, and 4 are laid; 45° corresponds to a laying length of 1, and according to the area sequence, the third area is laid; 90° corresponds to a laying length of 4, and according to the area sequence, the third, 1, 5, and 2 are laid; the last laying angle of 45° corresponds to a laying length of 5, and according to the area sequence, five areas 3, 1, 5, 2, and 4 are laid.

[0108] Third, set the individual crossover operator.

[0109] Reference Figure 5To address the problem of regional sequence crossover, the OX operator, which solves the TSP problem, is introduced as a crossover method for plying regional sequences. The crossover regional sequence is then spliced ​​with the rest of the individual to form a new plying individual (the rest of the individual crosses normally). First, OX selects the parent's split position, and the first offspring inherits the intermediate gene between the two split positions of the first parent. Subsequently, the second parent is rotated about the second split position. Finally, the rotated parent's genes are filtered to identify genes that differ from those of the first offspring. These filtered genes are then used in order to fill the empty gene after the second split position in the first offspring, yielding the first offspring. Reversing the order of the parents and performing the same crossover operation yields the second offspring. For example, the two parent genes p1 and p2 are (24|3 5|1 6) and (1 2|4 6|3 5), respectively, with the vertical bars representing the split positions. The offspring c1 inherits the intermediate gene at p1's split position, (0 0|3 5|0 0), with '0' representing an empty gene. Then, p2 is rotated at the second split position (1 2 | 4 6 | 3 5) to (3 5 1 2 4 6). Next, the duplicate genes '3' and '5' in c1 are filtered out, leaving q2 (1 2 4 6). Finally, q2 is filled in with the empty gene after the second truncation position in c1, resulting in the daughter c1 = (4 6 35 1 2). The same crossover operation is performed on the parent p1 and p2, yielding the daughter c2 = (3 5 4 6 1 2).

[0110] Furthermore, the specific process of establishing the composite propeller layup optimization model using finite element software includes the following steps:

[0111] Calculating and interpolating the propeller using a fast propagation algorithm to obtain a tension coefficient of each cross section of the propeller and a pressure coefficient of each pressure point of the cross section;

[0112] The pressure at infinity of the propeller is obtained according to the local atmospheric density and the total velocity of each cross section of the propeller in combination with the tension coefficient and the pressure coefficient of each cross section;

[0113] The local pressure is obtained according to the altitude and the atmospheric parameters, and the pressure at the pressure point of the propeller is obtained according to the pressure at infinity and the local pressure.

[0114] Distributing the aerodynamic node load to four adjacent structural points according to the energy equivalence principle, and forming a quadrilateral through the four structural points;

[0115] Based on the aerodynamic nodes, equal percentage lines are drawn for the quadrilateral to obtain four small quadrilaterals;

[0116] The finite element node loads allocated to each small quadrilateral are obtained according to the area ratio between each small quadrilateral deformation and the quadrilateral and the aerodynamic node load.

[0117] Specifically, first, a finite element model was established using the commercial software Hyperworks, the mesh unit used was the SHELL-CQUAD4 unit, the propeller radius was R = 1000 mm, and each area of ​​the propeller was set to use the fuhe material T700 ply.

[0118] Second, calculate the aerodynamic load process of the propeller wing. The specific process is to calculate and interpolate the propeller through QPROP, obtain the tension coefficient of each section, and output the pressure coefficient Cp of 161 points of each section under three working conditions. Through the formula dp=C p ×ρV 2 / 2, calculate the pressure dp at the infinite distance of the propeller, where ρ is the local atmospheric density and V is the total velocity of each section of the propeller. Then, according to the different altitudes H, the corresponding atmospheric parameters are obtained to obtain the local pressure (PH), and the formula P = dp + P H , calculate the pressure at each point.

[0119] Third, the four-point row distribution method is used to convert the starting node loads in the above-mentioned wing structure into finite element node loads. Figure 6 The so-called four-point arrangement refers to the load P on the aerodynamic node C. c According to the principle of static equivalence, it is distributed to the four adjacent structural nodes. Let the structural unit quadrilateral ijhm, make an equal percentage line of the quadrilateral through the aerodynamic node C, and divide the quadrilateral ijhm into four small quadrilaterals. The area of ​​each small quadrilateral is recorded as S i 、S j 、S h 、S m , the area of ​​quadrilateral ijhm is S.

[0120] Load P c The calculation formula assigned to these four structural nodes is P k =(S k / S)×P c , where k = i, j, h, m. The forces assigned to the same structural node are superimposed to obtain the equivalent nodal force, which can be used to obtain the propeller load model.

[0121] Furthermore, the specific process of using MATLAB to write the information interaction optimization program in the embodiment of the present application is as follows Figure 7 As shown, it specifically includes the following steps:

[0122] First, rewrite the .fem material card by optimizing the interface.

[0123] Second, call OptiStruct to perform model solution calculations on the updated .fem file and generate *.disp and *.strain result files.

[0124] Third, the optimizer reads the result file and performs constraints and filtering based on the obtained data.

[0125] Reference Figure 8 , Figure 8 This is a complete flow chart of a method for aerodynamic and structural optimization of a high-altitude adaptive deformable composite propeller provided in an embodiment of the present application, including the following steps:

[0126] Establish a composite propeller layup optimization model;

[0127] Initialize the design variables of the composite propeller layup optimization model;

[0128] Establish a serialized regional fiber model and perform optimization calculations;

[0129] An information interaction optimization program is used to obtain the required strain of the composite material, the pitch angle at the design point, and the minimum number of plies in the region;

[0130] Bring in the optimization objective function for calculation;

[0131] Determine whether the algebraic operation is completed;

[0132] Output the optimal individual for ply optimization.

[0133] Reference Figure 9 The present application also provides an aerodynamic and structural optimization device for a high-altitude adaptive deformable composite propeller, comprising:

[0134] A model building module 910 is used to build a composite propeller layup optimization model and initialize the design variables of the model;

[0135] A sub-model building module 920 is used to build a serialized regional fiber sub-model of the composite propeller layup optimization model and perform optimization calculations in the serialized regional fiber sub-model;

[0136] A simulation module 930 is configured to read output data of the composite propeller layup optimization model through simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups;

[0137] The iterative optimization module 940 is used to use the optimization objective function set by the serialized regional fiber sub-model for the allowable strain, the pitch angle at the design point, and the minimum number of regional plies, and iteratively optimize the guide layer ply angle, guide layer coverage length, and regional sequence of the composite material according to the set number of algorithm population individuals and the number of iterations until the iteration is completed and the optimal individual for ply optimization is output.

[0138] In some embodiments, establishing a serialized regional fiber sub-model of the composite propeller layup optimization model and performing an optimization operation in the serialized regional fiber sub-model includes:

[0139] Constructing a sequenced regional fiber sub-model, wherein the sequenced regional fiber sub-model is determined based on the GBBM guide layer parameters and in combination with the regional sequence, the guide layer layup angle, and the guide layer cover length factor;

[0140] Selecting the guide layer laying angle, the guide layer coverage length, and the region sequence, determining the individual code corresponding to each angle, and determining the angle sequence corresponding to the guide layer laying angle according to the individual code;

[0141] determining a guide layer coverage length corresponding to each angle, and paving regions of the region sequence according to the guide layer coverage length;

[0142] The OX operator is used to perform sequence crossover in the plying region, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated genes to obtain a new offspring individual.

[0143] In some embodiments, the method of performing ply region sequence crossover using the OX operator, selecting a split position from two parent generations and inheriting the intermediate gene of the first parent generation individual, rotating the second parent generation individual and filling in non-repeated genes to obtain a new offspring individual, comprises:

[0144] Performing position segmentation on the first parent individual and the second parent individual to determine a first segmentation position and a second segmentation position of the first parent individual, and a third segmentation position and a fourth segmentation position of the second parent individual;

[0145] Determining an intermediate gene between the first cleavage position and the second cleavage position, so that the first offspring individual inherits the intermediate gene;

[0146] Rotating the second parent individual at the third split position to obtain a rotated gene;

[0147] screening the rotated genes for genes that are repeated in the first offspring individual to obtain remaining genes;

[0148] filling the remaining genes into the empty genes after the second split position of the first progeny individual in order to obtain an optimized first progeny;

[0149] The positions of the first parent individual and the second parent individual are exchanged, and the crossover operation is repeated to obtain the second offspring.

[0150] In some embodiments, establishing a composite propeller layup optimization model includes:

[0151] Establishing a geometric model of the propeller in the target software, meshing the propeller using mesh units, setting the propeller radius, and determining the composite material of each region of the propeller;

[0152] Calculate the aerodynamic load process of the propeller airfoil and obtain the pressure at the pressure point of the propeller;

[0153] The aerodynamic node loads in the propeller airfoil structure are converted into finite element node loads using the four-point row distribution method.

[0154] The composite propeller layup optimization model is determined based on the propeller radius, composite material, pressure point pressure and finite element node load.

[0155] In some embodiments, the process of calculating the aerodynamic load of the propeller airfoil to obtain the pressure at the pressure point of the propeller includes:

[0156] Calculating and interpolating the propeller using a fast propagation algorithm to obtain a tension coefficient of each cross section of the propeller and a pressure coefficient of each pressure point of the cross section;

[0157] The pressure at infinity of the propeller is obtained according to the local atmospheric density and the total velocity of each cross section of the propeller in combination with the tension coefficient and the pressure coefficient of each cross section;

[0158] The local pressure is obtained according to the altitude and the atmospheric parameters, and the pressure at the pressure point of the propeller is obtained according to the pressure at infinity and the local pressure.

[0159] In some embodiments, converting the aerodynamic nodal loads in the propeller airfoil structure into finite element nodal loads using a four-point row distribution method includes:

[0160] Distributing the aerodynamic node load to four adjacent structural points according to the energy equivalence principle, and forming a quadrilateral through the four structural points;

[0161] Based on the aerodynamic nodes, equal percentage lines are drawn for the quadrilateral to obtain four small quadrilaterals;

[0162] The finite element node loads allocated to each small quadrilateral are obtained according to the area ratio between each small quadrilateral deformation and the quadrilateral and the aerodynamic node load.

[0163] In some embodiments, the optimization objective function is as shown in the following formula:

[0164] minf(x)=max(β1-β2)

[0165]

[0166] Where β1 represents the profile pitch after deformation under non-design conditions; β2 represents the optimal profile pitch; RF represents the ratio of the maximum strain of the propeller to the allowable strain of the composite material; ε i Indicates the maximum strain of the propeller in any direction of x, y, xy; β real Indicates the pitch angle of each section of the propeller after deformation; β obj Indicates optimized paddle; Panel ply Indicates the number of plies in each area.

[0167] It is understandable that the detailed functional implementation of each of the above units / modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0168] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method and will not be repeated here.

[0169] Reference Figure 10 Based on the methods in the above embodiments, an embodiment of the present application provides an electronic device, which may include: a processor 1010, a communications interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communications interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. The processor 1010 may call logic instructions in the memory 1030 to execute the methods in the above embodiments.

[0170] In addition, the logic instructions in the above-mentioned memory 1030 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0171] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0172] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0173] It is understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0174] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0175] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0176] It will be understood that the various numerical numbers involved in the embodiments of the present application are merely distinctions for the convenience of description and are not intended to limit the scope of the embodiments of the present application.

[0177] It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for aerodynamic and structural optimization of a high-altitude adaptive deformable composite propeller, characterized in that: include: Establish a composite propeller layup optimization model and initialize the model's design variables; Establishing a serialized regional fiber sub-model of the composite propeller layup optimization model, and performing optimization calculations in the serialized regional fiber sub-model; The output data of the composite propeller layup optimization model is read by simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups; The allowable strain, the pitch angle at the design point, and the minimum number of regional plies are used in the optimization objective function set by the serialized regional fiber sub-model, and the guide layer ply angle, guide layer coverage length, and regional sequence of the composite material are iteratively optimized according to the set number of algorithm population individuals and the number of iterations until the optimal individual for ply optimization is output after the iteration is completed; The establishing of the serialized regional fiber sub-model of the composite propeller layup optimization model and performing optimization calculations in the serialized regional fiber sub-model include: Constructing a sequenced regional fiber sub-model, wherein the sequenced regional fiber sub-model is determined based on the GBBM guide layer parameters and in combination with the regional sequence, the guide layer layup angle, and the guide layer cover length factor; Selecting the guide layer laying angle, the guide layer coverage length, and the region sequence, determining the individual code corresponding to each angle, and determining the angle sequence corresponding to the guide layer laying angle according to the individual code; determining a guide layer coverage length corresponding to each angle, and paving regions of the region sequence according to the guide layer coverage length; The OX operator is used to perform sequence crossover in the plying region, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated genes to obtain a new offspring individual.

2. The aerodynamic and structural optimization method for high-altitude adaptive deformation composite propeller according to claim 1 is characterized in that: The OX operator is used to perform ply region sequence crossover, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated gene to obtain a new offspring individual, including: Performing position segmentation on the first parent individual and the second parent individual to determine a first segmentation position and a second segmentation position of the first parent individual, and a third segmentation position and a fourth segmentation position of the second parent individual; Determining an intermediate gene between the first cleavage position and the second cleavage position, so that the first offspring individual inherits the intermediate gene; Rotating the second parent individual at the third split position to obtain a rotated gene; screening the rotated genes for genes that are repeated in the first offspring individual to obtain remaining genes; filling the remaining genes into the empty genes after the second split position of the first progeny individual in order to obtain an optimized first progeny; The positions of the first parent individual and the second parent individual are exchanged, and the crossover operation is repeated to obtain the second offspring.

3. The aerodynamic and structural optimization method for high-altitude adaptive deformation composite propeller according to claim 1 is characterized in that: The establishment of the composite propeller layup optimization model includes: Establishing a geometric model of the propeller in the target software, meshing the propeller using mesh units, setting the propeller radius, and determining the composite material of each region of the propeller; Calculate the aerodynamic load process of the propeller airfoil and obtain the pressure at the pressure point of the propeller; The aerodynamic node loads in the propeller airfoil structure are converted into finite element node loads using the four-point row distribution method. The composite propeller layup optimization model is determined based on the propeller radius, composite material, pressure point pressure and finite element node load.

4. The aerodynamic and structural optimization method for high-altitude adaptive deformation composite propeller according to claim 3 is characterized in that: The process of calculating the aerodynamic load of the propeller airfoil to obtain the pressure at the pressure point of the propeller includes: Calculating and interpolating the propeller using a fast propagation algorithm to obtain a tension coefficient of each cross section of the propeller and a pressure coefficient of each pressure point of the cross section; The pressure at infinity of the propeller is obtained according to the local atmospheric density and the total velocity of each cross section of the propeller in combination with the tension coefficient and the pressure coefficient of each cross section; The local pressure is obtained according to the altitude and the atmospheric parameters, and the pressure at the pressure point of the propeller is obtained according to the pressure at infinity and the local pressure.

5. The aerodynamic and structural optimization method for high-altitude adaptive deformation composite propeller according to claim 3 is characterized in that: The method of converting the aerodynamic node loads in the propeller airfoil structure into finite element node loads by using the four-point row distribution method includes: Distributing the aerodynamic node load to four adjacent structural points according to the energy equivalence principle, and forming a quadrilateral through the four structural points; Based on the aerodynamic nodes, equal percentage lines are drawn for the quadrilateral to obtain four small quadrilaterals; The finite element node loads allocated to each small quadrilateral are obtained according to the area ratio between each small quadrilateral deformation and the quadrilateral and the aerodynamic node load.

6. The aerodynamic and structural optimization method for a high-altitude adaptive deformable composite propeller according to any one of claims 1 to 5, characterized in that: The optimization objective function is shown in the following formula: in, It represents the profile pitch after deformation under non-design conditions; Indicates the optimal pitch of the profile; RF represents the ratio of the maximum strain of the propeller to the allowable strain of the composite material; Indicates Maximum propeller strain in any direction; Indicates the pitch angle of each section of the propeller after deformation; Indicates optimized paddle; Indicates the number of plies in each area.

7. A high-altitude adaptive deformation composite propeller aerodynamic and structural optimization device, characterized by: include: Model building module, used to establish composite propeller layup optimization model and initialize the model's design variables; a sub-model establishment module, configured to establish a serialized regional fiber sub-model of the composite propeller layup optimization model and perform optimization calculations in the serialized regional fiber sub-model; A simulation module is used to read the output data of the composite propeller layup optimization model through simulation software to obtain the allowable strain of the composite material, the pitch angle at the design point, and the minimum number of regional layups; an iterative optimization module, configured to use the optimization objective function set by the serialized regional fiber sub-model for the allowable strain, the pitch angle at the design point, and the minimum number of regional plies, and iteratively optimize the guide layer ply angle, guide layer coverage length, and regional sequence of the composite material according to the set number of algorithm population individuals and the number of iterations, until the iteration is completed and the optimal individual for ply optimization is output; The establishing of the serialized regional fiber sub-model of the composite propeller layup optimization model and performing optimization calculations in the serialized regional fiber sub-model include: Constructing a sequenced regional fiber sub-model, wherein the sequenced regional fiber sub-model is determined based on the GBBM guide layer parameters and in combination with the regional sequence, the guide layer layup angle, and the guide layer cover length factor; Selecting the guide layer laying angle, the guide layer coverage length, and the region sequence, determining the individual code corresponding to each angle, and determining the angle sequence corresponding to the guide layer laying angle according to the individual code; determining a guide layer coverage length corresponding to each angle, and paving regions of the region sequence according to the guide layer coverage length; The OX operator is used to perform sequence crossover in the plying region, select the split position from the two parents and inherit the intermediate gene of the first parent individual, rotate the second parent individual and fill in the non-repeated genes to obtain a new offspring individual.

8. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed on a processor, the processor is caused to execute the method according to any one of claims 1 to 6.

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