A curved slope flow separation control device based on intelligent combined blowing

Abstract

The application provides a curved surface slope flow separation control device based on intelligent combined blowing, and relates to the field of fluid mechanics active control technology, and comprises the following: a plurality of tangential blowing slits which are arranged on a curved surface slope and are distributed along a flow direction; a pressure measurement unit which is arranged on the surface of the curved surface slope and a downstream area thereof and is used for collecting flow field pressure data; a gas path supply and control unit which is connected with the plurality of tangential blowing slits and is used for providing independent controllable pulse blowing to each slit; and an intelligent control unit which is signal connected with the pressure measurement unit and the gas path supply and control unit and is configured to: based on the pressure data collected by the pressure measurement unit, iteratively calculate through an embedded optimization algorithm, and automatically optimize to obtain a set of optimal control parameter combinations for controlling the gas path supply and control unit. The application can achieve the best control effect of the curved surface slope flow separation, and has higher control efficiency and smaller input energy compared with traditional technologies.

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 depending on 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 flow separation of the curved ramp, 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 flow separation of the curved ramp 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:

[0007] A plurality of tangential blowing slits are provided on the curved ramp and are distributed along the flow direction;

[0008] 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;

[0009] 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.

[0010] 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.

[0011] 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.

[0012] Optionally, the air path supply and control unit comprises:

[0013] An air source;

[0014] A pressure regulating device connected with the air source and configured to accurately regulate the pressure of the output air flow;

[0015] A high-speed on-off valve connected with the pressure regulating device and configured to modulate the continuous air flow into pulse jet flow according to the received control signal;

[0016] The control ends of the pressure regulating device and the high-speed on-off valve are connected with the intelligent control unit.

[0017] 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 common to all slits and a phase difference parameter between the blowing pulse signals of each slit.

[0018] Optionally, the optimization algorithm is a genetic algorithm, and the optimization process comprises the following steps:

[0019] Step 1, initialization: randomly generate an initial population containing a plurality of individuals, each individual representing a set of control parameter combinations;

[0020] Step 2, preliminary evaluation: send 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, collect the pressure data through the pressure measurement unit and calculate the cost function value corresponding to each individual;

[0021] Step 3, preliminary judgment: if the cost function value of the best individual meets the preset convergence condition, stop optimization and output the current best individual as the optimal control parameter combination; otherwise, execute step 4.

[0022] Step 4, initial evolution: based on the cost function value of the individual in the current population, a new generation of population is generated through selection, crossover and mutation operations, and returns to step 2.

[0023] Optionally, the cost function J is composed of a first term J1 representing the flow separation suppression effect and a second term J2 representing the input energy consumption, and the expression is: J = J 1+ α J 2, wherein α is an adjustable weight coefficient for adjusting the optimization goal to focus on separation suppression or energy saving.

[0024] Optionally, the first term J1 is defined as the absolute value of the difference between the measured pressure coefficient C p，end at the end of the curved surface slope and the ideal pressure coefficient C p，end(ref) ; and the second term J2 is defined as the ratio of the current input energy E and the reference input energy E ref .

[0025] Optionally, the input energy E is calculated as: , wherein U jet1 , U jet2 , U jet3 represent the tangential slit blowing outlet velocity at the positions of 0.95h, 1.50h and 1.95h from the starting point of the slope on the curved surface slope, U ∞ represents the incoming flow velocity, T is the time period, and ∫dt is the time integral.

[0026] Optionally, the optimization algorithm is replaced by a Bayesian optimization algorithm or an ant colony optimization algorithm.

[0027] Optionally, the curved surface slope and the plurality of tangential blowing slits opened thereon are an integrally formed structure.

[0028] The present application has the following beneficial effects:

[0029] Unlike the conventional single-slit blowing control, the present application provides three slits for collaborative blowing. By controlling the three slits separately, the best control effect of the curved surface slope flow separation can be achieved. The present application designs an intelligent blowing system that can independently control excitation, collect data and optimize parameters. Through genetic algorithm iteration, the blowing input parameters of the three slits are obtained, and the optimal solution of the input energy and control effect is calculated, thereby achieving higher control efficiency and smaller input energy compared to traditional technology. The intelligent blowing system designed by the present application has wide applicability. By modifying the cost function and other parameters inside the intelligent blowing system of the present application, the ideal control law can be optimized and obtained according to different requirements.

[0030] The existing control technology of curved surface flow separation is limited to the control of a single blowing slit, although it has good control effect, but cannot further optimize energy consumption. The present application blows through three slits in combination, obtains the corresponding control parameters by means of genetic algorithm optimization, and compares with the control effect of the ideal working condition of a single slit, and the control parameters optimized by the system can save at least 70% of the input energy under the condition of the same control effect. At the same time, the genetic algorithm is used to optimize the parameters, which can greatly save manpower and avoid tedious repetitive experiments.

[0031] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be achieved and obtained by the structure particularly pointed out in the written description and the accompanying drawings.

[0032] The technical solutions of the present application will be further described in detail below by means of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0033] The accompanying drawings are used to provide further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with embodiments of the present application, and do not constitute a limitation of the present application. In the drawings:

[0034] Figure 1 is a schematic diagram of the curved surface slope experimental device of the present application as a whole;

[0035] Figure 2 is a schematic diagram of the outlet position of the tangential blowing slit on the curved surface slope of the present application;

[0036] Figure 3 is a sectional view of the internal design of the tangential blowing slit exciter of the present application;

[0037] Figure 4 is a schematic diagram of the exciter gas path system and intelligent control principle of the present application;

[0038] Figure 5 is a comparison diagram of the unsteady blowing control optimized by the genetic algorithm of the present application and the reference working condition (single-slit steady blowing) in terms of energy consumption and pressure coefficient recovery;

[0039] Figure 6 is a time-averaged flow field diagram of the curved surface slope flow under different control conditions. DETAILED DESCRIPTION

[0040] The preferred embodiments of the present application will be described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0041] The embodiment of the present application provides a curved-surface slope flow separation control device based on intelligent combined blowing, which comprises:

[0042] A plurality of tangential blowing slits are arranged on the curved-surface slope and are distributed along the flow direction.

[0043] A pressure measuring unit is arranged on the curved-surface slope surface and a downstream area thereof, and is used for collecting flow field pressure data.

[0044] A gas path supply and control unit is connected with the plurality of tangential blowing slits, and is used for providing independent controllable pulse blowing to each slit.

[0045] An intelligent control unit is connected with the pressure measuring unit and the gas path supply and control unit in signal, and is configured to: based on the pressure data collected by the pressure measuring unit, perform iterative calculation through an embedded optimization algorithm, and automatically obtain a set of optimal control parameter combinations for controlling the gas path supply and control unit, so that flow separation is inhibited with low energy consumption.

[0046] The plurality of tangential blowing slits are three in number, and the outlets thereof are located at the flow direction positions of 0.95h, 1.50h and 1.95h from a starting point of the curved-surface slope, wherein h is the height of the curved-surface slope.

[0047] The gas path supply and control unit comprises:

[0048] A gas source;

[0049] A pressure regulating device connected with the gas source and used for accurately regulating the pressure of the output gas flow;

[0050] A high-speed on-off valve connected with the pressure regulating device and used for modulating continuous gas flow into pulse jet flow according to the received control signal;

[0051] The control ends of the pressure regulating device and the high-speed on-off valve are connected with the intelligent control unit.

[0052] The optimal control parameter combination comprises blowing pressure parameters and blowing duty cycle parameters corresponding to each tangential blowing slit, and blowing frequency parameters and phase difference parameters between blowing pulse signals of each slit which are shared by all the slits.

[0053] The optimization algorithm is a genetic algorithm, and the optimization process thereof comprises the following steps:

[0054] Step 1, initialization: randomly generating an initial population containing a plurality of individuals, each individual representing a set of control parameter combinations;

[0055] Step 2, initial evaluation: the control parameters corresponding to each individual in the population are sent to the air path supply and control unit for execution, and after the flow field stabilizes, the pressure data is collected by the pressure measurement unit, and the cost function value corresponding to each individual is calculated;

[0056] Step 3, initial judgment: if the cost function value of the optimal individual meets the preset convergence condition, stop optimization and output the current optimal individual as the optimal control parameter combination; otherwise, execute step 4;

[0057] Step 4, initial evolution: based on the cost function values of the individuals in the current population, a new generation of population is generated through selection, crossover and mutation operations, and returns to step 2.

[0058] The cost function J is composed 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, wherein α is an adjustable weight coefficient for adjusting the optimization target to focus on separation suppression or energy saving.

[0059] The first term J1 is defined as the absolute value of the difference between the measured pressure coefficient C p，end at the end of the curved surface slope and the ideal pressure coefficient C p，end(ref) ; the second term J2 is defined as the ratio of the current input energy E to the reference input energy E ref .

[0060] The calculation method of the input energy E is: , wherein U jet1 , U jet2 , and U jet3 represent the tangential slit blowing outlet velocities at the positions of 0.95h, 1.50h and 1.95h on the surface slope from the starting point of the slope, U ∞ represents the incoming flow velocity, T is the time period, and ∫dt is the time integral.

[0061] The optimization algorithm is replaced by a Bayesian optimization algorithm or an ant colony optimization algorithm.

[0062] The curved surface slope and the plurality of tangential blowing slits opened thereon are an integral structure.

[0063] Specifically, the application provides a curved-surface ramp flow separation control device based on intelligent combined blowing, which comprises three tangential blowing slit exciters located on a curved-surface ramp section, pressure measuring holes distributed on the ramp and a downstream flat plate section, an air inlet channel of the exciters, and a control parameter output and pressure data acquisition program based on an embedded genetic algorithm of LabVIEW software. Figure 1 The origin O of the Cartesian coordinate system is defined below the starting point of the ramp and parallel to the downstream flat plate, and the directions x, y and z correspond to the flow direction, the spanwise direction and the vertical direction, respectively. The length of the upstream flat plate L1 is 2500 mm, and the length of the downstream flat plate L3 is 1600 mm. The curved-surface ramp is composed of multiple circular arcs, the height h of which is 77.2 mm, and the length L2 in the flow direction is 202 mm. Figure 1 Three red line segments in the curved-surface ramp position represent three tangential slits for flow separation control, and the outlet positions are shown in Figure 2 The three red line segments in the curved-surface ramp position represent three tangential slits for flow separation control, and the outlet positions are shown in Figure 3 The internal design cross-sectional view of the exciter is shown. Figure 3 Part (a) is a y-z plane cross-sectional view, and part (b) is an x-y plane interface view. The red arrows represent the direction of air flow. One blowing slit is composed of eight cavities, each slit has a length l of 60 mm and a width m of 1.3 mm. The air flow enters the cavity through the lower circular air port, then passes through an expansion section to the slit outlet. The expansion section is used for the air flow to develop fully in the cavity, so as to achieve the purpose of uniform blowing at the outlet of the exciter. The curved-surface ramp section and the blowing slit are integrally processed and formed by 3D printing using resin material. At the middle cross section of the ramp, a row of pressure measuring holes are evenly distributed on the upstream of the ramp, the ramp and the downstream of the ramp. The pressure measuring holes are connected with a 64-channel pressure scanner (PSI micro pressure scanner) to measure the distribution of the surface pressure P of the curved-surface ramp and judge the flow separation control effect.

[0064] Figure 4 The air inlet channel of the exciter and the electrical elements for controlling the pulse jet are shown. The air flow is output by an upstream air source air compressor, filtered through an oil and water filter to reach an electrical proportional valve for adjusting the pressure. The downstream pressure P e is adjusted by changing the driving voltage of the electrical proportional valve (SMC company ITV2030-312BS type electrical proportional valve). The pressure-adjusted air flow realizes on-off control of the air flow through an electromagnetic valve (FESTO company MHJ10-S-2,5-QS-4-MF type electromagnetic valve), and the pulse jet is finally sprayed out of the outlet of the exciter. The electromagnetic valve is controlled by a square wave signal, and different blowing frequencies f e, duty cycle DC and slit blowing phase. The unsteady blowing system of the present invention has ten control parameters, which are driving pressure P e1 , P e2 , P e3 , blowing duty cycle DC1, DC2, DC3 of three tangential slits, blowing frequency f e , control signal phase of middle slit blowing (x / h = 1.50). The control signal phase of downstream slit blowing (x / h = 0.95). In order to realize the function of autonomously searching for excellent control parameters for incoming flow characteristics, the present invention designs a control system embedded with genetic algorithm using LabVIEW software as a medium, and the running logic thereof is shown in Fig. 8. First, the genetic algorithm generates control parameters and inputs them to the electrical proportional valve and electromagnetic valve, and after the blowing is stable, the pressure scanning valve is used to collect flow field pressure data through the pressure measuring hole located on the ramp surface. The cost function value is calculated according to the pressure data, and the genetic algorithm stores the cost function value and sorts it to generate the next set of control parameters. The whole process is repeated until the cost function value converges. Figure 4

[0065] The definition of the cost function determines the direction of parameter optimization. In order to realize the suppression of turbulent flow separation, the present invention uses the cost function J based on the pressure coefficient to evaluate the control effect. The expression of J is as follows

[0066]

[0067] Wherein, J1 is the difference between the pressure coefficient C p，end at the end of the ramp and the ideal pressure coefficient C p，end(ref) , representing the suppression effect of flow separation, and J2 represents the energy E needed for control, and a is a constant used to adjust the proportion of J1 and J2. By adjusting a, we can realize the optimization of the parameters in the direction of more conducive to suppressing flow separation (a small) or more conducive to reducing energy consumption (a large). The definition of E is as follows:

[0068]

[0069] Wherein, U jet1 , U jet2 , U jet3 values represent the tangential slit blowing outlet velocity at x / h = 0.95, 1.50, 1.95, and U ∞ value represents the incoming flow velocity.

[0070] ​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.

[0071] 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 5 The 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 6The current-voltage diagram and velocity cloud diagram at the time of the middle (d) part) The flow field under the control of the optimal individual found at α = 0.30, although not completely suppress flow separation, but the recirculation zone is greatly reduced, the energy consumption at this time is only 17.5% of the reference condition, its control efficiency is very considerable.

[0072] Unlike the traditional single slit blowing control, the present invention provides three slits for coordinated blowing. By controlling the blowing of the three slits separately, the optimal control of the curved surface slope flow separation can be achieved. The present invention designs an intelligent blowing system that can independently control the excitation, collect data, and optimize parameters. Through genetic algorithm iteration, the blowing input parameters of the three slits are obtained, and the optimal solution of input energy and control effect is calculated, thereby achieving higher control efficiency and smaller input energy compared to traditional technology. The intelligent blowing system designed by the present invention has wide applicability. By modifying the cost function and other parameters inside the intelligent blowing system, the ideal control law can be optimized according to different requirements.

[0073] The existing control surface flow separation technology is limited to the control of a single blowing slit, although it has good control effect, but cannot further optimize the energy consumption. The present invention uses three slits for combined blowing, and uses genetic algorithm optimization to obtain the corresponding control parameters. Compared with the ideal working condition control effect of a single slit, the control parameters optimized by the system can save at least 70% of the input energy under the same control effect. At the same time, the use of genetic algorithm for parameter optimization can greatly save manpower and avoid tedious repetitive experiments.

[0074] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A curved ramp flow separation control device based on smart combination blowing, characterized by, 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 smart combination blowing based curved surface ramp flow separation control device according to claim 1, wherein, 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 smart combination blowing based curved surface ramp flow separation control device according to claim 1, wherein, 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 smart combination blowing based curved surface ramp flow separation control device according to claim 1, wherein, 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 smart combination blowing based curved surface ramp flow separation control device according to claim 1, wherein, 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 smart combination blowing based curved surface ramp flow separation control device according to claim 5, wherein, The cost function J by a first term representing the flow separation suppression effect J 1 and a second term representing the input energy consumption J 2 weighted composition, whose expression is: J J 1 + α J 2, where α is an adjustable weight coefficient for adjusting the optimization target to focus on separation suppression or energy saving.​ 7. The smart combination blowing based curved surface ramp flow separation control device according to claim 6, wherein, the first term J 1 defined as the absolute value of the difference between the measured pressure coefficient at the end of the curved ramp C p，end and the ideal pressure coefficient C p，end(ref) ; the second term J 2 defined as the ratio of the current input energy E to the reference input energy E ref .

8. The smart combination blowing based curved surface ramp flow separation control device according to claim 7, wherein, The input energy E is calculated as: ， wherein U jet1 , U jet2 , U jet3 values represent the tangential slot blowing exit velocity at the flow direction locations of 0.95h, 1.50h and 1.95h from the start of the slope, U ∞ values represent the incoming flow wind speed, T is the time period, ∫dt is the time integral.

9. The smart combination blowing based curved surface ramp flow separation control device according to claim 5, wherein, Replace the optimization algorithm with a Bayesian optimization algorithm or an ant colony optimization algorithm.

10. The smart combination blowing based curved surface ramp flow separation control device according to claim 1, wherein, The curved ramp and the multiple tangential air-blowing slits formed thereon are integrally molded structures.

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