M. Voskuijl
Please Note
17 records found
1
Flight Mechanics and Performance of Direct Lift Control
Applying Control Allocation Methods to a Staggered Box-Wing Aircraft Configuration
Redundant effectors can be linked together, and to the pilot input, in many ways according to different optimality criteria and/or performance objectives. In particular, the research presented in this dissertation focuses on the possibility to achieve Direct Lift Control (DLC). The latter is intended as the ability to use control effectors to alter the aircraft lift "without, or largely without, significant change in the aircraft incidence, and ideally is meant not to generate pitching moment."
The ability to do so is essentially dependent on the position of the Control Center of Pressure (CCoP), which is the center of pressure of aerodynamic forces solely due to control surface deflections. In case of a single control surface dedicated to DLC, the CCoP coincides with the control surface itself. In case of redundant control surfaces, their deflections can be coordinated to induce the position of the CCoP towards some preferred location, as allowed by the architecture of the aircraft and the available control effectiveness.
The first three chapters of the dissertation are dedicated to establishing the societal, scientific, and technical background underlying the subsequent research studies, including an overview of the CA problem for redundant control effectors. The following four chapters present, in this order: an evaluation of the mission performance of a staggered box-wing aircraft model designed for commercial transonic operations; a comparison of different CA methods on the design of an optimum control surface layout for a box-wing aircraft, with control surface both fore and aft the aircraft center of gravity; a trim problem formulation which employs forces and moments due to the aircraft control surfaces as decision variables, to maximize control authority, minimize aerodynamic drag or obtain a prescribed pitch angle; a CA-based formulation aimed at altering the characteristics of the transient response of an aircraft by exploiting the properties of the CCoP.
The conclusive chapter presents a comprehensive, top-level recap of the main aspects and topics covered within the dissertation. It reflects on the classic meaning of DLC, and what it means to achieve it with redundant control surfaces that are not expressly dedicated to it. With some considerations on the needs of aviation market, it speculates on the practical role of unconventional aircraft configurations in the near future. Lastly, it provides suggestions for improvements and future research studies.
...
Redundant effectors can be linked together, and to the pilot input, in many ways according to different optimality criteria and/or performance objectives. In particular, the research presented in this dissertation focuses on the possibility to achieve Direct Lift Control (DLC). The latter is intended as the ability to use control effectors to alter the aircraft lift "without, or largely without, significant change in the aircraft incidence, and ideally is meant not to generate pitching moment."
The ability to do so is essentially dependent on the position of the Control Center of Pressure (CCoP), which is the center of pressure of aerodynamic forces solely due to control surface deflections. In case of a single control surface dedicated to DLC, the CCoP coincides with the control surface itself. In case of redundant control surfaces, their deflections can be coordinated to induce the position of the CCoP towards some preferred location, as allowed by the architecture of the aircraft and the available control effectiveness.
The first three chapters of the dissertation are dedicated to establishing the societal, scientific, and technical background underlying the subsequent research studies, including an overview of the CA problem for redundant control effectors. The following four chapters present, in this order: an evaluation of the mission performance of a staggered box-wing aircraft model designed for commercial transonic operations; a comparison of different CA methods on the design of an optimum control surface layout for a box-wing aircraft, with control surface both fore and aft the aircraft center of gravity; a trim problem formulation which employs forces and moments due to the aircraft control surfaces as decision variables, to maximize control authority, minimize aerodynamic drag or obtain a prescribed pitch angle; a CA-based formulation aimed at altering the characteristics of the transient response of an aircraft by exploiting the properties of the CCoP.
The conclusive chapter presents a comprehensive, top-level recap of the main aspects and topics covered within the dissertation. It reflects on the classic meaning of DLC, and what it means to achieve it with redundant control surfaces that are not expressly dedicated to it. With some considerations on the needs of aviation market, it speculates on the practical role of unconventional aircraft configurations in the near future. Lastly, it provides suggestions for improvements and future research studies.
Prediction of unsteady nonlinear aerodynamic loads using deep convolutional neural networks
Investigating the dynamic response of agile combat aircraft
Unfortunately, conventional modelling tools either lack the required fidelity or they are too expensive. Traditional, highly-efficient approaches are not suitable for modelling nonlinear flow phenomena. Concurrently, high fidelity Computational Fluid Dynamics (CFD) simulations are computationally demanding and therefore impractical in many cases. To enhance aircraft design, it is desirable to obtain models joining the best of these two worlds. A common approach is to distill high fidelity methods into Reduced-Order Models (ROMs) that can accurately approximate unsteady aerodynamics at orders of magnitudes lower costs than CFD. Relevant literature offers many different ROM techniques for varying purposes. Nonetheless, constructing such models is still challenging and currently there is no generally agreed method.
In the current thesis a ROM technique that may be applicable to wider ranges of problems and simpler to construct is sought. The objective is to obtain a model that can promote aircraft control design, performance assessment and structural analysis throughout dynamic maneuvers over complete flight envelopes. The thesis proposes a novel approach utilizing modern, deep convolutional neural networks (CNNs). The devised model consists of three main components. First it incorporates a geometry description constituted by coordinates of an aircraft CFD surface grid. Second, a primary encoding-decoding CNN predicts pressure distribution at the grid points of the geometry. The final and third part of the model is an auxiliary encoding CNN deriving integral aerodynamic loads corresponding to the pressure field predictions of the primary network. The model evaluates and produces instantaneous values. Given a maneuver, it proceeds in timesteps. The predictions of the separate instances are computed directly without the need of subiterations (as it would be the case for CFD simulations).
As a proof of concept, the model is applied to symmetric motions in the vertical plane at fixed Mach number and altitude. The subject of the investigations is the MULDICON configuration of the 251 th Science and Technology Organization work-group of NATO. To fully exploit the advantages of reduced-order modelling, flow characteristics are inferred from a single excitation following an efficient system identification technique using Schroeder sweeps as input signals. The performance of the model is assessed by numerous test cases performed in CFD. First, steady conditions of varying incidence angles are investigated. Second, harmonic pitch and plunge oscillations around different angles of attack at different amplitudes and frequencies are considered. Third, additional test cases of a linear pitch up-down -- and a climbing maneuver are studied.
Considering computational efficiency, the results show robust model performance. GPU-accelerated CNN calculations are conducted roughly 5000 times faster than CFD simulations. The primary network can accurately resolve the pressure distributions over large portions of the geometry. Lower surface predictions are very accurate. However, among certain conditions discrepancies are observable on the upper surface towards the wingtips. Still, the secondary network can predict corresponding aerodynamic forces accurately. In contrast, its moment predictions are sensitive to errors in pressure distributions. Consequently, moment predictions can largely deviate from reference data, especially when nonlinear phenomena are prominent. However, in many cases errors are attributed to insufficient regressor space coverage, i.e.\ certain input combinations are explored poorly by the Schroeder sweeps. Reconsidering system identification practices might mitigate those issues. Nevertheless, the thesis proves the applicability of deep CNNs to the problems at hand. Additionally, the results encourage further investigations. ...
Unfortunately, conventional modelling tools either lack the required fidelity or they are too expensive. Traditional, highly-efficient approaches are not suitable for modelling nonlinear flow phenomena. Concurrently, high fidelity Computational Fluid Dynamics (CFD) simulations are computationally demanding and therefore impractical in many cases. To enhance aircraft design, it is desirable to obtain models joining the best of these two worlds. A common approach is to distill high fidelity methods into Reduced-Order Models (ROMs) that can accurately approximate unsteady aerodynamics at orders of magnitudes lower costs than CFD. Relevant literature offers many different ROM techniques for varying purposes. Nonetheless, constructing such models is still challenging and currently there is no generally agreed method.
In the current thesis a ROM technique that may be applicable to wider ranges of problems and simpler to construct is sought. The objective is to obtain a model that can promote aircraft control design, performance assessment and structural analysis throughout dynamic maneuvers over complete flight envelopes. The thesis proposes a novel approach utilizing modern, deep convolutional neural networks (CNNs). The devised model consists of three main components. First it incorporates a geometry description constituted by coordinates of an aircraft CFD surface grid. Second, a primary encoding-decoding CNN predicts pressure distribution at the grid points of the geometry. The final and third part of the model is an auxiliary encoding CNN deriving integral aerodynamic loads corresponding to the pressure field predictions of the primary network. The model evaluates and produces instantaneous values. Given a maneuver, it proceeds in timesteps. The predictions of the separate instances are computed directly without the need of subiterations (as it would be the case for CFD simulations).
As a proof of concept, the model is applied to symmetric motions in the vertical plane at fixed Mach number and altitude. The subject of the investigations is the MULDICON configuration of the 251 th Science and Technology Organization work-group of NATO. To fully exploit the advantages of reduced-order modelling, flow characteristics are inferred from a single excitation following an efficient system identification technique using Schroeder sweeps as input signals. The performance of the model is assessed by numerous test cases performed in CFD. First, steady conditions of varying incidence angles are investigated. Second, harmonic pitch and plunge oscillations around different angles of attack at different amplitudes and frequencies are considered. Third, additional test cases of a linear pitch up-down -- and a climbing maneuver are studied.
Considering computational efficiency, the results show robust model performance. GPU-accelerated CNN calculations are conducted roughly 5000 times faster than CFD simulations. The primary network can accurately resolve the pressure distributions over large portions of the geometry. Lower surface predictions are very accurate. However, among certain conditions discrepancies are observable on the upper surface towards the wingtips. Still, the secondary network can predict corresponding aerodynamic forces accurately. In contrast, its moment predictions are sensitive to errors in pressure distributions. Consequently, moment predictions can largely deviate from reference data, especially when nonlinear phenomena are prominent. However, in many cases errors are attributed to insufficient regressor space coverage, i.e.\ certain input combinations are explored poorly by the Schroeder sweeps. Reconsidering system identification practices might mitigate those issues. Nevertheless, the thesis proves the applicability of deep CNNs to the problems at hand. Additionally, the results encourage further investigations.
Bi-Level Optimal Control Algorithm for Climate Optimized Cruise Trajector
With En-route Step Climb and Descent Flight Modes
inputs of a fixed mode sequence and, the upper level updates the mode sequence with mode insertion which lower the cost locally. The problem for trajectory optimization is formulated here as a hybrid optimal control problem with a switched system and with a variable mode sequence, where step-climb and descent modes are included in the mode sequence. Optimal Control problems for minimizing operating cost and climate cost with fictitious climate cost functions (CCF), varying with altitude, are solved to study the performance of the algorithm. The algorithm is implemented within the Trajectory Optimization Module (TOM) by building a bi-level framework. The framework was validated by solving the operating cost optimal control problem. The maximum error between the cost reduction estimated by the algorithm and the actual cost reduction was found to be less than 15%. With high probability it can be stated that the bi-level framework is able to calculate an optimal mode sequence as the framework allow for zero entry modes in the mode sequence i.e. modes of zero duration. Although, careful consideration is required while selecting a mode for insertion as the framework is highly dependent on the sequence of the set of modes.
Despite a satisfactory performance of the bi-level optimal control technique there are few challenges which limits the scope of this technique. The maximum error was found to increase for optimal control problems with AirClim CCFs. The dependence of the AirClim CCFs on position of the aircraft influences the locus of the trajectory at each flight level. Because of this the the trajectories calculated in each iteration of the framework are found to be inconsistent. A flight trajectory guided by waypoints is proposed as a solution for future studies to handle the inconsistency between trajectories. As future studies are expected to focus on finding optimal mode definitions for designing climate optimal trajectories, the bi-level optimal control algorithm can act as an intermediary tool with which the researchers can systematically investigate cost benefits along the trajectories. ...
inputs of a fixed mode sequence and, the upper level updates the mode sequence with mode insertion which lower the cost locally. The problem for trajectory optimization is formulated here as a hybrid optimal control problem with a switched system and with a variable mode sequence, where step-climb and descent modes are included in the mode sequence. Optimal Control problems for minimizing operating cost and climate cost with fictitious climate cost functions (CCF), varying with altitude, are solved to study the performance of the algorithm. The algorithm is implemented within the Trajectory Optimization Module (TOM) by building a bi-level framework. The framework was validated by solving the operating cost optimal control problem. The maximum error between the cost reduction estimated by the algorithm and the actual cost reduction was found to be less than 15%. With high probability it can be stated that the bi-level framework is able to calculate an optimal mode sequence as the framework allow for zero entry modes in the mode sequence i.e. modes of zero duration. Although, careful consideration is required while selecting a mode for insertion as the framework is highly dependent on the sequence of the set of modes.
Despite a satisfactory performance of the bi-level optimal control technique there are few challenges which limits the scope of this technique. The maximum error was found to increase for optimal control problems with AirClim CCFs. The dependence of the AirClim CCFs on position of the aircraft influences the locus of the trajectory at each flight level. Because of this the the trajectories calculated in each iteration of the framework are found to be inconsistent. A flight trajectory guided by waypoints is proposed as a solution for future studies to handle the inconsistency between trajectories. As future studies are expected to focus on finding optimal mode definitions for designing climate optimal trajectories, the bi-level optimal control algorithm can act as an intermediary tool with which the researchers can systematically investigate cost benefits along the trajectories.
Fuel Cell and Battery Hybrid System Optimization
Towards Increased Range and Endurance
Because most demonstrated applications are for fixed wing aircraft, the unmanned GeoCopter GC-201 helicopter was used for performance requirements, weight and volume analysis. The study focuses on the preliminary sizing of the powertrain and the optimization of fuel cell and mission profile variables for this vehicle. Helicopter performance modelling, fuel cell static behavior as well as a battery discharge simulation are combined with lower fidelity models for other components.
The study results in a comparison of battery-only and fuel cell-battery configurations through payload-range diagrams, allowing for a quick evaluation of application areas. These mainly show that batteries excel at high payload, low range applications whereas a fuel cell-battery combination shows clear advantages at low payload, longer range applications. Liquid hydrogen will be shown to be comparable to the current micro gas turbine powered rotorcraft, with 400 and 500 km range capabilities respectively. Range capabilities for 300 bar and 700 bar compressed gas tank storage options show 140 and 180 km, with battery-only reaching a maximum range of 80 km. ...
Because most demonstrated applications are for fixed wing aircraft, the unmanned GeoCopter GC-201 helicopter was used for performance requirements, weight and volume analysis. The study focuses on the preliminary sizing of the powertrain and the optimization of fuel cell and mission profile variables for this vehicle. Helicopter performance modelling, fuel cell static behavior as well as a battery discharge simulation are combined with lower fidelity models for other components.
The study results in a comparison of battery-only and fuel cell-battery configurations through payload-range diagrams, allowing for a quick evaluation of application areas. These mainly show that batteries excel at high payload, low range applications whereas a fuel cell-battery combination shows clear advantages at low payload, longer range applications. Liquid hydrogen will be shown to be comparable to the current micro gas turbine powered rotorcraft, with 400 and 500 km range capabilities respectively. Range capabilities for 300 bar and 700 bar compressed gas tank storage options show 140 and 180 km, with battery-only reaching a maximum range of 80 km.
In this study, a method to assess the safety of deployment of a deployable morphing UAV is constructed. To do this, an aircraft test case is taken and a corresponding model of the aircraft is made using the Multibody dynamics approach. This model is then verified and validated by two different methods. First, a comparison of the stability derivatives of the created model and an off-the-shelf aerodynamic solver is performed. Secondly, the response of the created model is compared with actual flight test data, where the test case aircraft performs a maneuver. For both validation methods used in this study, the created model is able to resemble the output from the off-the-shelf aerodynamic solver and the flight test data. The validated model is then used as to test the method developed in this study.
The method developed starts with the definition of a safe deployment of a deployable morphing aircraft, where three different safety concerns are considered. The definition of a safe deployment also helps in deriving different categories of deployment which includes safe and various unsafe deployment depending on what causes the deployment to be unsafe. This method is tested on two different deployment scenarios.
By using the method developed in this study, safety deployment spaces are constructed from the range of input parameters determined for the two different scenarios. It is revealed from this safety deployment space what combination of input parameters is favorable for a safe deployment, and what causes the different unsafe deployments. Unsafe deployments are also categorized to understand which of the safety concern causes the deployment to be unsafe. ...
In this study, a method to assess the safety of deployment of a deployable morphing UAV is constructed. To do this, an aircraft test case is taken and a corresponding model of the aircraft is made using the Multibody dynamics approach. This model is then verified and validated by two different methods. First, a comparison of the stability derivatives of the created model and an off-the-shelf aerodynamic solver is performed. Secondly, the response of the created model is compared with actual flight test data, where the test case aircraft performs a maneuver. For both validation methods used in this study, the created model is able to resemble the output from the off-the-shelf aerodynamic solver and the flight test data. The validated model is then used as to test the method developed in this study.
The method developed starts with the definition of a safe deployment of a deployable morphing aircraft, where three different safety concerns are considered. The definition of a safe deployment also helps in deriving different categories of deployment which includes safe and various unsafe deployment depending on what causes the deployment to be unsafe. This method is tested on two different deployment scenarios.
By using the method developed in this study, safety deployment spaces are constructed from the range of input parameters determined for the two different scenarios. It is revealed from this safety deployment space what combination of input parameters is favorable for a safe deployment, and what causes the different unsafe deployments. Unsafe deployments are also categorized to understand which of the safety concern causes the deployment to be unsafe.
The NCADE is designed to disable its target by means of kinetic penetration, meaning that there is no explosive warhead present. The missile is derived from the AIM120D AMRAAM, with a similar outer shape and suspension points. The NCADE consists of two stages, where the first stage is equipped with a solid booster for a fast acceleration. Control deflections are provided with aerodynamic surfaces. The second stage, also called Kill Vehicle (KV), is equipped with an IR sensor to determine the location of the target. Some sensor inaccuracy is present due to the amount of pixels used in the sensor. Control inputs on the second stage are performed using monopropellant pulses. Both control inputs and thrust of the KV use monopropellant from the same source, meaning that when the monopropellant tank is depleted, both control deflections and thrust cannot be delivered. To calculate different trajectories of the NCADE, the equations of motion are set up, where the NCADE is modelled as a 3 degrees of freedom point mass. Aerodynamic coefficients are obtained using software applying empirical methods, for which an extended database of projectiles is available. Verification of the equations is performed using a validated generic missile model, made by TNO using Simulink.Â
The calculation of the guidance relies on a location of the target in the future. Therefore, a trajectory prediction must be performed, for which the states of the BM must be determined. There are however only position measurements of the BM available, from which a more extended set of states of the BM must be derived. This is performed using an Extended Kalman Filter (EKF), which was developed during an earlier study. The filter initiates with a guess of the states of the BM, and continuously updates those as new readings of the BM become available. Using the Kalman states, a trajectory prediction is performed. The Kalman states require a certain tracking period to converge to the correct values, to be able to calculate usable trajectory predictions. The quality of the tracking prediction is quantified by a score, which is forwarded to the guidance algorithm to be able to take the significant uncertainties in the trajectory prediction into account. The certainty score improves when the tracking duration increases and when the trajectory prediction is nearby in the future. The certainty results are forwarded to the guidance algorithm by means of coefficients of a polynomial.
Due to the complexity of the control system of the NCADE and the uncertain target trajectory, trajectory optimisation is applied in the guidance algorithm. Trajectory optimisation aims to decrease the defined performance index, which is in this case the divert cone minus the uncertainty ellipse of the trajectory prediction, to maximise the probability for interception. The divert cone of the NCADE is a volume which the missile is able to reach on a certain time, given its states and reserve fuel. The divert cone is calculated using a separate shooting optimisation algorithm, which maximises the distance in three ENU frame directions. To maximise the probability of interception, a shooting method is applied, which uses candidate solutions in the form of functions describing the control input, to calculate the performance index. Using constraints, the missile is directed towards an interception point. Constraints are also applied to bound the magnitude of the controls, and at the trajectory itself to remain physical feasible.
To investigate the behaviour of the guidance algorithm, simulations of interceptions of the NCADE have been performed on a modelled Scud BM, using a range of launch locations and tracking settings. The optimum results are presented in control deflection functions of the NCADE, which achieve the flight with the minimised performance index. When only the tracking uncertainty is minimised, flight time is minimised, as the prediction becomes less reliable when a longer trajectory prediction is performed. When only the size of the divert cone is to be maximised, the propellant of the sustainer, used for control and propulsion, is saved to increase the divert cone. Because of this, the altitude of the flight is increased, and $t_{f}$ must become larger, because less monopropellant is applied to increase the velocity at the beginning of the sustain phase. The optimum solution is a compromise between the divert cone size and time to flight. As the duration of the tracking time increases, the target trajectory prediction becomes more reliable, so the maximisation of the divert cone becomes more prominent. However, this results in the maximum range to decrease, since there is less time for interception, and the altitude of the target has increased. When the launch location is positioned further from the target, the reduction of time to flight becomes more prominent and the divert cone decreases. In conclusion, the optimisation routine performs the compromise between the amount of reserve propellant available, and the uncertainty of the trajectory prediction. ...
The NCADE is designed to disable its target by means of kinetic penetration, meaning that there is no explosive warhead present. The missile is derived from the AIM120D AMRAAM, with a similar outer shape and suspension points. The NCADE consists of two stages, where the first stage is equipped with a solid booster for a fast acceleration. Control deflections are provided with aerodynamic surfaces. The second stage, also called Kill Vehicle (KV), is equipped with an IR sensor to determine the location of the target. Some sensor inaccuracy is present due to the amount of pixels used in the sensor. Control inputs on the second stage are performed using monopropellant pulses. Both control inputs and thrust of the KV use monopropellant from the same source, meaning that when the monopropellant tank is depleted, both control deflections and thrust cannot be delivered. To calculate different trajectories of the NCADE, the equations of motion are set up, where the NCADE is modelled as a 3 degrees of freedom point mass. Aerodynamic coefficients are obtained using software applying empirical methods, for which an extended database of projectiles is available. Verification of the equations is performed using a validated generic missile model, made by TNO using Simulink.Â
The calculation of the guidance relies on a location of the target in the future. Therefore, a trajectory prediction must be performed, for which the states of the BM must be determined. There are however only position measurements of the BM available, from which a more extended set of states of the BM must be derived. This is performed using an Extended Kalman Filter (EKF), which was developed during an earlier study. The filter initiates with a guess of the states of the BM, and continuously updates those as new readings of the BM become available. Using the Kalman states, a trajectory prediction is performed. The Kalman states require a certain tracking period to converge to the correct values, to be able to calculate usable trajectory predictions. The quality of the tracking prediction is quantified by a score, which is forwarded to the guidance algorithm to be able to take the significant uncertainties in the trajectory prediction into account. The certainty score improves when the tracking duration increases and when the trajectory prediction is nearby in the future. The certainty results are forwarded to the guidance algorithm by means of coefficients of a polynomial.
Due to the complexity of the control system of the NCADE and the uncertain target trajectory, trajectory optimisation is applied in the guidance algorithm. Trajectory optimisation aims to decrease the defined performance index, which is in this case the divert cone minus the uncertainty ellipse of the trajectory prediction, to maximise the probability for interception. The divert cone of the NCADE is a volume which the missile is able to reach on a certain time, given its states and reserve fuel. The divert cone is calculated using a separate shooting optimisation algorithm, which maximises the distance in three ENU frame directions. To maximise the probability of interception, a shooting method is applied, which uses candidate solutions in the form of functions describing the control input, to calculate the performance index. Using constraints, the missile is directed towards an interception point. Constraints are also applied to bound the magnitude of the controls, and at the trajectory itself to remain physical feasible.
To investigate the behaviour of the guidance algorithm, simulations of interceptions of the NCADE have been performed on a modelled Scud BM, using a range of launch locations and tracking settings. The optimum results are presented in control deflection functions of the NCADE, which achieve the flight with the minimised performance index. When only the tracking uncertainty is minimised, flight time is minimised, as the prediction becomes less reliable when a longer trajectory prediction is performed. When only the size of the divert cone is to be maximised, the propellant of the sustainer, used for control and propulsion, is saved to increase the divert cone. Because of this, the altitude of the flight is increased, and $t_{f}$ must become larger, because less monopropellant is applied to increase the velocity at the beginning of the sustain phase. The optimum solution is a compromise between the divert cone size and time to flight. As the duration of the tracking time increases, the target trajectory prediction becomes more reliable, so the maximisation of the divert cone becomes more prominent. However, this results in the maximum range to decrease, since there is less time for interception, and the altitude of the target has increased. When the launch location is positioned further from the target, the reduction of time to flight becomes more prominent and the divert cone decreases. In conclusion, the optimisation routine performs the compromise between the amount of reserve propellant available, and the uncertainty of the trajectory prediction.Â
The effect of shifting the Centre of Gravity on fuel burn during long haul flights
A study on the practical implementation of Centre of Gravity shifting
The CFD solver TAU developed at the German Aerospace Center (DLR) includes among its features an actuator disk module which transmits to the flow field prescribed time-averaged load distributions both in axial and tangential directions by means of pressure and tangential velocity jumps. The computation of these loads can be achieved by using the Blade Element Analysis Tool (BEAT), a developed rotor code based on the blade element theory. In addition, since it is considered that changes in blade motion about the feathering bearing and flapping hinge induce variations in the aerodynamic loads acting on the blades and vice versa, the loads need to be calculated under trimmed or equilibrium conditions.
The coupling between BEAT and the TAU actuator disk is defined in a way that the velocity captured at the grid points of the actuator disk surface after each simulation performed in TAU is transferred to BEAT, which computes an updated aerodynamic load distribution. The performance of this approach is tested for an isolated rotor configuration in hovering and forward flight conditions. In hovering flight, the convergence of the CFD flow simulations towards the steady state solution is not satisfactory due to the stiffness of the compressible Navier-Stokes equations at low Mach numbers. Furthermore, reverse flow regions are determined by TAU at the inner and outer boundaries of the actuator disk. The recirculation flow entails high gradients in angle of attack between neighboring blade sectional elements, which yields to the unstable formation of new reverse flow regions. Nevertheless, in forward flight conditions the performance of the flow solver is robust and convergent solutions can be obtained. Moreover, as the flight speed is increased, the shed vorticity is displaced more quickly outside the rotor disk and, hence, its associated effects on the performance of the rotor are diminished.
The accuracy of the coupling approach is validated by comparing the computed results with those measured in a wind tunnel test campaign. The found differences in pitch control angles are assigned to the fact that the blade elastic deformations are neglected in the developed method. This statement constitutes the baseline to be developed for future work.
Finally, the reduction in computation time required by the coupling approach with respect to other more accurate methods enhances the idea of further developments. Therefore, the developed method can be regarded as a suitable strategy to tackle the problem in forward flight conditions in cases where high fidelity results are not needed, such as in the preliminary design stages. ...
The CFD solver TAU developed at the German Aerospace Center (DLR) includes among its features an actuator disk module which transmits to the flow field prescribed time-averaged load distributions both in axial and tangential directions by means of pressure and tangential velocity jumps. The computation of these loads can be achieved by using the Blade Element Analysis Tool (BEAT), a developed rotor code based on the blade element theory. In addition, since it is considered that changes in blade motion about the feathering bearing and flapping hinge induce variations in the aerodynamic loads acting on the blades and vice versa, the loads need to be calculated under trimmed or equilibrium conditions.
The coupling between BEAT and the TAU actuator disk is defined in a way that the velocity captured at the grid points of the actuator disk surface after each simulation performed in TAU is transferred to BEAT, which computes an updated aerodynamic load distribution. The performance of this approach is tested for an isolated rotor configuration in hovering and forward flight conditions. In hovering flight, the convergence of the CFD flow simulations towards the steady state solution is not satisfactory due to the stiffness of the compressible Navier-Stokes equations at low Mach numbers. Furthermore, reverse flow regions are determined by TAU at the inner and outer boundaries of the actuator disk. The recirculation flow entails high gradients in angle of attack between neighboring blade sectional elements, which yields to the unstable formation of new reverse flow regions. Nevertheless, in forward flight conditions the performance of the flow solver is robust and convergent solutions can be obtained. Moreover, as the flight speed is increased, the shed vorticity is displaced more quickly outside the rotor disk and, hence, its associated effects on the performance of the rotor are diminished.
The accuracy of the coupling approach is validated by comparing the computed results with those measured in a wind tunnel test campaign. The found differences in pitch control angles are assigned to the fact that the blade elastic deformations are neglected in the developed method. This statement constitutes the baseline to be developed for future work.
Finally, the reduction in computation time required by the coupling approach with respect to other more accurate methods enhances the idea of further developments. Therefore, the developed method can be regarded as a suitable strategy to tackle the problem in forward flight conditions in cases where high fidelity results are not needed, such as in the preliminary design stages.
This thesis investigates structural load alleviation in the tail rotor drive train of the UH-60 Black Hawk. The Black Hawk provides a compelling case for load alleviation research because of its ever growing operational weight and resulting increase of drive train load levels. Furthermore, the lifetime of the UH-60 is to be extended so that it will fly for many years to come. Current research and applications of rotorcraft structural load alleviation focus on the main rotor but less attention is given to tail rotor drive train components. This project seeks to address this knowledge gap by investigating manoeuvres that result in critical dynamic loads in the UH-60 tail rotor drive train. A survey of pertinent literature and interviews with helicopter pilots indicate that pedal inputs for left-hand turns in hover lead to high dynamic loads in the UH-60 tail rotor drive train.
A flight simulation model is constructed that offers the novel capability to predict dynamic loads in tail rotor drive shafts. This model consists of an available high fidelity engine model and existing rotor models coupled by a multi body dynamics tail rotor drive train model with properties that are based on component measurements and CAD drawings. Experiments are conducted to determine the relation between manoeuvre aggressiveness and dynamic loads in tail rotor drive shafts. Based on the results a manoeuvre load alleviation control strategy is devised to reduce dynamic loads while ensuring applicable Level 1 handling quality requirements. Application of this control strategy will decrease dynamic loads during left-hand yaw manoeuvres in hover. Furthermore, the results highlight what reduction in loads can be achieved for varying levels of manoeuvre aggressiveness. These findings may aid in the design of flight control systems that incorporate tail rotor drive train load alleviation objectives. ...
This thesis investigates structural load alleviation in the tail rotor drive train of the UH-60 Black Hawk. The Black Hawk provides a compelling case for load alleviation research because of its ever growing operational weight and resulting increase of drive train load levels. Furthermore, the lifetime of the UH-60 is to be extended so that it will fly for many years to come. Current research and applications of rotorcraft structural load alleviation focus on the main rotor but less attention is given to tail rotor drive train components. This project seeks to address this knowledge gap by investigating manoeuvres that result in critical dynamic loads in the UH-60 tail rotor drive train. A survey of pertinent literature and interviews with helicopter pilots indicate that pedal inputs for left-hand turns in hover lead to high dynamic loads in the UH-60 tail rotor drive train.
A flight simulation model is constructed that offers the novel capability to predict dynamic loads in tail rotor drive shafts. This model consists of an available high fidelity engine model and existing rotor models coupled by a multi body dynamics tail rotor drive train model with properties that are based on component measurements and CAD drawings. Experiments are conducted to determine the relation between manoeuvre aggressiveness and dynamic loads in tail rotor drive shafts. Based on the results a manoeuvre load alleviation control strategy is devised to reduce dynamic loads while ensuring applicable Level 1 handling quality requirements. Application of this control strategy will decrease dynamic loads during left-hand yaw manoeuvres in hover. Furthermore, the results highlight what reduction in loads can be achieved for varying levels of manoeuvre aggressiveness. These findings may aid in the design of flight control systems that incorporate tail rotor drive train load alleviation objectives.
Low Reynolds number Performance of contra-rotating Coaxial Rotors
Evaluated for use by Unmanned Aerial Vehicles
The new developed model was tested on the full-scale Kamov 32 helicopter as well as two small Unmanned Aerial Vehicles. These are the commercial available Walkera Lama and the Guardian Angle, which was developed by undergraduate students during a design synthesis exercise. The results show a successful implementation of the calculation methods, with some interesting insight in the limits imposed by them. ...
The new developed model was tested on the full-scale Kamov 32 helicopter as well as two small Unmanned Aerial Vehicles. These are the commercial available Walkera Lama and the Guardian Angle, which was developed by undergraduate students during a design synthesis exercise. The results show a successful implementation of the calculation methods, with some interesting insight in the limits imposed by them.
Reduced-order modelling for prediction of aircraft flight dynamics
Based on indicial step response functions investigating agile aircraft undergoing rapid manoeuvres
The method investigated is based on indicial step response functions, which are samples in the form of unsteady aerodynamic flow behaviour functions of the full-order model. The idea is that once these samples are known, any flight manoeuvre can be analysed within minutes. Research found in literature has assessed some of the capabilities and limitations of this method, but not yet applied this to flight dynamics prediction. The research described within this report will address this gap by using two test cases. The first testcase is used to assess the assumptions made in literature, on aerodynamics loads modelling, by applying the method on a two-dimensional airfoil in subsonic flow conditions. It was found that the indicial step response functions are indeed representing the full-order model, thereby taking into account unsteady flow behaviour in aerodynamic loads prediction. In longitudinal motions, the angle of attack and pitch rate effect need to be taken into account to predict lift, drag and pitching moments. Multiple frequencies of the same manoeuvre can be analysed within minutes once the samples are calculated. Results show that the accuracy of the predictions becomes a trade-off issue between samples calculated and accuracy required. The second testcase is used to apply the indicial response functions to flight dynamics prediction of an agile
unmanned bomber aircraft undergoing fast manoeuvres. A longitudinal-directional climbing manoeuvre was calculated by developing a flight dynamics model based on stability derivatives. The flow behaviour encountered during this manoeuvre was analysed to include highly unsteady and non-linear phenomena (e.g. vortices and flow separation) at higher angles of attack. By comparing the results of themethod under investigation to the full-order solutions, it was shown that aerodynamic flight dynamics predictions were accurate in capturing unsteady behaviour and weak non-linear flow behaviour. However, the samples proved to be inaccurate in representing behaviour in highly non-linear regions. Concluding, this means that indicial step response functions provide more accurate flight dynamics predictions than conventional stability derivatives in representing unsteady flow behaviour. The accuracy of the predictions are highly dependent on the samples chosen. Several samples suffice to predict the unsteady behaviour for linear and weak non-linear flow regions of the flightmanoeuvre. If surrogate modelling is applied, the method can become more computational efficient than conducting multiple full-order time-marching numerical calculations. It is recommended that more research is performed on indicial step response functions
in capturing highly non-linear flow behaviour, as the research showed that the size of the samples affects the flow behaviour representation. ...
The method investigated is based on indicial step response functions, which are samples in the form of unsteady aerodynamic flow behaviour functions of the full-order model. The idea is that once these samples are known, any flight manoeuvre can be analysed within minutes. Research found in literature has assessed some of the capabilities and limitations of this method, but not yet applied this to flight dynamics prediction. The research described within this report will address this gap by using two test cases. The first testcase is used to assess the assumptions made in literature, on aerodynamics loads modelling, by applying the method on a two-dimensional airfoil in subsonic flow conditions. It was found that the indicial step response functions are indeed representing the full-order model, thereby taking into account unsteady flow behaviour in aerodynamic loads prediction. In longitudinal motions, the angle of attack and pitch rate effect need to be taken into account to predict lift, drag and pitching moments. Multiple frequencies of the same manoeuvre can be analysed within minutes once the samples are calculated. Results show that the accuracy of the predictions becomes a trade-off issue between samples calculated and accuracy required. The second testcase is used to apply the indicial response functions to flight dynamics prediction of an agile
unmanned bomber aircraft undergoing fast manoeuvres. A longitudinal-directional climbing manoeuvre was calculated by developing a flight dynamics model based on stability derivatives. The flow behaviour encountered during this manoeuvre was analysed to include highly unsteady and non-linear phenomena (e.g. vortices and flow separation) at higher angles of attack. By comparing the results of themethod under investigation to the full-order solutions, it was shown that aerodynamic flight dynamics predictions were accurate in capturing unsteady behaviour and weak non-linear flow behaviour. However, the samples proved to be inaccurate in representing behaviour in highly non-linear regions. Concluding, this means that indicial step response functions provide more accurate flight dynamics predictions than conventional stability derivatives in representing unsteady flow behaviour. The accuracy of the predictions are highly dependent on the samples chosen. Several samples suffice to predict the unsteady behaviour for linear and weak non-linear flow regions of the flightmanoeuvre. If surrogate modelling is applied, the method can become more computational efficient than conducting multiple full-order time-marching numerical calculations. It is recommended that more research is performed on indicial step response functions
in capturing highly non-linear flow behaviour, as the research showed that the size of the samples affects the flow behaviour representation.
This thesis presents a combination of physics based and knowledge based design methodologies to size the wing subsystems and position them in the airframe. Consequently, the methods are integrated into the conceptual aircraft design process to enable multidisciplinary design with supporting domains. The methods are aimed to aid the design of conventional systems architectures and More Electric Aircraft (MEA) systems architectures as well. With these methodologies, the Systems Model Generator (SMG) application is developed in Python to facilitate semi-automatic wing subsystems sizing and orientation in the airframe based on top-level aircraft requirements, initial aircraft design parameters and system specific parameters. The subsystem models generated with the proposed methodology for short-medium range civil transport aircraft are verified and validated as well. Knowledge based systems and subsystems selection are implemented to facilitate semi-automated systems, subsystems and architecture selection, based on the aircraft configuration and systems specific requirements. Methods for automatic iterative fuel tanks sizing and intersection detection are implemented to further reduce the overall design time and make the tool more suitable for integrated sizing.
With the multidisciplinary design framework, the conceptual parametric models, volume, mass, power consumption and position of the subsystems in the airframe are generated and propagated in the conceptual aircraft design stage; thus bridging the conceptual and the preliminary design stages. In the proposed framework, the domains of aircraft design generation, systems selection and sizing, subsystems selection and sizing, engine sizing and mission simulation are considered for the multidisciplinary design process. The domains are integrated with the DLR CPACS-RCE framework.
A case study to demonstrate the process of integrated parametric subsystems sizing of the aircraft, with the proposed framework is presented. The aim of this case study is to assess the influence of the MEA systems architecture relative to the conventional systems architecture for a short-medium range transport aircraft, similar to the Airbus A320-200. In this case study, the quantitative influence of the subsystems' parameters on the aircraft design and performance parameters is determined and analysed. The subsystems' parameters constitute the mass, power consumption, volume and location of the subsystems in the airframe and the aircraft design parameters constitute the aircraft masses such as the overall empty mass and the fuel mass for the mission. The generation and propagation of the design and performance parameters of the aircraft through each domain of the framework are presented and analysed as well with the case study. In this case study, it is observed that the MEA systems architecture results in a lower mission fuel mass relative to the conventional systems architecture by nearly 2.3\%. Furthermore, these results are compared with literature and observed to be in the similar range of 2-7\%. Thus, the validated aircraft design framework presented in this thesis enables to substantially increases and propagate the design knowledge of aircraft systems, in the early design stages. ...
This thesis presents a combination of physics based and knowledge based design methodologies to size the wing subsystems and position them in the airframe. Consequently, the methods are integrated into the conceptual aircraft design process to enable multidisciplinary design with supporting domains. The methods are aimed to aid the design of conventional systems architectures and More Electric Aircraft (MEA) systems architectures as well. With these methodologies, the Systems Model Generator (SMG) application is developed in Python to facilitate semi-automatic wing subsystems sizing and orientation in the airframe based on top-level aircraft requirements, initial aircraft design parameters and system specific parameters. The subsystem models generated with the proposed methodology for short-medium range civil transport aircraft are verified and validated as well. Knowledge based systems and subsystems selection are implemented to facilitate semi-automated systems, subsystems and architecture selection, based on the aircraft configuration and systems specific requirements. Methods for automatic iterative fuel tanks sizing and intersection detection are implemented to further reduce the overall design time and make the tool more suitable for integrated sizing.
With the multidisciplinary design framework, the conceptual parametric models, volume, mass, power consumption and position of the subsystems in the airframe are generated and propagated in the conceptual aircraft design stage; thus bridging the conceptual and the preliminary design stages. In the proposed framework, the domains of aircraft design generation, systems selection and sizing, subsystems selection and sizing, engine sizing and mission simulation are considered for the multidisciplinary design process. The domains are integrated with the DLR CPACS-RCE framework.
A case study to demonstrate the process of integrated parametric subsystems sizing of the aircraft, with the proposed framework is presented. The aim of this case study is to assess the influence of the MEA systems architecture relative to the conventional systems architecture for a short-medium range transport aircraft, similar to the Airbus A320-200. In this case study, the quantitative influence of the subsystems' parameters on the aircraft design and performance parameters is determined and analysed. The subsystems' parameters constitute the mass, power consumption, volume and location of the subsystems in the airframe and the aircraft design parameters constitute the aircraft masses such as the overall empty mass and the fuel mass for the mission. The generation and propagation of the design and performance parameters of the aircraft through each domain of the framework are presented and analysed as well with the case study. In this case study, it is observed that the MEA systems architecture results in a lower mission fuel mass relative to the conventional systems architecture by nearly 2.3\%. Furthermore, these results are compared with literature and observed to be in the similar range of 2-7\%. Thus, the validated aircraft design framework presented in this thesis enables to substantially increases and propagate the design knowledge of aircraft systems, in the early design stages.
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enthusiast. Inspired by his own vision of improved powered parachutes he built a closed-cockpit
paraplane for one person, which unfortunately never flew. ...
enthusiast. Inspired by his own vision of improved powered parachutes he built a closed-cockpit
paraplane for one person, which unfortunately never flew.