The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs m...The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.展开更多
In this letter, a piezoaeroelastic energy harvester based on an airfoil with double plunge degrees of freedom is proposed to additionally take advantage of the vibrational energy of the airfoil pitch motion. An analyt...In this letter, a piezoaeroelastic energy harvester based on an airfoil with double plunge degrees of freedom is proposed to additionally take advantage of the vibrational energy of the airfoil pitch motion. An analytical model of the proposed energy harvesting system is built and compared with an equivalent model using the well-explored pitch-plunge configuration. The dynamic response and average power output of the harvester are numerically studied as the flow velocity exceeds the cut-in speed (flutter speed). It is found that the harvester with double-plunge configuration generates 4%-10% more power with varying flow velocities while reducing 670 of the cut-in speed than its counterpart.展开更多
Analytical indicial aerodynamic functions are calculated for several trapezoidal wings in subsonic flow, with a Mach number 0.3 Ma 0.7. The formulation herein proposed extends wellknown aerodynamic theories, which are...Analytical indicial aerodynamic functions are calculated for several trapezoidal wings in subsonic flow, with a Mach number 0.3 Ma 0.7. The formulation herein proposed extends wellknown aerodynamic theories, which are limited to thin aerofoils in incompressible flow, to generic trapezoidal wing planforms. Firstly, a thorough study is executed to assess the accuracy and limitation of analytical predictions, using unsteady results from two state-of-the-art computational fluid dynamics solvers as cross-validated benchmarks. Indicial functions are calculated for a step change in the angle of attack and for a sharp-edge gust, each for four wing configurations and three Mach numbers. Then, analytical and computational indicial responses are used to predict dynamic derivatives and the maximum lift coefficient following an encounter with a one-minus-cosine gust. It is found that the analytical results are in excellent agreement with the computational results for all test cases. In particular, the deviation of the analytical results from the computational results is within the scatter or uncertainty in the data arising from using two computational fluid dynamics solvers. This indicates the usefulness of the developed analytical theories.展开更多
Morphing aircraft can meet requirements of multi-mission during the whole flight due to changing the aerodynamic shape,so it is necessary to study itsmorphing rules along the trajectory.However,trajectory planning con...Morphing aircraft can meet requirements of multi-mission during the whole flight due to changing the aerodynamic shape,so it is necessary to study itsmorphing rules along the trajectory.However,trajectory planning considering morphing variables requires a huge number of expensive CFD computations due to the morphing in view of aerodynamic performance.Under the given missions and trajectory,to alleviate computational cost and improve trajectory-planning efficiency formorphing aircraft,an offline optimizationmethod is proposed based onMulti-Fidelity Kriging(MFK)modeling.The angle of attack,Mach number,sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the MFK models,in which many inviscid aerodynamic solutions are used as low-fidelity data,while the less high-fidelity data are obtained by solving viscous flow.Then the built MFK models of the lift,drag and pressure centre at the different angles of attack andMach numbers are used to predict the aerodynamic performance of the morphing aircraft,which keeps the optimal sweep angle and axial position of the wing during trajectory planning.Hence,themorphing rules can be correspondingly acquired along the trajectory,aswell as keep the aircraftwith the best aerodynamic performance during thewhole task.The trajectory planning of amorphing aircraft was performed with the optimal aerodynamic performance based on the MFK models,built by only using 240 low-fidelity data and 110 high-fidelity data.The results indicate that a complex trajectory can take advantage of morphing rules in keeping good aerodynamic performance,and the proposed method is more efficient than trajectory optimization by reducing 86%of the computing time.展开更多
This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data l...This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques.The cornerstone of the approach is l_(1) regularised regression,resulting in sparselyconnected models where only the important quadratic interactions between modes are retained.The original dynamical behaviour is reproduced at low computational costs,as few quadratic interactions need to be evaluated.The approach has two key features.First,interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required.Second,the presence of a regularisation term improves the predictive performance of the original model,generally affected by noise and poor data quality.Test cases are for two-dimensional lid-driven cavity flows,at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum.It is found that:(A)the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients;this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible;(B)sparse models maintain a good temporal stability for predictions.The methodology is ready for more complex applications without modifications of the underlying theory,and the integration into a cyberphysical model is feasible.展开更多
文摘The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.
基金Tsupported by the National Natural Science Foundation of China(11402014,11572023)the Royal Academy of Engineering for the project ‘‘Fast Nonlinear Aeroelastic Search for Loads Assessment’’(NCRP/1415/51)
文摘In this letter, a piezoaeroelastic energy harvester based on an airfoil with double plunge degrees of freedom is proposed to additionally take advantage of the vibrational energy of the airfoil pitch motion. An analytical model of the proposed energy harvesting system is built and compared with an equivalent model using the well-explored pitch-plunge configuration. The dynamic response and average power output of the harvester are numerically studied as the flow velocity exceeds the cut-in speed (flutter speed). It is found that the harvester with double-plunge configuration generates 4%-10% more power with varying flow velocities while reducing 670 of the cut-in speed than its counterpart.
基金the Royal Academy of Engineering for funding this researchthe use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work
文摘Analytical indicial aerodynamic functions are calculated for several trapezoidal wings in subsonic flow, with a Mach number 0.3 Ma 0.7. The formulation herein proposed extends wellknown aerodynamic theories, which are limited to thin aerofoils in incompressible flow, to generic trapezoidal wing planforms. Firstly, a thorough study is executed to assess the accuracy and limitation of analytical predictions, using unsteady results from two state-of-the-art computational fluid dynamics solvers as cross-validated benchmarks. Indicial functions are calculated for a step change in the angle of attack and for a sharp-edge gust, each for four wing configurations and three Mach numbers. Then, analytical and computational indicial responses are used to predict dynamic derivatives and the maximum lift coefficient following an encounter with a one-minus-cosine gust. It is found that the analytical results are in excellent agreement with the computational results for all test cases. In particular, the deviation of the analytical results from the computational results is within the scatter or uncertainty in the data arising from using two computational fluid dynamics solvers. This indicates the usefulness of the developed analytical theories.
基金This study was co-supported by the National Defense Fundamental Research Funds of China(No.JCKY2016204B102 and JCKY2016208C001).
文摘Morphing aircraft can meet requirements of multi-mission during the whole flight due to changing the aerodynamic shape,so it is necessary to study itsmorphing rules along the trajectory.However,trajectory planning considering morphing variables requires a huge number of expensive CFD computations due to the morphing in view of aerodynamic performance.Under the given missions and trajectory,to alleviate computational cost and improve trajectory-planning efficiency formorphing aircraft,an offline optimizationmethod is proposed based onMulti-Fidelity Kriging(MFK)modeling.The angle of attack,Mach number,sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the MFK models,in which many inviscid aerodynamic solutions are used as low-fidelity data,while the less high-fidelity data are obtained by solving viscous flow.Then the built MFK models of the lift,drag and pressure centre at the different angles of attack andMach numbers are used to predict the aerodynamic performance of the morphing aircraft,which keeps the optimal sweep angle and axial position of the wing during trajectory planning.Hence,themorphing rules can be correspondingly acquired along the trajectory,aswell as keep the aircraftwith the best aerodynamic performance during thewhole task.The trajectory planning of amorphing aircraft was performed with the optimal aerodynamic performance based on the MFK models,built by only using 240 low-fidelity data and 110 high-fidelity data.The results indicate that a complex trajectory can take advantage of morphing rules in keeping good aerodynamic performance,and the proposed method is more efficient than trajectory optimization by reducing 86%of the computing time.
文摘This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system.Herein,the generation of an accurate reduced order model of twodimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques.The cornerstone of the approach is l_(1) regularised regression,resulting in sparselyconnected models where only the important quadratic interactions between modes are retained.The original dynamical behaviour is reproduced at low computational costs,as few quadratic interactions need to be evaluated.The approach has two key features.First,interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required.Second,the presence of a regularisation term improves the predictive performance of the original model,generally affected by noise and poor data quality.Test cases are for two-dimensional lid-driven cavity flows,at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum.It is found that:(A)the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients;this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible;(B)sparse models maintain a good temporal stability for predictions.The methodology is ready for more complex applications without modifications of the underlying theory,and the integration into a cyberphysical model is feasible.