Multidisciplinary optimization method, system, device, medium based on small camber airfoil

Abstract

The application belongs to the field of aircraft optimization technology and discloses a multi-disciplinary optimization method based on a small-radian airfoil, which comprises a pretreatment part of an airfoil and a grid, an airfoil parameterization and a dynamic grid part, an aerodynamic data evaluation part, a structure evaluation part, a stealth performance evaluation part, and an optimization part under multi-disciplinary constraints. The airfoil parameterization part is connected with spatial coordinate points by using an FFD parameterization method, realizes the change of the model surface grid by disturbing the design variables, and updates the spatial grid. The aerodynamic data evaluation part obtains and evaluates the aerodynamic data by using a flow field solver. The structure evaluation part evaluates the airfoil volume and thickness by using a script. The stealth performance evaluation part realizes the automatic evaluation of RCS by using electromagnetic software and a script. On the basis of aerodynamic, structural and stealth data, deformation and optimization are carried out, and then the optimal solution of the airfoil under multi-disciplinary constraints is obtained.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of aircraft optimization design, and particularly relates to a multi-disciplinary optimization method, system, device and medium based on a small-radian airfoil. BACKGROUND

[0002] Airfoil optimization design is the basis of aircraft optimization design, and the traditional high-cohesion serial design mode ignores the synergistic effect between subsystems, and cannot obtain overall optimal performance, and meanwhile, the design process takes a long time and has high economic cost. Current optimization design in the field is mainly for a single discipline and single evaluation. However, due to the mutual influence and coupling of aerodynamics, structure, stealth and other disciplines, if each factor is artificially separated, the design cost and development cycle will be unacceptable.

[0003] Therefore, the current optimization in the field of airfoils is limited to a single or two disciplines, and the problem of mutual coupling influence among multiple disciplines is ignored. SUMMARY

[0004] The application aims to provide a multi-disciplinary optimization method, system, device and medium based on a small-radian airfoil, which solves the problem that current aircraft optimization is limited to a single or two disciplines and ignores the mutual coupling influence among multiple disciplines.

[0005] The application is implemented by the following technical solutions:

[0006] A multi-disciplinary optimization method based on a small-radian airfoil comprises the following steps:

[0007] S1. Preprocessing is performed according to a current two-dimensional airfoil to obtain a model grid, and the model grid comprises an original surface grid and an original space grid;

[0008] The preprocessing is to scale the two-dimensional airfoil to a unit chord length, and to extend the two-dimensional airfoil by one unit length in the spanwise direction to change the two-dimensional airfoil into a three-dimensional airfoil;

[0009] S2. An FFD control frame is constructed according to the three-dimensional airfoil, five control points on the upper and lower surfaces of the airfoil are set as design variables, the variation range of the design variables is preliminarily given, the FFD method is used to parameterize the geometry of the original surface grid, and a parameterized surface grid is obtained;

[0010] S3. The design variables are randomly assigned, the parameterized surface grid is deformed, the original space grid is updated, an updated space grid is obtained, and the updated space grid and the parameterized deformed surface grid constitute an updated model grid;

[0011] S4. The updated model grid is given to a flow field solver to perform flow field calculation, flow field information is obtained, and aerodynamic data in the flow field information is evaluated;

[0012] The airfoil volume and thickness are calculated by scripts, and then the airfoil is structurally evaluated;

[0013] The radar cross section is automatically calculated by electromagnetic software and scripts, and then the airfoil is stealth performance evaluated;

[0014] S5. After evaluating the multi-disciplinary information, the calculation optimization is performed, the updated model grid is disturbed to form a new iteration estimation configuration, new round of aerodynamic data, structural data and stealth data are obtained and evaluated, and it is judged whether the optimization can be stopped;

[0015] If the iteration stopping condition is met, the optimization is stopped, and the corresponding optimization result is output;

[0016] If the condition is not met, return to S3 to generate new design variable values and re-deform the space grid.

[0017] Further, S1 is specifically:

[0018] S101. Take the length of the two-dimensional airfoil as the unit chord length, draw the grid with a preset thickness at the trailing edge part, and obtain the two-dimensional airfoil model grid;

[0019] S102. Stretch the two-dimensional airfoil model grid in the spanwise direction by 1m to form a three-dimensional grid, and then obtain the original surface grid and the original space grid.

[0020] Further, in S2, the FFD control body is established on the original surface grid, so that the surface grid is completely contained in the control body frame, and a plurality of FFD control points are defined along the edges of the control body. The control points here are design variables, and the upper and lower variation ranges of the preliminary design variables are 0.05m. The control frame and the surface grid are frozen to establish the mapping between the surface grid and the control frame, complete the parameterization of the surface grid, and obtain the parameterized surface grid.

[0021] Further, in S4, the updated model grid is given to the flow field solver to perform flow field calculation to obtain flow field information, which includes aerodynamic data. The aerodynamic data is evaluated, specifically including the following sub-steps:

[0022] S401. The updated model grid is given to the flow field solver to perform flow field calculation to obtain flow field information, wherein the aerodynamic data includes flow field pressure, temperature, friction, streamline, lift coefficient, drag coefficient and moment coefficient;

[0023] S402. Compare the lift coefficient, drag coefficient and moment coefficient in the aerodynamic data with the expected value, and the expected value is the objective function and the constraint function, which is defined as follows:

[0024] The specific form of the objective function is The specific form of the constraint function is

[0025] In the above formula: A and B are weight coefficients, C L is a lift coefficient, is a target lift coefficient value, C D is a drag coefficient, is a target drag value;

[0026] S403. Determine whether the value of the expected function is within the constraints, the constraint condition being: the value of the lift coefficient C L does not decrease or increase by 10%; or the value of the drag coefficient C D does not increase or decrease by 5%.

[0027] Further, in S4, the wing profile volume is calculated by a script, specifically including the following sub-steps:

[0028] S501. After solving the flow field, obtain the current model file in the flow field information and output it in stl format;

[0029] S502. Run the volume calculation script file based on MATLAB;

[0030] S503. The program obtains the path output by the current model file and parses the current model file content;

[0031] S504. When parsing the current model file, call the loop function to read the file line by line;

[0032] S505. After reading the current model file content, store the character type data on the pointer;

[0033] S506. Determine whether the vector in the character type data is a face normal vector;

[0034] S507. According to the judgment of S506, if it is a face normal vector, read the spatial coordinates of each face normal vector;

[0035] S508. Determine whether a point in the character type data is a vertex coordinate;

[0036] S509. According to the judgment of S508, read the spatial coordinates of the three vertices of each triangle;

[0037] S5010. Calculate and output the number of triangles in the current file according to the triangle vertex;

[0038] S5011. According to the triangle vertex coordinates, establish a tetrahedron for each triangle face in relation to the origin, determine whether the current volume normal vector points to the origin, if it points to the origin, the volume sign is positive, if it deviates from the origin, the volume sign is negative.

[0039] S5012. According to S5011, the number of tetrahedrons is obtained, and the Jacobian determinant is calculated to obtain the volume of all tetrahedrons;

[0040] S5013. The volume of the tetrahedron is calculated according to S5012, and the positive and negative of the volume of the tetrahedron is judged according to S5011. All tetrahedrons with volume symbols are traversed and summed up to obtain the volume of the model;

[0041] S5014. The volume of the model is evaluated to determine whether the current model volume is greater than or equal to the model volume obtained by initial calculation;

[0042] If the current model volume is larger than the model volume obtained by initial calculation, it means that the expectation is met;

[0043] If the current model volume is smaller than the model volume obtained by initial calculation, it means that the current model does not meet the requirements, and the calculation is restarted after returning to S3.

[0044] Further, in S4, the thickness of the airfoil is calculated by script, which includes the following sub-steps:

[0045] S601. After running the volume calculation script, start running the tecplot script;

[0046] S602. Slice the specified position of the current model file obtained by S501 to output the current cross-section information;

[0047] S603. Switch the current cross-section information to XYLine mode and save the current cross-section information as a file in dat format;

[0048] S604. After saving the cross-section information, start the script file for thickness processing based on python;

[0049] S605. Get the path output by the cross-section information file and read the cross-section information file content;

[0050] S606. When reading the cross-section information file, obtain the value from the specified row and store the data as a dataframe;

[0051] S607. Store the first column data of the dataframe form data into np array and force it to be float form;

[0052] S608. Take the specified interval of the float form array and output the corresponding z value in the dataframe. Judge the positive and negative of each value, average them respectively, then sum up the two averages and take the absolute value to output the current thickness value;

[0053] S609. The thickness of the model is evaluated to determine whether the thickness value at the specified position of the current model is greater than or equal to the thickness value at the same position of the model obtained by initial calculation;

[0054] If the thickness value at the specified position of the current model is increased compared to the thickness value at the specified position of the model obtained by initial calculation, it indicates that the requirement is met;

[0055] If the thickness value at the specified position of the current model is decreased compared to the thickness value at the specified position of the model obtained by initial calculation, it indicates that the current model does not meet the requirement, and the calculation is restarted after returning to S3.

[0056] Further, in the S4, the automatic calculation of the radar reflection cross section is realized by the electromagnetic software FEKO and the script, and then the stealth performance of the airfoil is evaluated, which specifically includes the following sub-steps:

[0057] S601. Start the FEKO script file and obtain the current model file path obtained in S501;

[0058] S602. Read the FEKO script file information and import the current model file;

[0059] S603. Set boundary conditions and calculation parameters;

[0060] S604. Define material properties, specify radiation power or source power;

[0061] S605. Set the frequency, define the polarization mode, and realize excitation by linearly polarized incident plane wave;

[0062] S606. Perform RCS calculation and output the corresponding out file, read the peak value of RCS in the out file and output;

[0063] S607. Evaluate the radar reflection cross section index, if the peak value of the current radar reflection cross section is decreased compared to the peak value of the radar reflection cross section obtained by initial calculation, it indicates that the requirement is met and the calculation can continue;

[0064] If the peak value of the current radar reflection cross section is increased compared to the peak value of the radar reflection cross section obtained by initial calculation, it indicates that the current model does not meet the requirement, and the calculation is restarted after returning to S3.

[0065] A multi-disciplinary optimization system based on a small-arc airfoil, comprising:

[0066] A mesh module for pre-processing according to the current two-dimensional airfoil to obtain a model mesh, the model mesh including an original surface mesh and an original space mesh;

[0067] The pre-processing is to scale the two-dimensional airfoil to a unit chord length, and to extend the two-dimensional airfoil by one unit length in the spanwise direction to convert the two-dimensional airfoil into a three-dimensional airfoil;

[0068] FFD control module, for constructing FFD control box according to three-dimensional airfoil, setting five control points on the upper and lower surfaces of the three-dimensional airfoil as design variables, initially giving the design variable variation range, completing the geometric parameterization of the original surface grid by the FFD method, and obtaining the parameterized surface grid;

[0069] Grid updating module, for randomly assigning design variables, deforming the parameterized surface grid, updating the original space grid, and obtaining the updated space grid, the updated space grid and the parameterized deformed surface grid forming the updated model grid;

[0070] Aerodynamic evaluation module, for submitting the updated model grid to a flow field solver for flow field calculation, obtaining flow field information, and evaluating aerodynamic data in the flow field information;

[0071] Structural evaluation module, for calculating the airfoil volume and thickness through a script, and then performing structural evaluation on the airfoil;

[0072] Stealth evaluation module, for realizing automatic calculation of radar reflection cross section through electromagnetic software and a script, and then performing stealth performance evaluation on the airfoil;

[0073] Multidisciplinary information comprehensive module, for calculating and optimizing after multidisciplinary information evaluation, perturbing the updated model grid to form a new iteration estimation configuration, obtaining new round of aerodynamic data, structural data and stealth data and evaluation, and judging whether to stop optimization;

[0074] If the iteration stop condition is met, the optimization stops, and the corresponding optimization result is output;

[0075] If the condition is not met, new design variable values are generated in the FFD control module, and the space grid is deformed again.

[0076] A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the multidisciplinary optimization method based on the small-radian airfoil when executing the computer program.

[0077] A computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by a processor to implement the steps of the multidisciplinary optimization method based on the small-radian airfoil.

[0078] Compared with the prior art, the present application has the following beneficial technical effects:

[0079] The application discloses a multidisciplinary optimization method based on a small-radian airfoil, which comprises a pretreatment part of the airfoil and a grid, an airfoil parameterization and a dynamic grid part, an airfoil aerodynamic data evaluation part, an airfoil structure evaluation part, an airfoil stealth performance evaluation part and an optimization part under multidisciplinary constraints. BRIEF DESCRIPTION OF DRAWINGS

[0080] Figure 1 It is a main step flow of the multidisciplinary optimization design method of the small-radian airfoil.

[0081] Figure 2 It is a grid chart and a corresponding control frame. Figure 2 a is a two-dimensional 0012 grid, Figure 2 b is a three-dimensional control frame.

[0082] Figure 3 It is a flow field pressure coefficient and a streamline distribution before and after airfoil optimization. Figure 3 a is a flow field pressure coefficient and a streamline distribution before airfoil optimization. Figure 3 b is a flow field pressure coefficient and a streamline distribution after airfoil optimization.

[0083] Figure 4 It is an airfoil surface pressure coefficient and an airfoil change comparison. Figure 4 a is an airfoil surface pressure coefficient comparison chart. Figure 4 b is an airfoil change comparison chart. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical scheme and advantages of the application clearer and more apparent, the following will be further described in detail in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application, that is, the described examples are only a part of the examples of the application, not all examples.

[0085] The components shown in the description and drawings of the application can be arranged and designed in a variety of different configurations, therefore, the detailed description of the embodiments of the application provided in the following drawings is not intended to limit the scope of the application claimed, but merely represents a selected embodiment of the application. Based on the drawings and embodiments of the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0086] It should be noted that the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, element, method, article or device including a list of elements does not only include those elements, but also includes other elements not explicitly listed, or inherent to such process, element, method, article or device.

[0087] As shown in Figure 1 The application discloses a multidisciplinary optimization method based on a small-arc airfoil, comprising the following steps:

[0088] S1. Preprocessing is performed according to the current two-dimensional airfoil to obtain a model grid, the model grid comprising an original surface grid and an original space grid;

[0089] The preprocessing is to scale the two-dimensional airfoil to a unit chord length, and to extend the two-dimensional airfoil to a three-dimensional airfoil by one unit length in the spanwise direction;

[0090] S2. An FFD control frame is constructed according to the three-dimensional airfoil, five control points on the upper and lower surfaces of the airfoil are set as design variables, the variation range of the design variables is preliminarily given, the geometric parameterization of the original surface grid is completed by using the FFD method, and a parameterized surface grid is obtained;

[0091] S3. The design variables are randomly assigned, the parameterized surface grid is deformed, the original space grid is updated, an updated space grid is obtained, and the updated space grid and the parameterized deformed surface grid constitute an updated model grid;

[0092] S4. The updated model grid is given to a flow field solver for flow field calculation, flow field information is obtained, and aerodynamic data in the flow field information is evaluated;

[0093] The volume and thickness of the airfoil are calculated through a script, and then the airfoil is structurally evaluated;

[0094] The radar reflection cross section is automatically calculated through electromagnetic software and a script, and then the airfoil is stealthily evaluated;

[0095] S5. After the multi-disciplinary information is evaluated, the calculation optimization is performed, the updated model grid is disturbed to form a new iteration estimation configuration, new round of aerodynamic data, structural data and stealth data are obtained and evaluated to determine whether the optimization can be stopped;

[0096] If the iteration stopping condition is met, the optimization is stopped, and the corresponding optimization result is output;

[0097] If the condition is not met, return to S3 to generate new design variable values and re-deform the space grid.

[0098] The features and performances of the present application are further described in detail in combination with the embodiments.

[0099] Taking the 0012 airfoil as an example, the processing steps are as follows:

[0100] In this example, in S1, the airfoil modeling and grid processing includes the following sub-steps:

[0101] S101. Take the length of the two-dimensional airfoil as the unit chord length (1m), and take a certain thickness (10mm to 20mm) at the trailing edge part to facilitate grid drawing.

[0102] Here, the trailing edge is taken as 10-20mm, which means that the tail of the airfoil is generally sharp, which is not convenient for drawing the grid, so the sharp tail is cut off, which will leave a certain thickness at the trailing edge.

[0103] S102. Generate a two-dimensional model grid as shown in Figure 2 a, stretch the two-dimensional model grid in the spanwise direction by 1m to form a three-dimensional grid, and obtain an original surface grid and an original space grid.

[0104] In this example, in S2, the FFD control body is established on the original surface grid, so that the surface grid is completely contained in the control body frame, and a plurality of FFD control points are defined along the edges of the control body. The control points here are design variables, and then the design variables are preliminarily given with an upper and lower variation range of 0.05m. The control frame and the surface grid are frozen to establish the mapping of the surface grid and the control frame, complete the parameterization of the surface grid, and obtain the parameterized surface grid, as shown in Figure 2 b.

[0105] In this example, in S4, the updated model grid is given to the flow field solver for flow field calculation to obtain flow field information, and the flow field information includes starting aerodynamic data. The aerodynamic data is evaluated, including the following sub-steps:

[0106] S401. Give the grid to the solver for flow field calculation to obtain flow field information, and the flow field information includes starting data, wherein the aerodynamic data includes flow field pressure, temperature, friction, streamline, lift coefficient, drag coefficient, moment coefficient, etc.

[0107] S402. Compare the lift coefficient and the drag coefficient in the aerodynamic data with the expected values, divide them into objective functions and constraint functions, and determine whether the current constraint conditions are met, the constraint conditions being: the value of the lift coefficient C L does not decrease or increase by 10%; or the value of the drag coefficient C D does not increase or decrease by 5%.

[0108] The specific form of the objective function is The specific form of the constraint function is In the formula, A and B are weight coefficients, C L is the lift coefficient, is the target lift coefficient value, C D is the drag coefficient, is the target drag value.

[0109] In this example, in S4, the airfoil volume and thickness are calculated by a script, and then the airfoil structure is evaluated, including the following sub-steps:

[0110] S501. After solving the flow field, obtain the current model file in the flow field information and output it in stl format, and the output command is export mesh_as_new.stl;

[0111] S502. Run the volume calculation script file based on MATLAB;

[0112] S503. The program obtains the path output by the current model file and parses the current model file content;

[0113] S504. When parsing the current model file, call the loop function to read the file line by line;

[0114] S505. After reading the content of the current model file, store the character type data on the pointer;

[0115] S506. Determine whether the vector in the character type data is a face normal vector;

[0116] S507. If it is a normal vector, read the spatial coordinates of each face normal vector;

[0117] S508. Determine whether a point in the character type data is a vertex coordinate;

[0118] S509. According to the judgment of S508, read the spatial coordinates of the three vertices of each triangle;

[0119] S5010. Calculate and output the number of triangles in the current file according to the triangle vertexes;

[0120] S5011. According to the coordinates of the triangle vertices, establish a tetrahedron for each triangular face in relation to the origin, determine whether the current volume vector points to the origin, if it points to the origin, the volume sign is defined as positive, if it deviates from the origin, the volume sign is defined as negative;

[0121] S5012. According to S5011, the number of tetrahedrons is obtained, and the Jacobian determinant is calculated to calculate the volume of all tetrahedrons;

[0122] S5013. According to S5012, the volume of the tetrahedron is calculated, combined with the positive and negative judgment of the volume of the tetrahedron in S5011, all tetrahedrons with volume signs are traversed and summed up to obtain the volume of the model;

[0123] S5014. Start running the tecplot script tec360-b-p new.mcr;

[0124] S5015. Slice the specified position of the model, and output the current cross-section information;

[0125] S5016. Switch to XYLine mode and save the current file information as a dat format;

[0126] S5017. Start the thickness processing file based on python;

[0127] S5018. Get the path output by the thickness processing file and read the file content;

[0128] S5019. Get the numerical value from the specified row and store the data as a dataframe;

[0129] S5020. Store the first column data in the np array and force it to be float;

[0130] S5021. Take the x value in the specified interval and output the corresponding z value, judge the positive and negative of each value, average them respectively, then sum the two averages and take the absolute value, output the current thickness value; S5015. Slice the specified position of the current model file obtained by S501, and output the current cross-section information;

[0131] S5016. Switch the current cross-section information to XYLine mode and save the current cross-section information as a dat format file;

[0132] S5017. After saving the cross-section information, start the script file based on python thickness processing;

[0133] S5018. Get the path output by the cross-section information file and read the cross-section information file content;

[0134] S5019. When reading the cross-section information file, obtain the numerical value from the specified row and store the data in the form of a dataframe;

[0135] S5020. Store the first column data of the dataframe-form data in an np array and force it to be in float form;

[0136] S5021. Take the specified interval of the float-form array and output the corresponding z value in the dataframe, determine the positive and negative of each numerical value, average them respectively, then sum the two averages and take the absolute value to output the current thickness value;

[0137] S5022. Evaluate the volume of the model obtained in S5013 and the thickness obtained in S5021 respectively, divide them into objective functions and constraint functions, and define them in the same way as the objective and constraint functions in the aerodynamic data evaluation, determine whether their values are within the constraint interval, if not, return to S3 and recalculate.

[0138] In this example, in S6, the automatic calculation of the radar cross section (RCS) is realized through electromagnetic software and scripts, and then the stealth performance of the airfoil is evaluated, which specifically includes the following sub-steps:

[0139] S601. Start the FEKO script file and obtain the current model file path obtained in S501;

[0140] S602. Read the FEKO script file information, import the current model file, and convert the format to cfm format;

[0141] S603. Set boundary conditions and calculation parameters;

[0142] S604. Define material properties, specify radiation power or source power;

[0143] S605. Set the frequency, define the polarization method, and realize excitation by linearly polarized incident plane waves;

[0144] S606. Perform RCS calculation and output the corresponding out file, read the RCS peak value in the out file and output;

[0145] S607. Evaluate the RCS index, divide it into objective functions and constraint functions, and define them in the same way as the objective and constraint functions in the aerodynamic data evaluation, determine whether their values are within the constraint interval, if not, return to S3 and recalculate.

[0146] In this example, in S7, after the multi-disciplinary information is evaluated, the calculation optimization is performed, the updated model grid is disturbed, a new iteration estimation configuration is formed, new round of aerodynamic, structural, and stealth data are obtained, and the optimization is judged whether to stop; if the iteration stop condition is met, the optimization stops, and the corresponding optimization result is output; if the condition is not met, return to S3, generate new design variable values, deform the space grid again, including the following sub-steps:

[0147] S701. The aerodynamic, structural, and stealth data of the current flow field are integrated and written into an output file as the basis value of the optimization process.

[0148] S702. Based on the current multi-disciplinary information, the optimization calculation is performed, the updated model grid is disturbed, a new iteration estimation configuration is formed, new round of aerodynamic, structural, and stealth data are obtained, and the optimization is judged whether to stop; if the iteration stop condition is met, the optimization stops, and the corresponding optimization result is output; if the condition is not met, return to S3, generate new design variable values, deform the space grid again.

[0149] A multi-disciplinary optimization verification is performed on the 0012 airfoil under low Mach number incoming flow. The optimization state is: Ma=0.265, AOA=3°; the lift coefficient is improved, and the drag coefficient is reduced as the target; the volume and RCS index are used as the constraint; there are 18 groups of control variables on the upper and lower airfoils, the chord length is 1m and remains unchanged, each group contains two control points and is disturbed vertically to the airfoil surface.

[0150] As shown in Table 1, the lift-drag ratio is increased from 25.05 to 38.97, an increase of 55.56%; according to Figure 3 a and Figure 3 b comparison before and after optimization, the pressure coefficient distribution of the flow field also changes, the stagnation point of the leading edge moves up, the low-pressure area of the upper surface and the high-pressure area of the lower surface increase and strengthen, and the same is true for the trailing edge; according to Figure 4 a airfoil surface pressure coefficient distribution, the area surrounded by the pressure curve after optimization increases significantly, and the pressure difference increases, which means that the airfoil can provide higher lift under the same incoming flow state. After optimization, the airfoil has changed greatly as Figure 4 b: the leading edge of the airfoil is deformed downward, the lower surface near the trailing edge has a reverse concave, the trailing edge is thin and slightly upturned. Table 1 shows the changes of the target functions and constraint functions, according to the results, the RCS index is reduced while the lift-drag ratio is improved, which may be mainly due to the influence of the change of the leading edge, but the volume is relatively reduced, the windward area is also reduced, and thus the drag is reduced, thereby improving the lift-drag ratio.

[0151] Table 1 Changes of target functions and constraint functions of 0012 test case

[0152]

[0153] The application also discloses a multi-disciplinary optimization system based on a small-radian airfoil, comprising:

[0154] a grid module, which is used for preprocessing according to a current two-dimensional airfoil to obtain a model grid, the model grid comprising an original surface grid and an original space grid;

[0155] The preprocessing is to scale the two-dimensional airfoil to a unit chord length and expand the two-dimensional airfoil to a three-dimensional airfoil by one unit length in the spanwise direction;

[0156] an FFD control module, which is used for constructing an FFD control frame according to the three-dimensional airfoil, setting five control points on upper and lower surfaces of the three-dimensional airfoil as design variables, and initially giving a variation range of the design variables, so as to complete geometric parameterization of the original surface grid by the FFD method and obtain a parameterized surface grid;

[0157] a grid updating module, which is used for randomly assigning values to the design variables, deforming the parameterized surface grid, updating the original space grid, and obtaining an updated space grid, so as to form an updated model grid comprising the updated space grid and the parameterized deformed surface grid;

[0158] an aerodynamic evaluation module, which is used for submitting the updated model grid to a flow field solver to perform flow field calculation, obtaining flow field information, and evaluating aerodynamic data in the flow field information;

[0159] a structure evaluation module, which is used for calculating a wing profile volume and thickness through a script, and then performing structure evaluation on the wing profile;

[0160] a stealth evaluation module, which is used for realizing automatic calculation of a radar reflection cross section through electromagnetic software and a script, and then performing stealth performance evaluation on the wing profile;

[0161] a multi-disciplinary information comprehensive module, which is used for calculating and optimizing after multi-disciplinary information evaluation, perturbing the updated model grid to form a new iteration estimation configuration, obtaining new aerodynamic data, structure data and stealth data and performing evaluation, and judging whether optimization can be stopped;

[0162] If the iteration stopping condition is met, the optimization is stopped, and corresponding optimization results are output;

[0163] If the condition is not met, new design variable values are generated in the FFD control module, and the space grid is deformed again.

[0164] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to realize the steps of the multi-disciplinary optimization method based on the small radian airfoil.

[0165] Those skilled in the art will further appreciate that the functions of the examples described herein-based units and algorithm steps can be implemented using electronic hardware, computer software, or any combination thereof. To clearly illustrate this interchangeability of hardware and software, various examples have been described herein in terms of their functional generalities. Whether such functions are implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0166] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in random access memory (RAM), memory, flash memory, read-only memory (ROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0167] Finally, it should be noted that the above-described embodiments are merely intended for describing the technical solutions of the present application, but not to limit the technical solutions of the present application. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific implementation of the present application can be modified or replaced, and any modification or replacement without departing from the spirit and scope of the present application should be covered within the protection scope of the claims of the present application.

Claims

1. A multidisciplinary optimization method based on small-radius airfoils, characterized in that, Includes the following steps: S1. Perform preprocessing based on the current two-dimensional airfoil to obtain the model mesh, which includes the original surface mesh and the original spatial mesh; The preprocessing involves scaling the two-dimensional airfoil to a unit chord length and extending it by one unit length in the spanwise direction, thus transforming the two-dimensional airfoil into a three-dimensional airfoil. S2. Construct an FFD control frame based on the three-dimensional airfoil, take five control points on each of the upper and lower surfaces of the airfoil as design variables, initially give the range of variation of the design variables, complete the geometric parameterization of the original surface mesh by the FFD method, and obtain the parameterized surface mesh. S3. Randomly assign values ​​to the design variables, deform the parameterized surface mesh, update the original spatial mesh, and obtain the updated spatial mesh. The updated spatial mesh and the parameterized deformed surface mesh constitute the updated model mesh. S4. The updated model mesh is handed over to the flow field solver for flow field calculation to obtain flow field information, and the aerodynamic data in the flow field information is evaluated; The airfoil volume and thickness are calculated using a script, and then the airfoil structure is evaluated. The radar cross section is automatically calculated using electromagnetic software and scripts, and then the stealth performance of the airfoil is evaluated. S5. After evaluating the multidisciplinary information, perform computational optimization, perturb the updated model mesh to form a new iterative prediction configuration, obtain a new round of aerodynamic data, structural data, and stealth data, and evaluate them to determine whether optimization can be stopped. If the iteration stopping condition is met, the optimization stops and the corresponding optimization result is output. If the conditions are not met, return to S3, generate new design variable values, and reshape the spatial mesh.

2. The multidisciplinary optimization method based on small-radius airfoils according to claim 1, characterized in that, S1 specifically refers to: S101. Take the length of the two-dimensional airfoil as the unit chord length, and draw a mesh with a preset thickness for the trailing edge part to obtain the two-dimensional airfoil model mesh; S102. Stretching the spanwise mesh by 1m on the basis of the two-dimensional airfoil model mesh to form a three-dimensional mesh, thus obtaining the original surface mesh and the original spatial mesh.

3. The multidisciplinary optimization method based on small-radius airfoils according to claim 1, characterized in that, In step S2, an FFD control volume is established on the original surface mesh, so that the surface mesh is completely contained within the control volume frame. Several FFD control points are defined along each side of the control volume. These control points are the design variables. The initial range of the design variables is 0.05m. The control frame and the surface mesh are frozen to establish the mapping between the surface mesh and the control frame, thus completing the parameterization of the surface mesh and obtaining the parameterized surface mesh.

4. The multidisciplinary optimization method based on small-radius airfoils according to claim 1, characterized in that, In step S4, the updated model mesh is handed over to the flow field solver for flow field calculation to obtain flow field information, which includes aerodynamic data. The aerodynamic data is evaluated, specifically including the following sub-steps: S401. The updated model mesh is handed over to the flow field solver for flow field calculation to obtain flow field information, including aerodynamic data such as flow field pressure, temperature, friction, streamlines, lift coefficient, drag coefficient and torque coefficient. S402. Compare the lift coefficient, drag coefficient, and moment coefficient in the aerodynamic data with the desired values, which are defined by the objective function and constraint function as follows: The specific form of the objective function is as follows: The specific form of the constraint function is as follows: In the above formula: A and B are weighting coefficients, C L The lift coefficient, For the target lift coefficient value, C D The drag coefficient, The target resistance value; S403. Determine whether the value of the expected function is within the constraints, the constraints being: lift coefficient C. L The value does not decrease or increase by 10%; or the drag coefficient C D The value does not increase or decrease by 5%.

5. The multidisciplinary optimization method based on small-radius airfoils according to claim 1, characterized in that, In S4, the airfoil volume is calculated using a script, specifically including the following sub-steps: S501. After solving the flow field, obtain the current model file from the flow field information and output it in STL format; S502. Run the MATLAB-based volume calculation script file; S503. The program obtains the output path of the current model file and parses the contents of the current model file; S504. When parsing the current model file, a loop function is called to read the file line by line; S505. After reading the contents of the current model file, store the character data in the pointer; S506. Determine whether a vector in character data is a surface normal vector; S507. Based on S506, if it is a surface normal vector, then read the spatial coordinates of each surface normal vector; S508. Determine whether a point in a character data type is a vertex coordinate; S509. Based on the judgment in S508, read the spatial coordinates of the three vertices of each triangle; S5010. Calculate and output the number of triangles in the current file based on the triangle vertices; S5011. Based on the coordinates of the triangle vertices, establish a tetrahedron by connecting each triangle face to the origin. Determine whether the current volume normal vector points to the origin. If it points to the origin, the volume sign is defined as positive; if it deviates from the origin, the volume sign is defined as negative. S5012. Based on S5011, obtain the number of tetrahedrons, and calculate the volume of all tetrahedrons using the Jacobian determinant; S5013. Calculate the volume of the tetrahedron according to S5012, and combine it with the positive and negative judgment of the tetrahedron volume in S5011. Iterate through all tetrahedrons with volume signs and sum them to obtain the volume of the model. S5014. Evaluate the volume of the model and determine whether the current model volume is greater than or equal to the model volume value obtained in the initial calculation; If the current model volume is larger than the model volume obtained in the initial calculation, it means that the expectation is met; If the current model volume is smaller than the model volume obtained in the initial calculation, it means that the current model does not meet the requirements, and the calculation is repeated after returning to S3.

6. The multidisciplinary optimization method based on a small-radius airfoil according to claim 5, characterized in that, In S4, the airfoil thickness is calculated using a script, specifically including the following sub-steps: S601. After the volume calculation script finishes running, start the tecplot script; S602. Slice the current model file obtained in S501 at a specified location and output the current section information; S603. Switch the current section information to XYLine mode and save the current section information as a dat format file; S604. After saving the cross-sectional information, start the Python-based thickness processing script file; S605. Obtain the output path of the cross-section information file and read the contents of the cross-section information file; S606. When reading the cross-section information file, obtain the value from the specified line and store the data in the form of a dataframe; S607. Store the first column of the data in the dataframe format into the np array and force it to be in float format; S608. Take a specified range from a float array and output the corresponding z value in the dataframe. Determine the sign of each value, average them, sum the two averages, take the absolute value, and output the current thickness value. S609. Evaluate the thickness of the model and determine whether the thickness value at the specified location of the current model is greater than or equal to the thickness value at the same location of the model obtained in the initial calculation; If the thickness value at the specified location in the current model is larger than the thickness value at the specified location obtained in the initial calculation, it means that the expectation is met; If the thickness value at the specified location of the current model is smaller than the thickness value at the specified location of the model obtained in the initial calculation, it means that the current model does not meet the requirements, and the calculation is repeated after returning to S3.

7. The multidisciplinary optimization method based on a small-radius airfoil according to claim 5, characterized in that, In step S4, the radar cross section is automatically calculated using the electromagnetic software FEKO and scripts, and then the stealth performance of the airfoil is evaluated. This specifically includes the following sub-steps: S601. Start the FEKO script file and obtain the current model file path obtained in S501; S602. Read FEKO script file information and import the current model file; S603. Set boundary conditions and calculation parameters; S604. Define material properties, specifying radiated power or source power; S605. Set the frequency, define the polarization mode, and achieve excitation through linearly polarized incident plane waves; S606. Perform RCS calculation and output the corresponding out file, read the peak value of RCS in the out file and output it; S607. Evaluate the radar cross-section index. If the current peak value of the radar cross-section is smaller than the peak value of the radar cross-section obtained in the initial calculation, it means that the expectation is met and the calculation can continue. If the current peak value of the radar cross section is larger than the peak value of the radar cross section obtained in the initial calculation, it means that the current model does not meet the requirements, and the calculation is repeated after returning to S3.

8. A multidisciplinary optimization system based on small-radius airfoils, characterized in that, include: The mesh module is used to perform preprocessing based on the current two-dimensional airfoil to obtain the model mesh, which includes the original surface mesh and the original spatial mesh. The preprocessing involves scaling the two-dimensional airfoil to a unit chord length and extending it by one unit length in the spanwise direction, thus transforming the two-dimensional airfoil into a three-dimensional airfoil. The FFD control module is used to construct the FFD control frame based on the three-dimensional airfoil. Five control points on each of the upper and lower surfaces of the three-dimensional airfoil are set as design variables. The variation range of the design variables is initially given, and the geometric parameterization of the original surface mesh is completed by the FFD method to obtain the parameterized surface mesh. The mesh update module is used to randomly assign values ​​to design variables, deform the parameterized surface mesh, update the original spatial mesh, and obtain the updated spatial mesh. The updated spatial mesh and the parameterized deformed surface mesh constitute the updated model mesh. The aerodynamic evaluation module is used to pass the updated model mesh to the flow field solver for flow field calculation, obtain flow field information, and evaluate the aerodynamic data in the flow field information. The structural evaluation module is used to calculate the airfoil volume and thickness using scripts, and then perform a structural evaluation of the airfoil. The stealth assessment module is used to automatically calculate the radar cross section through electromagnetic software and scripts, and then evaluate the stealth performance of the airfoil. The multidisciplinary information integration module is used to evaluate multidisciplinary information, perform computational optimization, perturb the updated model grid, form a new iterative prediction configuration, obtain a new round of aerodynamic data, structural data, and stealth data, evaluate them, and determine whether optimization can be stopped. If the iteration stopping condition is met, the optimization stops and the corresponding optimization result is output. If the conditions are not met, new design variable values ​​are generated in the FFD control module, and the spatial mesh is re-deformed.

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, When the processor executes the computer program, it implements the steps of the multidisciplinary optimization method based on small-radian airfoils as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the multidisciplinary optimization method based on small-radian airfoils as described in any one of claims 1 to 7.

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