Curved surface slope flow separation control device based on intelligent combined blowing

Abstract

The invention provides a curved slope flow separation control device based on intelligent combined blowing, and relates to the technical field of active control of fluid mechanics, and the curved slope flow separation control device comprises a plurality of tangential blowing slits which are formed in a curved slope and are distributed along the flow direction; the pressure measuring unit is arranged on the surface of the curved slope and a downstream area thereof and is used for collecting flow field pressure data; the gas path supply and control unit is connected with the plurality of tangential blowing slits and is used for providing independent and controllable pulse blowing for each slit; and the intelligent control unit is in signal connection with the pressure measurement unit and the gas path supply and control unit, and is configured to perform iterative calculation through a built-in optimization algorithm based on the pressure data acquired by the pressure measurement unit, and perform automatic optimization to obtain a group of optimal control parameter combinations for controlling the gas path supply and control unit. According to the invention, the best effect of controlling the flow separation of the curved slope can be achieved, and compared with the traditional technology, the control efficiency is higher and the input energy is smaller.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of fluid mechanics active control, and particularly relates to a curved ramp flow separation control device based on intelligent combined blowing. BACKGROUND

[0002] Currently, when fluid flows through a curved ramp, flow separation will occur due to the influence of adverse pressure gradient, which is a common physical phenomenon in industry. For example, when the angle of attack of an aircraft flying in the atmosphere increases, flow separation will occur on the wing. When a submarine or other underwater vehicle is moving in the ocean, flow separation will also occur at the tail. Flow separation leads to a sudden decrease in pressure in the separation zone, which in turn causes a sudden increase in noise and drag, directly affecting the safety, energy consumption, and comfort of aircraft, submarines, and other vehicles. By using flow control technology to suppress or even eliminate flow separation, some problems encountered in engineering can be effectively solved. Therefore, the development of flow control technology has always been the focus of attention of academia and industry. Flow control technology can be divided into passive control and active control according to whether energy is input. As an active control method, slot blowing has the property of being able to control the main flow characteristics, which can more effectively control flow separation. He et al.

He S, Zhang K, Song Y, et al. Control of flow separation from a curved ramp using a steady-blowing jet [J]. Physics of Fluids, 2023, 35(4).

[0003] Existing flow separation control technologies are mostly focused on passive control, such as vortex generators for aircraft engines, automobile spoilers, wind turbine blade tip wings, etc. However, they have the shortcomings of being unable to adjust the control strategy autonomously according to the incoming flow conditions and having unsatisfactory aerodynamic performance in some working conditions. Active control requires additional input energy to generate disturbances in the flow field, but has the advantages of flexible adjustment and strong disturbance intensity. For example, Dandois et al.

Dandois, J., Garnier, E., & Sagaut, P. (2007). Numerical simulation of active separation control by a synthetic jet. Journal of Fluid Mechanics, 574, 25-58. doi: 10.1017 / s0022112006003995

[0004] However, both of the above methods have the problem of high energy consumption. To solve this problem, for the phenomenon of curved ramp flow separation, the present application provides an intelligent combined blowing control device. The device uses multi-slit pulse blowing jet, analyzes the pressure data collected from the flow field, and uses intelligent algorithms to autonomously find the optimal combination of control parameters according to the incoming flow characteristics. At the same time, by reasonably distributing the input energy to each slit, the purpose of effectively controlling the curved ramp flow separation and saving input energy is achieved. SUMMARY

[0005] The present application aims to provide a curved ramp flow separation control device based on intelligent combined blowing to solve the problems pointed out in the background art.

[0006] The curved ramp flow separation control device based on intelligent combined blowing provided by the embodiments of the present application comprises: A plurality of tangential blowing slits are provided on the curved ramp and are distributed along the flow direction. A pressure measurement unit is arranged on the surface of the curved ramp and the downstream area thereof, and is used to collect flow field pressure data. The air path supply and control unit is connected with the plurality of tangential blowing slits and is configured to provide independent controllable pulse blowing to each slit. The intelligent control unit is connected with the pressure measurement unit and the air path supply and control unit, and is configured to: based on the pressure data collected by the pressure measurement unit, perform iterative calculation through an embedded optimization algorithm, and automatically obtain a set of optimal control parameter combinations for controlling the air path supply and control unit to achieve low energy consumption to suppress flow separation.

[0007] Optionally, the plurality of tangential blowing slits are three, and the outlets thereof are located at the streamwise positions of 0.95h, 1.50h and 1.95h from the starting point of the curved slope, where h is the height of the curved slope.

[0008] Optionally, the air path supply and control unit comprises: an air source; a pressure regulating device connected with the air source and configured to accurately regulate the pressure of the output air flow; a high-speed on-off valve connected with the pressure regulating device and configured to modulate the continuous air flow into pulse jets according to the received control signal; wherein the control ends of the pressure regulating device and the high-speed on-off valve are connected with the intelligent control unit.

[0009] Optionally, the optimal control parameter combination comprises a blowing pressure parameter and a blowing duty cycle parameter corresponding to each tangential blowing slit, and a blowing frequency parameter and a phase difference parameter between the blowing pulse signals of each slit commonly used by all the slits.

[0010] Optionally, the optimization algorithm is a genetic algorithm, and the optimization process thereof comprises the following steps: Step 1, initialization: randomly generating an initial population comprising a plurality of individuals, each individual representing a set of control parameter combinations; Step 2, preliminary evaluation: sending the control parameters corresponding to each individual in the population to the air path supply and control unit for execution, and after the flow field is stable, collecting pressure data through the pressure measurement unit and calculating the cost function value corresponding to each individual; Step 3, preliminary judgment: if the cost function value of the best individual meets the preset convergence condition, the optimization is stopped and the current best individual is output as the optimal control parameter combination; otherwise, step 4 is executed; Step 4, preliminary evolution: based on the cost function values of the individuals in the current population, a new generation population is generated through selection, crossover and mutation operations, and step 2 is returned.

[0011] Optionally, the cost function J is a weighted sum of a first term J1 representing the flow separation suppression effect and a second term J2 representing the input energy consumption, and its expression is: J = J 1+α J 2, where α is an adjustable weighting coefficient used to adjust the optimization objective to focus on separation suppression or energy saving.

[0012] Optionally, the first term J1 is defined as the measured pressure coefficient C at the end of the curved slope. p，end With ideal pressure coefficient C p，end(ref) The absolute value of the difference between the current input energy E and the reference input energy E; the second term J2 is defined as the difference between the current input energy E and the reference input energy E. ref The ratio of .

[0013] Optionally, the input energy E is calculated as follows: , among which, U jet1 U jet2 U jet3 The value represents the tangential slit outlet velocity at flow-direction locations on the slope at distances of 0.95h, 1.50h, and 1.95h from the slope initiation point, U. ∞ The value represents the incoming air velocity, T is the time period, and ∫dt is the integral over time.

[0014] Optionally, the optimization algorithm can be replaced with a Bayesian optimization algorithm or an ant colony optimization algorithm.

[0015] Optionally, the curved ramp and the multiple tangential air-blowing slits formed thereon are integrally molded structures.

[0016] The present invention has achieved the following beneficial effects: Unlike traditional single-slit blowing control, this invention employs three slits for coordinated blowing. By controlling the blowing of each of the three slits individually, optimal flow separation on the curved slope can be achieved. This invention designs an intelligent blowing system capable of autonomously controlling excitation, acquiring data, and optimizing parameters. Through iterative genetic algorithms, the blowing input parameters for each of the three slits are obtained, and the optimal solution for input energy and control effect is calculated, achieving higher control efficiency and lower input energy compared to traditional techniques. The intelligent blowing system designed in this invention has wide applicability; by modifying parameters such as the cost function within the intelligent blowing system, ideal control laws can be optimized to meet different needs.

[0017] Existing techniques for controlling surface flow separation are limited to controlling a single air-blowing slit. While these techniques offer good control, they cannot further optimize energy consumption. This invention utilizes a combination of three slits for air blowing, employing a genetic algorithm to optimize the corresponding control parameters. By comparing the control performance with that under ideal conditions using a single slit, the optimized control parameters obtained by this system can save at least 70% of the input energy while maintaining the same control effect. Furthermore, using a genetic algorithm for parameter optimization significantly reduces manpower and avoids tedious, repetitive experiments.

[0018] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0019] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the overall curved slope experimental device of the present invention; Figure 2 This is a schematic diagram of the outlet position of the tangential blowing slit of the present invention on the curved slope; Figure 3 This is a cross-sectional view of the internal design of the tangential air-blowing slit exciter of the present invention; Figure 4 This is a schematic diagram of the exciter air circuit system and intelligent control principle of the present invention; Figure 5 This is a comparison chart of energy consumption and pressure coefficient recovery between the unsteady blowing control obtained by the genetic algorithm optimization of this invention and the reference condition (single slit steady blowing); Figure 6 These are time-averaged flow field diagrams of curved slope flow under different control conditions. Detailed Implementation

[0021] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0022] This application provides a curved slope flow separation control device based on intelligent combined air blowing, the device comprising: Multiple tangential air-blowing slits are opened on the curved slope and distributed along the flow direction; A pressure measurement unit is installed on the surface of the curved slope and its downstream region to collect flow field pressure data; An air supply and control unit is connected to the multiple tangential blowing slits and is used to provide independently controllable pulse blowing to each slit; The intelligent control unit, which is connected to the pressure measurement unit and the gas supply and control unit respectively, is configured to: based on the pressure data collected by the pressure measurement unit, perform iterative calculations through a built-in optimization algorithm to automatically find a set of optimal control parameters for controlling the gas supply and control unit, so as to suppress flow separation with low energy consumption.

[0023] The number of the multiple tangential blowing slits is three, and their outlets are located on the curved slope at flow positions of 0.95h, 1.50h, and 1.95h from the starting point of the slope, respectively, where h is the height of the curved slope.

[0024] The gas supply and control unit includes: Gas source; A pressure regulating device, connected to the air source, is used to precisely regulate the pressure of the output airflow; A high-speed switching valve, connected to the pressure regulating device, is used to modulate a continuous airflow into a pulse jet according to a received control signal; The control terminals of both the pressure regulating device and the high-speed switching valve are connected to the intelligent control unit.

[0025] The optimal control parameter combination includes the blowing pressure parameter and blowing duty cycle parameter corresponding to each tangential blowing slit, as well as the blowing frequency parameter shared by all slits and the phase difference parameter between the blowing pulse signals of each slit.

[0026] The optimization algorithm is a genetic algorithm, and its optimization process includes the following steps: Step 1, Initialization: Randomly generate an initial population containing multiple individuals, each individual representing a set of control parameter combinations; Step 2, Initial Assessment: Send the control parameters corresponding to each individual in the population to the gas supply and control unit for execution. After the flow field stabilizes, collect pressure data through the pressure measurement unit and calculate the cost function value corresponding to each individual. Step 3, Initial Judgment: If the cost function value of the best individual satisfies the preset convergence condition, then stop optimization and output the current best individual as the optimal control parameter combination; otherwise, proceed to step 4. Step 4, Initial Evolution: Based on the cost function values ​​of individuals in the current population, generate a new generation of population through selection, crossover, and mutation operations, and return to Step 2.

[0027] The cost function J is a weighted sum of a first term J1 representing the flow separation suppression effect and a second term J2 representing the input energy consumption, and its expression is: J = J 1+α J 2, where α is an adjustable weighting coefficient used to adjust the optimization objective to focus on separation suppression or energy saving.

[0028] The first term J1 is defined as the measured pressure coefficient C at the end of the curved slope. p，end With ideal pressure coefficient C p，end(ref) The absolute value of the difference between the current input energy E and the reference input energy E; the second term J2 is defined as the difference between the current input energy E and the reference input energy E. ref The ratio of .

[0029] The input energy E is calculated as follows: , among which, U jet1 U jet2 U jet3 The value represents the tangential slit outlet velocity at flow-direction locations on the slope at distances of 0.95h, 1.50h, and 1.95h from the slope initiation point, U. ∞ The value represents the incoming air velocity, T is the time period, and ∫dt is the integral over time.

[0030] Replace the optimization algorithm with a Bayesian optimization algorithm or an ant colony optimization algorithm.

[0031] The curved ramp and the multiple tangential air-blowing slits formed thereon are integrally molded structures.

[0032] Specifically, this invention provides a flow separation control device for curved slopes based on intelligent combined blowing, comprising three tangential blowing slit exciters located on the curved slope section, pressure measuring holes distributed on the slope and its downstream flat plate section, air inlet paths for the exciters, and a control parameter output and pressure data acquisition program based on an embedded genetic algorithm in LabVIEW software. To verify the effectiveness of this device, this invention designed a wind tunnel testing platform (… Figure 1 The origin O of the Cartesian coordinate system is defined below the starting point of the slope, parallel to the downstream plate. The directions x, y, and z correspond to the flow direction, spanwise direction, and vertical direction, respectively. The upstream plate has a length L1 = 2500 mm, and the downstream plate has a length L3 = 1600 mm. The curved slope consists of multiple circular arcs with a height h of 77.2 mm and a flow-direction length L2 = 202 mm. Figure 1 The three red line segments at the mid-curved slope represent the three tangential slits used for flow separation control, with their exit locations as shown below. Figure 2 As shown, they are located at x=0.95h, 1.50h, and 1.95h respectively. Figure 3 The figure shown is a cross-sectional view of the internal design of the exciter.Figure 3 Part (a) is a cross-sectional view in the yz plane, and part (b) is a cross-sectional view in the xy plane. The red arrows represent the airflow direction. A blowing slit consists of eight chambers, each with a length l = 60 mm and a width m = 1.3 mm. Airflow enters the chamber through the lower circular vent, then passes through an expansion section to reach the slit outlet. The expansion section is designed to allow the airflow to fully develop within the chamber, thus achieving uniform blowing at the exciter outlet. The curved ramp section and blowing slits are all made of resin material and 3D printed in one piece. At the middle section of the ramp, a row of pressure measuring holes is evenly distributed upstream, downstream, and on the ramp itself. These holes are connected to a 64-channel pressure scanner (PSI miniature pressure scanner) to measure the pressure P distribution on the curved ramp surface and assess the flow separation control effect.

[0033] Figure 4 The exciter's air intake path and the electrical components controlling the pulse jet are shown. The airflow is output from the upstream air compressor, passes through an oil-water filter to remove moisture, and reaches the electro-proportional valve for pressure regulation. The downstream pressure P is adjusted by changing the drive voltage of the electro-proportional valve (SMC ITV2030-312BS type). e The regulated airflow is controlled by a solenoid valve (FESTO MHJ10-S-2, 5-QS-4-MF type solenoid valve), and the pulse jet is finally ejected from the exciter outlet. The solenoid valve is controlled by a square wave signal; different blowing frequencies (f) are achieved by changing the square wave signal. e The unsteady blowing system of this invention has ten control parameters, namely the driving pressure P upstream of the three tangential slits at x / h=0.95, x / h=1.50, and x / h=1.95. e1 P e2 P e3 The three tangential slits have blowing duty cycles of DC1, DC2, and DC3, and all three slits share the same blowing frequency f. e The control signal phase φ1 is used for air blowing in the middle slit (x / h=1.50), and the control signal phase φ2 is used for air blowing in the downstream slit (x / h=0.95). To achieve the function of autonomously finding optimal control parameters based on the incoming flow characteristics, this invention designs a control system with an embedded genetic algorithm using LabVIEW software. Its operating logic is... Figure 4 As shown. First, the genetic algorithm generates control parameters and inputs them into the electro-proportional valve and the solenoid valve. After the air blowing stabilizes, pressure data of the flow field is collected using a pressure scanning valve through a pressure measuring hole located on the slope surface. The cost function value is calculated based on the pressure data. The genetic algorithm stores the cost function value and sorts it to generate the next set of control parameters. The entire process is repeated until the cost function value converges.

[0034] The definition of the cost function determines the direction of parameter optimization. To suppress turbulent flow separation, this invention uses a cost function J based on the pressure coefficient to evaluate the control effect. The expression for J is as follows: Where J1 is the pressure coefficient C at the end of the slope. p，end With ideal pressure coefficient C p，end(ref) The difference between J1 and J2 represents the effect of suppressing flow separation, J2 represents the energy input E required for control, and α is a constant used to adjust the ratio of J1 to J2. By adjusting α, we can optimize the parameters to either suppress flow separation (smaller α) or reduce energy consumption (larger α). E is defined as follows: Among them, U jet1 U jet2 U jet3 The value represents the tangential slit outlet velocity at x / h = 0.95, 1.50, and 1.95, U. ∞ The value represents the incoming air velocity.

[0035] The specific optimization process of the control system based on the genetic algorithm is as follows: (1) The genetic algorithm randomly generates the first generation population, and each individual in the population contains three slit jet control parameters. (2) All individuals in the population are verified in the experiment in turn. After the flow field stabilizes, the pressure is measured and the cost function J of each individual is calculated. The smaller the value of J, the better the individual is considered. (3) It is determined whether the cost function obtained by the individual in the population meets the stopping condition (the cost function of the best individual in the adjacent five generations of the population remains unchanged). If it meets the condition, it stops; if it does not meet the condition, it proceeds to the next step. (4) Based on the individuals in the current population and their corresponding cost functions, the genetic algorithm generates the next generation population through elite, selection, crossover, and mutation operations, and continues step (2). The entire optimization process is repeated until the stopping condition in step (3) is met, which means that the system control parameters have converged and stable and excellent control parameters have been found.

[0036] According to the research of this invention, the size of the recirculation zone is negatively correlated with the pressure coefficient at the end of the curved slope, i.e., C p，end The larger the value, the smaller the reflux region, C p，end The smaller the value, the larger the reflux zone. Ideal pressure coefficient C p，end(ref) The pressure coefficient at x / h=1.50, where steady blowing through a single slit completely eliminates the backflow region, is selected. The input energy at this point is E. ref This is referred to as the reference operating condition. Figure 5The graph shows a comparison between the unsteady blowing control obtained by the genetic algorithm optimization and the reference condition in terms of energy consumption and pressure coefficient recovery. When α=0.25, the optimal individual found by the genetic algorithm can achieve C... p，end =99.2%C p，end(ref) However, energy consumption is only 23.1% of the reference condition. Compared to the ideal condition of a single jet, it only sacrifices 0.8% of C. p，end At this value, 76.9% of the input energy was saved. When α=0.30, due to the large value of α, the input energy J2 dominates, therefore the energy input of the optimal individual found by the genetic algorithm is very small (E=17.5%E). ref However, at this time C p，end =85.8%C p，end(ref) This indicates that the flow separation suppression effect is significantly reduced at this point. Figure 6 Demonstrates no control ( Figure 6 (a) in the reference condition ( Figure 6 Part (b) and the genetic algorithm at α=0.25 Figure 6 (Part c) and 0.30 Figure 6 The mean streamline and velocity contour plots for part (d) are shown. Although the flow separation was not completely suppressed under the optimal individual control found at α=0.30, the recirculation zone was significantly reduced, and the energy consumption at this time was only 17.5% of that of the reference condition, which is still very considerable.

[0037] Unlike traditional single-slit blowing control, this invention employs three slits for coordinated blowing. By controlling the blowing of each of the three slits individually, optimal flow separation on the curved slope can be achieved. This invention designs an intelligent blowing system capable of autonomously controlling excitation, acquiring data, and optimizing parameters. Through iterative genetic algorithms, the blowing input parameters for each of the three slits are obtained, and the optimal solution for input energy and control effect is calculated, achieving higher control efficiency and lower input energy compared to traditional techniques. The intelligent blowing system designed in this invention has wide applicability; by modifying parameters such as the cost function within the intelligent blowing system, ideal control laws can be optimized to meet different needs.

[0038] Existing techniques for controlling surface flow separation are limited to controlling a single air-blowing slit. While these techniques offer good control, they cannot further optimize energy consumption. This invention utilizes a combination of three slits for air blowing, employing a genetic algorithm to optimize the corresponding control parameters. By comparing the control performance with that under ideal conditions using a single slit, the optimized control parameters obtained by this system can save at least 70% of the input energy while maintaining the same control effect. Furthermore, using a genetic algorithm for parameter optimization significantly reduces manpower and avoids tedious, repetitive experiments.

[0039] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A curved slope flow separation control device based on intelligent combined air blowing, characterized in that, include: Multiple tangential air-blowing slits are opened on the curved slope and distributed along the flow direction; A pressure measurement unit is installed on the surface of the curved slope and its downstream region to collect flow field pressure data; An air supply and control unit is connected to the multiple tangential blowing slits and is used to provide independently controllable pulse blowing to each slit; The intelligent control unit, which is connected to the pressure measurement unit and the gas supply and control unit respectively, is configured to: based on the pressure data collected by the pressure measurement unit, perform iterative calculations through a built-in optimization algorithm to automatically find a set of optimal control parameters for controlling the gas supply and control unit, so as to suppress flow separation with low energy consumption.

2. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 1, characterized in that, The number of the multiple tangential blowing slits is at least three, and their outlets are located on the curved slope at different flow positions from the slope's starting point at different slope heights.

3. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 1, characterized in that, The gas supply and control unit includes: Gas source; A pressure regulating device, connected to the air source, is used to precisely regulate the pressure of the output airflow; A high-speed switching valve, connected to the pressure regulating device, is used to modulate a continuous airflow into a pulse jet according to a received control signal; The control terminals of both the pressure regulating device and the high-speed switching valve are connected to the intelligent control unit.

4. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 1, characterized in that, The optimal control parameter combination includes the blowing pressure parameter and blowing duty cycle parameter corresponding to each tangential blowing slit, as well as the blowing frequency parameter shared by all slits and the phase difference parameter between the blowing pulse signals of each slit.

5. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 1, characterized in that, The optimization algorithm is a genetic algorithm, and its optimization process includes the following steps: Step 1, Initialization: Randomly generate an initial population containing multiple individuals, each individual representing a set of control parameter combinations; Step 2, Initial Assessment: Send the control parameters corresponding to each individual in the population to the gas supply and control unit for execution. After the flow field stabilizes, collect pressure data through the pressure measurement unit and calculate the cost function value corresponding to each individual. Step 3, Initial Judgment: If the cost function value of the best individual satisfies the preset convergence condition, then stop optimization and output the current best individual as the optimal control parameter combination; otherwise, proceed to step 4. Step 4, Initial Evolution: Based on the cost function values ​​of individuals in the current population, generate a new generation of population through selection, crossover, and mutation operations, and return to Step 2.

6. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 5, characterized in that, The cost function J is a weighted sum of a first term J1 representing the flow separation suppression effect and a second term J2 representing the input energy consumption, and its expression is: J = J 1+α J 2, where α is an adjustable weighting coefficient used to adjust the optimization objective to focus on separation suppression or energy saving.

7. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 6, characterized in that, The first term J1 is defined as the measured pressure coefficient C at the end of the curved slope. p，end With ideal pressure coefficient C p，end(ref) The absolute value of the difference between the current input energy E and the reference input energy E; the second term J2 is defined as the difference between the current input energy E and the reference input energy E. ref The ratio of .

8. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 7, characterized in that, The input energy E is calculated as follows: , among which, U jet1 U jet2 U jet3 The value represents the tangential slit outlet velocity at flow-direction locations on the slope at distances of 0.95h, 1.50h, and 1.95h from the slope initiation point, U. ∞ The value represents the incoming air velocity, T is the time period, and ∫dt is the integral over time.

9. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 5, characterized in that, Replace the optimization algorithm with a Bayesian optimization algorithm or an ant colony optimization algorithm.

10. The curved slope flow separation control device based on intelligent combined air blowing as described in claim 1, characterized in that, The curved ramp and the multiple tangential air-blowing slits formed thereon are integrally molded structures.

Images