A NOVEL THREE DEGREE-OF-FREEDOMS OSCILLATION SYSTEM OF INSECT FLAPPING WINGS

We propose an oscillation system to replicate the dynamic behavior of flapping wings, inspired by insect flight muscles. In particular, we study the flight of the fruit fly Drosophila virilis . We model the wing as a rigid body with three degree-of-freedom, described by three Euler angles: the stroke angle, the rotation angle and the deviation angle. Insect flight muscles are separated into two types: power muscles and control muscles. One actuator and one torsional spring at the stroke angle act as the power muscles. Two torsional springs at the rotation angle and the deviation angle mimic the control muscles. A dynamic model, using a blade-element model and a quasi-steady model to calculate aerodynamic forces and moments, is set up for analysis of the system\u27s performance. Using non-dimensional analysis, we are able to identify the dynamic behavior of the system through four coefficients: stroke stiffness coefficient, rotation stiffness coefficient, deviation stiffness coefficient and input torque coefficient. We use the dynamic model to explore a large coefficients space of the oscillation system. We find that tuning deviation stiffness coefficient and rotation stiffness coefficient generates four different types of wing trajectories. Among them, the one with a high deviation stiffness coefficient and a mediate rotation stiffness coefficient produces high lift and high power loading. Its wing trajectory is quite similar to the wing trajectory in actual insects. Furthermore, a hybrid optimization algorithm (a genetic algorithm and a Nelder-Mead simplex algorithm) is implemented to find the optimal stiffness coefficients. Through these coefficients, the system minimizes power loading while still providing enough lift to maintain a time-averaged constant altitude over one stroke cycle. The results of this optimization indicate that the flapping wing with nonzero deviation achieves a better aerodynamic performance than the wing with zero deviation. The oscillatory property of this system does not only explain how insects use flight muscles to tune wing kinematics, but it also allows for design simplifications of the wing driving mechanism of flapping micro air vehicles

Principle Of Bio-Inspired Insect Wing Rotational Hinge Design

A principle for designing and fabricating bio-inspired miniature artificial insect flapping wing using flexure rotational hinge design is presented. A systematic approach of selecting rotational hinge stiffness value is proposed. Based on the understanding of flapping wing aerodynamics, a dynamic simulation is constructed using the established quasi-steady model and the wing design. Simulations were performed to gain insight on how different parameters affect the wing rotational response. Based on system resonance a model to predict the optimal rotational hinge stiffness based on given wing parameter and flapping wing kinematic is proposed. By varying different wing parameters, the proposed method is shown to be applicable to a wide range of wing designs with different sizes and shapes. With the selected hinge stiffness value, aspects of the rotational joint design is discussed and an integrated wing-hinge structure design using laminated carbon fiber and polymer film is presented. Manufacturing process of such composite structure is developed to achieve high accuracy and repeatability. The yielded hinge stiffness is verified by measurements. To validate the proposed model, flapping wing experiments were conducted. A flapping actuation set up is built using DC motor and a controller is implemented on a microcontroller to track desired wing stroke kinematic. Wing stroke and rotation kinematic were extracted using a high speed camera and the lift generation is evaluated. A total of 49 flapping experiments were presented, experimental data shows good correlation with the model\u27s prediction. With the wing rotational hinge stiffness designed so that the rotational resonant frequency is twice as the stroke frequency, the resulting wing rotation generates near optimal lift. With further simulation, the proposed model shows low sensitivity to wing parameter variation. As a result, giving a design parameter of a flapping wing robot platform, the proposed principle can predict the rotational hinge stiffness that leads to near optimal wing rotation. Further iteration can be done around the selected value and achieve the optimal lift generation

DESIGN AND CONTROL OF A HUMMINGBIRD-SIZE FLAPPING WING MICRO AERIAL VEHICLE

Flying animals with flapping wings may best exemplify the astonishing ability of natural selection on design optimization. They evince extraordinary prowess to control their flight, while demonstrating rich repertoire of agile maneuvers. They remain surprisingly stable during hover and can make sharp turns in a split second. Characterized by high-frequency flapping wing motion, unsteady aerodynamics, and the ability to hover and perform fast maneuvers, insect-like flapping flight presents an extraordinary aerial locomotion strategy perfected at small size scales. Flapping Wing Micro Aerial Vehicles (FWMAVs) hold great promise in bridging the performance gap between engineered flying vehicles and their natural counterparts. They are perfect candidates for potential applications such as fast response robots in search and rescue, environmental friendly agents in precision agriculture, surveillance and intelligence gathering MAVs, and miniature nodes in sensor networks

A Robust Data-Driven Model for Flapping Aerodynamics under different hovering kinematics

Flapping Wing Micro Air Vehicles (FWMAV) are highly manoeuvrable, bio-inspired drones that can assist in surveys and rescue missions. Flapping wings generate various unsteady lift enhancement mechanisms challenging the derivation of reduced models to predict instantaneous aerodynamic performance. In this work, we propose a robust CFD data-driven, quasi-steady (QS) Reduced Order Model (ROM) to predict the lift and drag coefficients within a flapping cycle. The model is derived for a rigid ellipsoid wing with different parameterized kinematics in hovering conditions. The proposed ROM is built via a two-stage regression. The first stage, defined as `in-cycle' (IC), computes the parameters of a regression linking the aerodynamic coefficients to the instantaneous wing state. The second stage, `out-of-cycle' (OOC), links the IC weights to the flapping features that define the flapping motion. The training and test dataset were generated via high-fidelity simulations using the overset method, spanning a wide range of Reynolds numbers and flapping kinematics. The two-stage regressor combines Ridge regression and Gaussian Process (GP) regression to provide estimates of the model uncertainties. The proposed ROM shows accurate aerodynamic predictions for widely varying kinematics. The model performs best for smooth kinematics that generate a stable Leading Edge Vortex (LEV). Remarkably accurate predictions are also observed in dynamic scenarios where the LEV is partially shed, the non-circulatory forces are considerable, and the wing encounters its own wake.Comment: submitted to Physics of Fluid

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999

These proceedings represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft

Aeronautical Engineering: A Continuing Bibliography with Indexes (supplement 194)

This bibliography lists 369 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1985

Aeronautical Engineering: A continuing bibliography with indexes (supplement 205)

This bibliography lists 517 reports, articles and other documents introduced into the NASA scientific and technical information system in September 1986

NASA Aeroelasticity Handbook Volume 2: Design Guides Part 2

The NASA Aeroelasticity Handbook comprises a database (in three formats) of NACA and NASA aeroelasticity flutter data through 1998 and a collection of aeroelasticity design guides. The Microsoft Access format provides the capability to search for specific data, retrieve it, and present it in a tabular or graphical form unique to the application. The full-text NACA and NASA documents from which the data originated are provided in portable document format (PDF), and these are hyperlinked to their respective data records. This provides full access to all available information from the data source. Two other electronic formats, one delimited by commas and the other by spaces, are provided for use with other software capable of reading text files. To the best of the author s knowledge, this database represents the most extensive collection of NACA and NASA flutter data in electronic form compiled to date by NASA. Volume 2 of the handbook contains a convenient collection of aeroelastic design guides covering fixed wings, turbomachinery, propellers and rotors, panels, and model scaling. This handbook provides an interactive database and design guides for use in the preliminary aeroelastic design of aerospace systems and can also be used in validating or calibrating flutter-prediction software

The Third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization

The third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization was held on 24-26 Sept. 1990. Sessions were on the following topics: dynamics and controls; multilevel optimization; sensitivity analysis; aerodynamic design software systems; optimization theory; analysis and design; shape optimization; vehicle components; structural optimization; aeroelasticity; artificial intelligence; multidisciplinary optimization; and composites