Final Report Summary - CLFCWTE (Development of a Closed Loop Flow Control Algorithm for Wing Trailing Edge Flow Control Including Experimental Validation in Two Low Speed Wind Tunnel Tests)
Executive Summary:
In this work, active flow control using pulsed air jets was investigated in order to delay flow separation on a two-element high-lift wing. The method was validated experimentally. A novel iterative learning control (ILC) algorithm was developed that uses position based pressure measurements to update the actuation. The method was experimentally tested on a wing model in a 0.9 m x 0.6 m wind tunnel initially and then the R. J. Mitchell wind tunnel at the University of Southampton. Compressed air and fast switching solenoid valves were used as actuators to excite the flow and the pressure distribution around the chord of the wing was measured as a feedback control signal for the ILC controller. Experimental results showed that the actuation was able to delay the separation and increase the overall lift by approximately 15% to 20%. By using the ILC algorithms, the controller was able to track the target lift and using the optimum control algorithm with an extended reference, the controller was able to maximize the lift enhancement. In the second wind tunnel test session, open loop tests were completed to generate data which was used to create a system model. A two-dimensional model function was then fitted using locally weighted scatter-plot smoothing and the model was applied in a model based iterative learning optimization algorithm. Wind tunnel experimental results showed that the method was able to optimise the performance with two variables and an overall lift enhancement of approximately 20% could be achieved.
Project Context and Objectives:
Smart Fixed Wing Aircraft (SFWA) aims to develop and test passive and active flow control technologies to improve the high lift performance of a wing. The technology will be used to help achieve the ACARE 2020 vision. SFWA will work towards the reducing the emissions by 20% and the noise by 5 – 10 dB. Pollution and the reduction in CO2 emissions are also both politically and regulatory important issues.
In this research, the use of pulsed blowing was used to delay separation, thereby increasing the performance of the high-lift system. A closed loop flow control system was developed and demonstrated. The high-lift configuration tested was a slat-less configuration with a single slotted fowler flap. In a traditional three-element high lift device system, the slat is used to increase the maximum coefficient of lift (CLmax). Using flow control to delay separation on the trailing-edge flap, the need of a leading-edge slat can be eliminated. Wind tunnel experiments have identified the leading-edge slat as one of the most dominant source of high lift noise on modern aircraft. The computational work on leading edge slat has focused on the generation of noise from the slat trailing edge, the unsteady oscillating slat cove vortex and the free shear layer bounding the slat cove vortex. By removing the slat, the airframe noise can be reduced and the weight of the aircraft can potentially be reduced thereby increasing fuel efficiency.
The purpose of this research was to develop and demonstrate a closed loop flow control to minimise the separation on a trailing-edge flap. The active flow control improved the aerodynamic performance by delaying the trailing-edge separation on a single element trailing-edge flap. The flow control was pulsed blowing applied near the leading-edge region of the flap. The pulsed blowing was applied through spanwise segmented slots. A closed loop flow control system was designed to demonstrate flow control on a mid-scale wind tunnel model.
The overall technical strategy of the work is described as follows. Firstly, the design of the closed loop flow control system was undertaken after a concept report on the chosen flow control method and the closed loop methodology. Secondly, pre-tests on the system were performed at the University of Southampton with a two-dimensional model. Thirdly, the flow control actuators and the appropriate parts of the closed loop flow control system were integrated into the wind tunnel model. The wind tunnel model for the mid-scale tests was provided by DLR. Fourthly, the mid-scale tests were performed in two wind tunnel tests.
The Topic Description calls for two directions of closed loop flow control methods. The first was a pre-modelled approach which allowed the calibrating of the algorithm. The second method was an adaptive algorithm, which was adjusted by a “learning-by-doing” system. These two approaches were demonstrated in wind tunnel tests.
Project Results:
In this research project, active flow control using pulsed air jets was investigated in order to delay flow separation on a two-element high-lift wing. The actuation was achieved by high pressure compressed air and fast switching solenoid valves. The valves were controlled by a dSPACE ds1006 system with a PC running Matlab/Simulink. A novel position based iterative learning control was developed and applied to active flow separation control. The technique uses surface pressure measurements to update actuation duty cycle iteratively in order to optimise the lift enhancement.
Open loop control tests were performed in order to get data for system modelling and reference generation. Wind tunnel experiments demonstrate that the basic P-type ILC algorithm was able to tracking the given reference and the performance could be maximised by an optimal ILC algorithm with extended reference. Additionally, an iterative learning optimisation algorithm was developed and tested using two two-dimensional models of different variable pairs which were obtained by performing open loop tests. Wind tunnel experiments demonstrated that the method was able to delay flow separation and provide lift enhancement without any reference signal. The control inputs converged to the expected optimal values and an overall lift improvement of approximately 20% was achieved.
The three milestones and four deliverables specified in the Description of Work were completed.
A fuller description of the main S & T results/foregrounds in included in the attached document.
Potential Impact:
There are three aspects of environmental impact of air transport: environmental noise, NOx emissions, and Carbon emissions (fuel burn). The three adverse effects of air transport, i.e. environmental noise, NOx emissions, and Carbon emissions, are closely linked together (see Figure 15). Often, technologies that can reduce one impact would directly lead to an increase in the other impact. For example, reducing environmental noise often requires introducing additional aerodynamic surfaces to deflect or shield noise away from the ground. This necessitates higher aerodynamic drag and therefore higher fuel burn to generate additional thrust, leading to higher CO2 and NOx emissions. Internationally in the ACARE (Advisory Council for Aerospace Research in Europe) “European Visions 2000-2020”, and in a similar manner spelled out in the NASA QAT (Quiet Aircraft Technology) program in the United States of America, a noise reduction target of 10 dB in 20 years was defined based on 1997 aircraft technology. This target has to be met together with targets of reducing NOx emissions by 80% and fuel consumption and CO2 emissions by 50% by 2020. These are a set of very stringent targets as a reduction of perceived external noise by 50% means a reduction of 10 dB (equivalent to a reduction of 90% of sound power).
The work performed in CLFCWTE will contribute towards the noise reduction target mentioned above and a decrease in the fuel consumption due to an increase in aerodynamic efficiency. This will add to the competiveness of the European Union. The active flow control on the slat-less high lift configuration will provide a benefit for those living in communities around airports. It will also allow airlines to comply with environmental regulations. Closed loop flow control on a high-lift configuration using novel algorithms goes beyond the state of the art and has the potential to change civil aviation aerodynamics.
List of Websites:
http://www.southampton.ac.uk/engineering
http://www.southampton.ac.uk/antc
In this work, active flow control using pulsed air jets was investigated in order to delay flow separation on a two-element high-lift wing. The method was validated experimentally. A novel iterative learning control (ILC) algorithm was developed that uses position based pressure measurements to update the actuation. The method was experimentally tested on a wing model in a 0.9 m x 0.6 m wind tunnel initially and then the R. J. Mitchell wind tunnel at the University of Southampton. Compressed air and fast switching solenoid valves were used as actuators to excite the flow and the pressure distribution around the chord of the wing was measured as a feedback control signal for the ILC controller. Experimental results showed that the actuation was able to delay the separation and increase the overall lift by approximately 15% to 20%. By using the ILC algorithms, the controller was able to track the target lift and using the optimum control algorithm with an extended reference, the controller was able to maximize the lift enhancement. In the second wind tunnel test session, open loop tests were completed to generate data which was used to create a system model. A two-dimensional model function was then fitted using locally weighted scatter-plot smoothing and the model was applied in a model based iterative learning optimization algorithm. Wind tunnel experimental results showed that the method was able to optimise the performance with two variables and an overall lift enhancement of approximately 20% could be achieved.
Project Context and Objectives:
Smart Fixed Wing Aircraft (SFWA) aims to develop and test passive and active flow control technologies to improve the high lift performance of a wing. The technology will be used to help achieve the ACARE 2020 vision. SFWA will work towards the reducing the emissions by 20% and the noise by 5 – 10 dB. Pollution and the reduction in CO2 emissions are also both politically and regulatory important issues.
In this research, the use of pulsed blowing was used to delay separation, thereby increasing the performance of the high-lift system. A closed loop flow control system was developed and demonstrated. The high-lift configuration tested was a slat-less configuration with a single slotted fowler flap. In a traditional three-element high lift device system, the slat is used to increase the maximum coefficient of lift (CLmax). Using flow control to delay separation on the trailing-edge flap, the need of a leading-edge slat can be eliminated. Wind tunnel experiments have identified the leading-edge slat as one of the most dominant source of high lift noise on modern aircraft. The computational work on leading edge slat has focused on the generation of noise from the slat trailing edge, the unsteady oscillating slat cove vortex and the free shear layer bounding the slat cove vortex. By removing the slat, the airframe noise can be reduced and the weight of the aircraft can potentially be reduced thereby increasing fuel efficiency.
The purpose of this research was to develop and demonstrate a closed loop flow control to minimise the separation on a trailing-edge flap. The active flow control improved the aerodynamic performance by delaying the trailing-edge separation on a single element trailing-edge flap. The flow control was pulsed blowing applied near the leading-edge region of the flap. The pulsed blowing was applied through spanwise segmented slots. A closed loop flow control system was designed to demonstrate flow control on a mid-scale wind tunnel model.
The overall technical strategy of the work is described as follows. Firstly, the design of the closed loop flow control system was undertaken after a concept report on the chosen flow control method and the closed loop methodology. Secondly, pre-tests on the system were performed at the University of Southampton with a two-dimensional model. Thirdly, the flow control actuators and the appropriate parts of the closed loop flow control system were integrated into the wind tunnel model. The wind tunnel model for the mid-scale tests was provided by DLR. Fourthly, the mid-scale tests were performed in two wind tunnel tests.
The Topic Description calls for two directions of closed loop flow control methods. The first was a pre-modelled approach which allowed the calibrating of the algorithm. The second method was an adaptive algorithm, which was adjusted by a “learning-by-doing” system. These two approaches were demonstrated in wind tunnel tests.
Project Results:
In this research project, active flow control using pulsed air jets was investigated in order to delay flow separation on a two-element high-lift wing. The actuation was achieved by high pressure compressed air and fast switching solenoid valves. The valves were controlled by a dSPACE ds1006 system with a PC running Matlab/Simulink. A novel position based iterative learning control was developed and applied to active flow separation control. The technique uses surface pressure measurements to update actuation duty cycle iteratively in order to optimise the lift enhancement.
Open loop control tests were performed in order to get data for system modelling and reference generation. Wind tunnel experiments demonstrate that the basic P-type ILC algorithm was able to tracking the given reference and the performance could be maximised by an optimal ILC algorithm with extended reference. Additionally, an iterative learning optimisation algorithm was developed and tested using two two-dimensional models of different variable pairs which were obtained by performing open loop tests. Wind tunnel experiments demonstrated that the method was able to delay flow separation and provide lift enhancement without any reference signal. The control inputs converged to the expected optimal values and an overall lift improvement of approximately 20% was achieved.
The three milestones and four deliverables specified in the Description of Work were completed.
A fuller description of the main S & T results/foregrounds in included in the attached document.
Potential Impact:
There are three aspects of environmental impact of air transport: environmental noise, NOx emissions, and Carbon emissions (fuel burn). The three adverse effects of air transport, i.e. environmental noise, NOx emissions, and Carbon emissions, are closely linked together (see Figure 15). Often, technologies that can reduce one impact would directly lead to an increase in the other impact. For example, reducing environmental noise often requires introducing additional aerodynamic surfaces to deflect or shield noise away from the ground. This necessitates higher aerodynamic drag and therefore higher fuel burn to generate additional thrust, leading to higher CO2 and NOx emissions. Internationally in the ACARE (Advisory Council for Aerospace Research in Europe) “European Visions 2000-2020”, and in a similar manner spelled out in the NASA QAT (Quiet Aircraft Technology) program in the United States of America, a noise reduction target of 10 dB in 20 years was defined based on 1997 aircraft technology. This target has to be met together with targets of reducing NOx emissions by 80% and fuel consumption and CO2 emissions by 50% by 2020. These are a set of very stringent targets as a reduction of perceived external noise by 50% means a reduction of 10 dB (equivalent to a reduction of 90% of sound power).
The work performed in CLFCWTE will contribute towards the noise reduction target mentioned above and a decrease in the fuel consumption due to an increase in aerodynamic efficiency. This will add to the competiveness of the European Union. The active flow control on the slat-less high lift configuration will provide a benefit for those living in communities around airports. It will also allow airlines to comply with environmental regulations. Closed loop flow control on a high-lift configuration using novel algorithms goes beyond the state of the art and has the potential to change civil aviation aerodynamics.
List of Websites:
http://www.southampton.ac.uk/engineering
http://www.southampton.ac.uk/antc
