In the present work, the authors examine two computational approaches that can be used to study flexible flapping systems. For illustration, a fully coupled interaction of a fluid system with a flapping profile performing harmonic flapping kinematics is studied. In one approach, the fluid model is based on the Navier-Stokes equations for viscous incompressible flow, where all spatio-temporal scales are directly resolved by means of Direct Numerical Simulations (DNS). In the other approach, the fluid model is an inviscid, potential flow model, based on the unsteady vortex lattice method (UVLM). In the UVLM model, the focus is on vortex structures and the fluid dynamics is treated as a vortex kinematics problem, whereas with the DNS model, one is able to form a more detailed picture of the flapping physics. The UVLM based approach, although coarse from a modeling standpoint, is computationally inexpensive compared to the DNS based approach. This comparative study is motivated by the hypothesis that flapping related phenomena are primarily determined by vortex interactions and viscous effects play a secondary role, which could mean that a UVLM based approach could be suitable for design purposes and/or used as a predictive tool. In most of the cases studied, the UVLM based approach produces a good approximation. Apart from aerodynamic load comparisons, features of the system dynamics generated by using the two computational approaches are also compared. The authors also discuss limitations of both approaches.

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A computational co-simulation framework for flying robots with flexible wings is presented. The authors combine a nonlinear aerodynamic model based on an extended version of the unsteady vortex-lattice method with a nonlinear structural model based on a segregated formulation of Lagrange's equations obtained with the Floating Frame of Reference formalism. The structural model construction allows for hybrid combinations of different models typically used with multibody systems such as models based on rigid-body dynamics, assumed-modes techniques, and finite-element methods. The aerodynamic model includes a simulation of leading-edge separation for large angles of attack. The governing differentialalgebraic equations are solved simultaneously and interactively to obtain the structural response and the flow in the time domain. The integration is based on the fourth-order predictor-corrector method of Hamming with a procedure to stabilize the iteration. The findings are found to capture known nonlinear behavior of flapping-wing systems. The developed framework should be relevant for conducting aeroelastic studies on a wide variety of air vehicle systems.

Converting flow-induced vibrations into electricity for low-power generation has received growing attention over the past few years. Aeroelastic phenomena, good candidates to yield high energy performance in renewable wind energy harvesting (EH) systems, can play a pivotal role in providing sufficient power for extended operation with little or no battery replacement. In this paper, a numerical model and a co-simulation approach have been developed to study a new EH device for power generation. We investigate the problem focusing on a weakly aerodynamically coupled flutter-based EH system. It consists of two flexible wings anchored by cantilevered beams with attached piezoelectric layers, undergoing nonlinear coupled bending–torsion limit cycle oscillations. Besides the development of individual EH devices, further issues are posed when considering multiple objects for realizing a network of devices and magnifying the extracted power due to nonlinear synergies and constructive interferences. This work investigates the effect of various external conditions and physical parameters on the performance of the piezoaeroelastic array of devices. From the viewpoint of applications, we are most concerned about whether an EH can generate sufficient power under a variable excitation. The results of this study can be used for the design and integration of low-energy wind generation technologies into buildings, bridges, and built-in sensor networks in aircraft structures.