Wing lift augmentation and steerage enhancement device and method based on discrete jet flow

Abstract

The invention relates to a wing lift augmentation and steerage enhancement device and method based on discrete jet flow, and belongs to the technical field of active flow control of aircrafts. The wing lift augmentation and steerage enhancement device comprises an engine gas source guide pipeline and a jet flow exciter; an outlet of the engine gas source guide pipeline is communicated with an inlet of the jet exciter; a jet flow outlet and a blocking block are arranged at the outlet position of the jet exciter at intervals. According to the active flow control method based on discrete jet flow arrangement, different control effects are achieved, adjustable parameters include the jet flow intensity, the jet flow blocking ratio and the like, and the lift coefficient and the control surface efficiency can be improved by increasing the jet flow momentum coefficient; different optimal jet flow blocking ratios exist under different conditions, and the blocking ratio needs to be adjusted to an optimal value to optimize aerodynamic performance. Meanwhile, compared with steady jet control, the method is higher in efficiency and less in air source demand.

Description

Technical Field

[0001] The present invention relates to the technical field of active flow control for aircraft, and particularly to a device and method for wing lift augmentation and rudder effectiveness enhancement based on discrete jets. Further, it relates to a method for suppressing flow separation on the wing surface based on discrete jet active flow control to improve the lift-drag performance of the aircraft and the control effect of the control rudder surface. Background Art

[0002] An aircraft needs the cooperation of the wing and the rudder surface to achieve flight control. When the flight angle of attack is too large, the phenomenon of flow separation on the wing surface is likely to occur, resulting in an increase in the pressure on the upper surface of the wing, a decrease in the lift of the aircraft, an increase in drag, and a reduction in the flight efficiency of the aircraft. Traditional rudder surface control will also experience insufficient control or low efficiency due to flow separation, resulting in insufficient control or even out-of-control of the aircraft. Currently, there are two main ideas for solving this problem: passive flow control and active flow control. Passive flow control only changes the aerodynamic shape of the wing without introducing energy from the outside, and improves the aerodynamic performance by improving the aerodynamic layout distribution. This type of method is simple and mature, but lacks flexibility, cannot adjust the control effect according to the actual working conditions, and will generate additional drag during cruising, with a low cost-effectiveness. Active flow control can, without changing the aerodynamic shape, only apply control at local sensitive points in the flow field, change the global flow field pattern, and thus improve the aerodynamic performance of the wing, effectively solving the problems of insufficient lift or insufficient rudder effectiveness.

[0003] Existing practical flow control technologies are mainly passive flow control. For example, the vortex generators used on fighter planes apply disturbances to the flow by changing the aerodynamic shape, generating vortex lift on the upper surface of the wing to improve the flight performance at large angles of attack and thus suppress flow separation. However, vortex generators will reduce the flight efficiency during level flight, increase drag, and have a fixed control effect, unable to adapt to different flight conditions. Research on active control has been relatively mature, but its application on large aircraft is still relatively rare at present. The main application method is steady jet control, and steady jets have disadvantages such as low jet control efficiency and a large demand for external air sources. Since the air source often comes from the engine jet, a large air source demand will lead to a decrease in engine power. Summary of the Invention

[0004] To overcome the deficiencies of the prior art, the present invention proposes a wing lift augmentation and rudder efficiency enhancement device and method based on discrete jets. Considering the requirements for safe and stable flight in the complex flight environment of an aircraft, an active flow control method based on discrete jet arrangement is proposed to achieve different control effects under the comprehensive consideration of external environment, wing geometric parameters, control surfaces, etc. The adjustable parameters include jet intensity, jet blockage ratio, etc. Increasing the jet momentum coefficient can improve the lift coefficient and rudder efficiency; there are different optimal jet blockage ratios under different conditions, and the blockage ratio needs to be adjusted to the optimal value to optimize the aerodynamic performance. At the same time, the method of the present invention has higher control efficiency and less air source demand compared to steady jet control.

[0005] The present invention provides a wing lift augmentation and rudder efficiency enhancement device based on discrete jets, including an engine air source guiding pipeline 1 and a jet actuator 2; the outlet of the engine air source guiding pipeline 1 is connected to the inlet of the jet actuator 2; jet outlets 4 and blocks 3 are arranged at intervals at the outlet position of the jet actuator 2; The jet actuator 2 is connected to the wing, and the outlet position of the jet actuator 2 is set at the connection between the jet actuator 2 and the wing.

[0006] On the other hand, the present invention also provides a wing lift augmentation and rudder efficiency enhancement method based on discrete jets, which is used to augment the wing lift and enhance the rudder efficiency according to the wing lift augmentation and rudder efficiency enhancement device described in claim 1. The specific steps are as follows: Step 1: Collect various flight environments, and under the setting of the jet outlet 4 and the block 3, the engine air source guiding pipeline 1 guides the high-speed jet generated by the engine to the rear of the jet actuator 2 to generate a jet momentum coefficient and a jet blockage degree; Step 2: Conduct an aerodynamic simulation experiment based on the jet momentum coefficient and jet blockage degree in Step 1 to obtain the corresponding lift coefficient; use the jet momentum coefficient, jet blockage degree, and the corresponding lift coefficient as a data set; Step 3: Set the optimization constraints for the lift coefficient and the jet flow rate constraints; Step 4: Based on the training set obtained in Step 2 and the lift coefficient optimization constraints and jet flow rate constraints in Step 3, use the genetic algorithm to obtain the optimal control parameter model under the flight conditions; Step 5: Use the optimal control parameter model under the flight conditions to modulate the high-speed jet generated by the engine guided by the jet actuator into the required optimal jet momentum coefficient and optimal jet blockage degree.

[0007] Optionally, the optimization constraints for the lift coefficient are not higher than the aircraft stall threshold and not lower than the aircraft flight threshold.

[0008] Optionally, the jet flow rate is constrained such that the gas flow rate generated by the gas source system does not exceed the gas supply capacity of the engine or the air supply system.

[0009] Optionally, the specific steps of Step 4 are as follows: Step 41: Divide the data set of Step 2 into multiple data groups as the initial generation population. Each data group includes a set of individual input parameters and output parameters. Step 42: Based on the multiple data groups of the current generation population, use bicubic spline interpolation to obtain the predicted lift coefficient corresponding to each group of individual input parameters. Step 43: Based on the predicted lift coefficient in Step 42, obtain the lift coefficient fitness of the current generation population. Step 44: Based on the lift coefficient fitness of the current generation population, obtain the selection retention probability for each group of individual input parameters to be selected and retained. Step 45: Select appropriate individuals as parental individuals for reproduction according to the selection retention probability for each group of individual input parameters to be selected and retained. Step 46: Cross the individual input parameters of the parental individuals in the current generation population to obtain offspring individuals. Step 47: Add random perturbations to the offspring individuals for mutation operations to obtain mutated offspring individuals. Step 48: Use bicubic spline interpolation to obtain the fitness of the current generation of mutated offspring individuals.

[0010] Step 49: Find the offspring individual corresponding to the maximum lift coefficient among the fitnesses of the current generation of mutated offspring individuals, and compare it with the best lift coefficient obtained from the populations of the previous preset number of generations. When the maximum lift coefficient for consecutive threshold generations is less than or equal to the difference threshold, obtain the blockage ratio and jet momentum coefficient corresponding to the maximum lift coefficient; if the lift coefficient difference for consecutive threshold generations is greater than the difference threshold, put the individuals with higher fitness rankings among the current generation of mutated offspring individuals into the current generation population in Step 42, and return to Step 42.

[0011] Optionally, the specific steps of Step 4 are as follows: Put the individuals with the top 25% fitness rankings among the current generation of mutated offspring individuals into the current generation population in Step 42.

[0012] Optionally, each data group includes a blockage ratio, a jet momentum coefficient, and the corresponding lift coefficient obtained by simulation; the blockage ratio and the jet momentum coefficient are a set of individual input parameters of the population, and the corresponding lift coefficient obtained by simulation is the output parameter of the population.

[0013] Compared with the prior art, the present invention has at least the following beneficial effects: 1. The wing lift augmentation and rudder effectiveness enhancement device and method based on discrete jets of the present invention can delay flow separation by injecting energy into the fluid above the wing using jets, thereby improving the lift-to-drag ratio of the wing. At the same time, delaying separation can prevent control surfaces such as the wing and aileron from failing due to airflow separation, enhancing the controllability of the aircraft.

[0014] 2. The lift augmentation and rudder effectiveness enhancement achieved by the wing lift augmentation and rudder effectiveness enhancement device and method based on discrete jets of the present invention are obvious, and can significantly improve the flight performance of the aircraft.

[0015] 3. The wing lift augmentation and rudder effectiveness enhancement device and method based on discrete jets of the present invention can achieve different control effects by manipulating parameters such as jet intensity and blockage degree, improving the performance of the aircraft and adapting to different mission requirements.

[0016] 4. The wing lift augmentation and rudder effectiveness enhancement device and method based on discrete jets of the present invention can generate a larger lift coefficient compared to the cases of no jets and continuous jets. The control efficiency is effectively improved through discrete jets, making it a more promising control method. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flowchart of the wing lift augmentation and rudder effectiveness enhancement method based on discrete jets of the present invention; Figure 2 is a schematic diagram of the wing lift augmentation and rudder effectiveness enhancement device based on discrete jets of the present invention; Figure 3 (a)-(b) are schematic diagrams of the changes in aerodynamic characteristics after jets with different momentum coefficients are applied at different angles of attack in the embodiments of the present invention; Figure 4 is a schematic diagram of the jet actuator of the present invention; Figure 5 (a)-(e) are schematic diagrams of the changes in aerodynamic characteristics after jets with a momentum coefficient are applied with different blockage degrees of the plug in an embodiment of the present invention.

[0018] REFERENCE SIGNS: 1. Engine air source guiding pipeline; 2. Jet actuator; 3. Plug; 4. Jet outlet. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. In addition, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0020] A specific embodiment of the present invention, such as Figures 1-5 , discloses a wing lift augmentation and rudder effectiveness enhancement device based on discrete jets, including an engine air source guiding pipeline 1 and a jet actuator 2; the outlet of the engine air source guiding pipeline 1 is communicated with the inlet of the jet actuator 2; a jet outlet 4 and a plug 3 are arranged at intervals at the outlet position of the jet actuator 2.

[0021] Furthermore, the jet actuator 2 is connected to the wing, and the outlet position of the jet actuator 2 is arranged at the connection between the jet actuator 2 and the wing.

[0022] Furthermore, an optimal control parameter model under flight conditions is used to obtain the required optimal jet momentum coefficient and optimal jet blockage ratio; the jet outlet and the plug of the jet actuator are determined according to the optimal jet momentum coefficient and the optimal jet blockage ratio.

[0023] Furthermore, the jet momentum coefficient is expressed as:

[0024] wherein, is the mass flow rate at the jet outlet; is the jet velocity at the jet outlet; is the oncoming flow density; is the oncoming flow velocity; S represents the jet outlet area.

[0025] Furthermore, the jet blockage ratio is the ratio of the blocked area of the jet outlet to the total area of the jet outlet.

[0026] Another specific embodiment of the present invention also discloses a wing lift augmentation and rudder effectiveness enhancement method based on discrete jets, and the specific steps are as follows: Step 1, collect various flight environments, and under the conditions of the jet outlet 4 and the plug 3 being set, the air source guiding pipeline 1 guides the high-speed jet generated by the engine to the rear of the jet actuator 2 to generate a jet momentum coefficient and a jet blockage ratio; For a given jet blockage ratio, the density is usually used to represent the density of the jet nozzles.

[0027] Step 2, conduct an aerodynamic simulation experiment based on the jet momentum coefficient and the jet blockage ratio in Step 1 to obtain the corresponding lift coefficient; the jet momentum coefficient, the jet blockage ratio, and the corresponding lift coefficient are used as a data set.

[0028] Exemplarily, for a two-dimensional airfoil, the chord length of the airfoil is c, and different jet momentum coefficients will generate different lift coefficients, as Figure 3 shown.

[0029] Exemplarily, a schematic diagram of the positions of the jet outlets and the plugs on the wing is asFigure 4 As shown, the greater the blockage degree, the more obvious the lift enhancement effect, but the power consumption is also greater. At the same blockage degree, the more the number of jet outlets, that is, the denser the jet outlets, the better the aerodynamic performance improvement. Therefore, in engineering applications, it is necessary to select the blockage degree according to the power that the aircraft can provide, and on this basis, try to make the nozzle distribution dense. The lift improvement results for different blockage degrees are as Figure 5 shown.

[0030] Step 3: Set the lift coefficient optimization constraints and jet flow rate constraints.

[0031] Specifically, the optimization constraint condition of the lift coefficient is not higher than the aircraft stall threshold and not lower than the aircraft flight threshold.

[0032] Specifically, the jet flow rate constraint is that the gas flow generated by the gas source system does not exceed the gas supply capacity of the engine or the air supply system.

[0033] Step 4: Based on the training set obtained in Step 2 and the lift coefficient optimization constraints and jet flow rate constraints in Step 3, use the genetic algorithm to obtain the optimal control parameter model under flight conditions.

[0034] In order to obtain the best control parameters under flight conditions, it is necessary to measure the control effects of different parameters and use them as the data set required for optimization. The jet momentum coefficient and the jet blockage degree are used as optimization variables, and the lift coefficient is used as the optimization objective.

[0035] Specifically, the optimal control parameters under flight conditions include the optimal jet momentum coefficient and the optimal jet blockage degree. Divide the data set in Step 2 into multiple data groups, and each data group contains the blockage degree a, the jet momentum coefficient and the corresponding lift coefficient obtained by simulation under this parameter . The goal is to use the genetic algorithm to optimize the input parameters of the blockage degree a and the jet momentum coefficient so that the corresponding output lift coefficient reaches the maximum value.

[0036] The specific steps are as follows: Step 41: Obtain the initial generation population; Specifically, divide the data set in Step 2 into multiple data groups as the initial generation population. Each data group includes a set of individual input parameters and output parameters; each data group contains the blockage degree a, the jet momentum coefficient and the corresponding lift coefficient obtained by simulation ; the blockage degree a and the jet momentum coefficient are a set of individual input parameters of the population, and the corresponding lift coefficient obtained by simulation is the output parameter of the population. N is the population size, that is, the total number of data groups.

[0037] Step 42: Based on the multiple data groups in Step 41, use bicubic spline interpolation to obtain the predicted lift coefficient corresponding to each group of individual input parameters. , thereby generating a corresponding smooth lift coefficient surface within the combination space of each group of individual input parameters in each group of individual input parameters ( ), where represents the blockage degree of the i th group of the current generation population, represents the i th group of the current generation, and the jet momentum coefficient.

[0038] Further, use the interpolation library in Python to perform spline interpolation.

[0039] Step 43: Obtain the lift coefficient fitness of the current generation population, and the expression is:

[0040] where represents the blockage degree of the i th group of the previous generation population and the jet momentum coefficient of the i th group of the current generation, and the lift coefficient fitness under this condition; represents the blockage degree of the i th group of the previous generation population and the jet momentum coefficient of the i th group of the current generation, and the predicted lift coefficient obtained by bicubic spline interpolation under this condition.

[0041] Step 44: Based on the lift coefficient fitness of the current generation population, obtain the selection and retention probability of each group of individual input parameters being selected and retained, and the expression is:

[0042] where represents the selection and retention probability of the i th generation of individual input parameters being selected and retained; represents the lift coefficient fitness under the i th group of individual input parameters of the current generation population.

[0043] Step 45: Select appropriate individuals as parents for reproduction according to the selection and retention probability of each group of individual input parameters being selected and retained.

[0044] Specifically, rank them according to the selection and retention probability of each group of individual input parameters being selected and retained, and select the top 5 individuals as the parent individuals of the current generation population.

[0045] Step 46: Randomly cross the individual input parameters of the five parental individuals in the current generation population to obtain offspring individuals. Step 47: Add random perturbations to the offspring individuals for mutation operations to obtain mutated offspring individuals.

[0046] The mutation operation performed in the present invention increases the diversity of the population and prevents premature convergence. Mutation can be applied to the blockage ratio 𝑎 or the jet momentum coefficient For example, the mutation operation may change the 𝑎 value of the offspring from 1 / 3 to 1 / 3.5 or the jet momentum coefficient from 0.004 to 0.0042.

[0047] Step 48: Use bicubic spline interpolation to obtain the fitness of the mutated offspring individuals in the current generation.

[0048] Step 49: Find the offspring individual corresponding to the maximum lift coefficient among the fitnesses of the mutated offspring individuals in the current generation, and compare it with the best lift coefficient obtained from the population in the previous preset number of generations. When the difference between the maximum lift coefficients for consecutive threshold generations is less than 2%, the blockage ratio and jet momentum coefficient corresponding to the maximum lift coefficient are the optimal control parameters; if the difference between the lift coefficients for consecutive threshold generations is greater than 2%, the algorithm has not converged at this time. Put the individuals with higher fitness rankings among the mutated offspring individuals in the current generation into the current generation population in Step 42, and return to Step 42.

[0049] Preferably, put the individuals with the top 25% fitness rankings among the mutated offspring individuals in the current generation into the current generation population in Step 42.

[0050] Step 5: Use the optimal control parameter model under flight conditions to modulate the high-speed jet generated by the engine guided by the jet actuator into the required optimal jet momentum coefficient and optimal jet blockage ratio.

[0051] Furthermore, determine the jet outlet and the plug of the jet actuator according to the optimal jet momentum coefficient and optimal jet blockage ratio. After receiving the airflow from the engine air source guiding pipeline, it modulates it to have the required optimal jet momentum coefficient and optimal jet blockage ratio, and inputs the jet into the flow field.

[0052] Furthermore, determine the spatial layout position of the jet actuator, the geometric parameters of the jet outlet shape, and the volume of the actuator cavity according to the optimal jet momentum coefficient and optimal jet blockage ratio. They can be adaptively adjusted and optimized according to actual engineering requirements. The jet actuator can be arranged at different chordwise positions to adapt to the space inside the wing, avoiding the difficulty of installing the jet actuator due to the thin wing. Therefore, the present invention can be applied to aircraft with different airfoils, broadening the scope of engineering applications.

[0053] Through the optimal jet momentum coefficient and the optimal jet blockage ratio, the discrete jets of the present invention interact with the oncoming flow of the external flow field to control the flow field, which can increase the momentum of the airflow on the wing surface. According to Bernoulli's principle, the faster the flow velocity on the upper surface, the lower the pressure, and the greater the pressure difference between the upper and lower surfaces. Therefore, the discrete jets increase the pressure difference between the upper and lower surfaces and enhance the lift of the wing. Increasing the airflow momentum on the wing surface can also make the flow less likely to separate from the surface, and even maintain the flow attachment at high angles of attack, avoiding the failure of the wing due to flow separation at large angles of attack. Therefore, introducing discrete jets on the wing surface can also improve the rudder effectiveness of the wing.

[0054] The present invention uses the optimal jet momentum coefficient and the optimal jet blockage ratio model to drive the jet actuator, modulates the guided airflow into discrete jets corresponding to the optimal jet momentum coefficient and the optimal jet blockage ratio. The jets and the oncoming flow interact with each other to achieve the control of the flow field, and further achieve the purpose of increasing lift and enhancing rudder effectiveness. The discrete jet actuator used in this method has strong control ability, greatly improves the flight performance of the controlled wing, solves the problems of poor aerodynamic performance and low rudder effectiveness of the current aircraft at some aerodynamic points, and improves the flight quality of the aircraft.

[0055] Furthermore, in order to reduce the change of the original aerodynamic shape of the wing, the jet actuator is integrated with the wing. The parameters such as the arrangement position, number and spacing of the jet actuator in the flow direction and spanwise direction mentioned above can be determined by aerodynamic simulation experiments or flight test experiments according to actual needs, obtain the values of the lift coefficient under different parameters, and select the parameters when the lift coefficient is the largest, which can achieve the best regulation of the lift and moment of the wing.

[0056] To verify the method for increasing lift and enhancing rudder effectiveness of the wing by discrete jet active flow control proposed by the present invention, Fluent aerodynamic simulation verification was carried out.

[0057] See Figure 3 , Figure 3 (a) is the lift coefficient at a small angle of attack of 3°, Figure 3 (b) is the lift coefficient at a large angle of attack of 9°. CL is the lift coefficient. It can be seen from the figure that after applying the flow control based on discrete jets of the present invention, the lift and drag of the airfoil increase, and the lift-to-drag ratio is effectively improved under medium lift coefficients, having good lift-increasing and rudder-effectiveness-enhancing control capabilities; under the interaction of the jets and the oncoming flow, a low-pressure recirculation area is formed at the trailing edge of the wing, increasing the pressure difference between the upper and lower surfaces, increasing the upper surface velocity, moving the front stagnation point forward, deflecting the rear fluid downward, increasing the effective angle of attack and the wing circulation, enhancing the lift, and slowing down the airflow separation above the wing, thereby enhancing the rudder effectiveness. It can be considered that by applying jets, the airflow separation on the upper surface of the wing is slowed down, the lift of the aircraft is increased and the drag is reduced, and the flight performance of the aircraft is improved.

[0058] Figure 5 Schematic diagram of the change in aerodynamic characteristics after applying a jet with a momentum coefficient of 0.0075 to 10-mm plugs with different blockage degrees, where Figure 5 (a) Blockage ratio 1:10; Figure 5 (b) Blockage ratio 1:8; Figure 5 (c) Blockage ratio 1:6; Figure 5 (d) Blockage ratio 1:5; Figure 5 (e) Blockage ratio 1:3. It can be seen that as the blockage ratio increases continuously, the lift coefficient of the aircraft increases continuously. When the blockage ratio is relatively low, the jet control efficiency is insufficient. It can be seen that at this time, the aircraft is still affected by the periodic shedding of the airflow separation, and its lift fluctuates continuously; as the blockage ratio increases, the jet control efficiency increases, the lift coefficient increases significantly, and the fluctuation stops. Through experiments, the optimal parameters under different working conditions can be determined and applied to actual flight control. The results of the above two figures show that changing the synthetic jet momentum coefficient and the blockage degree can significantly change the aerodynamic performance of the wing. In practical applications, more groups of simulation experiments can be carried out, and the obtained results are used as the data set in step 2.

[0059] As described above, it is only the preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. An aircraft wing lift augmentation and rudder effectiveness enhancement device based on discrete jets, characterized in that, It includes an engine air source guiding pipeline and a jet actuator; the outlet of the engine air source guiding pipeline is communicated with the inlet of the jet actuator; at the outlet position of the jet actuator, a jet outlet and a plug are arranged at intervals; The jet actuator is connected to the wing, and the outlet position of the jet actuator is arranged at the connection between the jet actuator and the wing.

2. A method for enhancing wing lift and rudder effectiveness based on discrete jets, which is used to enhance wing lift and rudder effectiveness according to the wing lift and rudder effectiveness enhancement device described in claim 1, and is characterized in that, The specific steps are as follows: Step 1: Collect various flight environments, and when the jet outlet and the plug are set, the air source guiding pipeline guides the high-speed jet generated by the engine to the rear of the jet actuator to generate a jet momentum coefficient and a jet blockage degree; Step 2: Conduct an aerodynamic simulation experiment based on the jet momentum coefficient and the jet blockage degree in Step 1 to obtain the corresponding lift coefficient; the jet momentum coefficient, the jet blockage degree, and the corresponding lift coefficient are used as a data set; Step 3: Set the lift coefficient optimization constraint conditions and the jet flow rate constraint; Step 4: Based on the training set obtained in Step 2 and the lift coefficient optimization constraint conditions and the jet flow rate constraint in Step 3, use the genetic algorithm to obtain the optimal control parameter model under the flight condition; Step 5: Use the optimal control parameter model under the flight condition to modulate the high-speed jet generated by the engine guided by the jet actuator into the required optimal jet momentum coefficient and the optimal jet blockage degree.

3. The wing lift augmentation and rudder effect enhancement method according to claim 2, wherein The optimization constraint condition of the lift coefficient is not higher than the aircraft stall threshold and not lower than the aircraft flight threshold.

4. The wing lift augmentation and rudder effectiveness enhancement method according to claim 2, wherein The jet flow rate constraint is that the gas flow rate generated by the air source system does not exceed the gas supply capacity of the engine or the air supply system.

5. The wing lift augmentation and rudder effectiveness enhancement method according to claim 2, wherein The specific steps of Step 4 are: Step 41: Divide the data set in Step 2 into multiple data groups as the initial generation population, and each data group includes a set of individual input parameters and output parameters; Step 42: Based on the multiple data groups of the current generation population, use the bicubic spline interpolation method to obtain the predicted lift coefficient corresponding to each group of individual input parameters; Step 43: Based on the predicted lift coefficient in Step 42, obtain the lift coefficient fitness of the current generation population; Step 44: Based on the lift coefficient fitness of the current generation population, obtain the selection and retention probability of each group of individual input parameters being selected and retained; Step 45: Select appropriate individuals as parent individuals according to the selection and retention probability of each group of individual input parameters being selected and retained for reproduction; Step 46: Cross the individual input parameters of the parent individuals in the current generation population to obtain offspring individuals; Step 47: Add random perturbations to the offspring individuals for mutation operations to obtain mutant offspring individuals; Step 48: Use the bicubic spline interpolation method to obtain the fitness of the current generation mutant offspring individuals; Step 49: Find the offspring individual corresponding to the maximum lift coefficient among the fitness of the current generation mutant offspring individuals, and compare it with the best lift coefficient obtained from the preset generation population before. When the maximum lift coefficient of the continuous threshold generation is less than or equal to the difference threshold, obtain the blockage degree and the jet momentum coefficient corresponding to the maximum lift coefficient; If the lift coefficient difference of the continuous threshold generation is greater than the difference threshold, put the individuals with the top-ranked fitness of the current generation mutant offspring individuals into the current generation population in Step 42, and return to Step 42.

6. The wing lift augmentation and rudder effectiveness enhancement method according to claim 5, wherein The specific steps of Step 4 are as follows: Put the individuals in the top 25% of the fitness rankings of the current generation of mutated offspring individuals into the current generation population in Step 42.

7. The wing lift augmentation and rudder effectiveness enhancement method according to claim 5, wherein Each data set includes the blockage ratio, the jet momentum coefficient, and the corresponding lift coefficient obtained by simulation; The blockage ratio and the jet momentum coefficient are a set of individual input parameters of the population, and the corresponding lift coefficient obtained by simulation is the output parameter of the population.

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