ABSTRACT: Flapping flight in birds presents a rich interplay between biomechanics, aerodynamics, and control, offering insights into both individual flight stability and collective energy-saving strategies. This presentation explores the dynamics of flapping flight through a combination of stability analysis and high-fidelity wake modeling. A reduced-order biomechanical model is used to identify periodic flight regimes and assess their stability via Floquet theory, revealing how tail configuration influences both energy consumption and the robustness of flight. Complementing this, a simulation framework coupling morphing wing models with vorticity-based flow solvers captures the complex wake structures generated by flapping wings and their exploitation in formation flight. The results demonstrate how birds can achieve significant energy savings by synchronizing their wingbeats and positioning themselves strategically within the leader’s wake. Building on these insights, ongoing work investigates simplified models for disturbance rejection in gliding flight, focusing on the synergy between the instantaneous compliance-based response of the musculo-skeletal system and the delayed active reflex-based responses.

BIOSKETCH: Prof. Philippe Chatelain is a mechanical engineer (UCLouvain, 1999) with advanced degrees in Aeronautics and Applied Mathematics from Caltech (M.S. 2000, Ph.D. 2005). He co-leads the Turbulence and Vorticity (T&V) group at UCLouvain’s Institute of Mechanics, Materials and Civil Engineering (iMMC), focusing on vorticity-dominated incompressible flows, turbulence modeling, and flow-structure interaction. Since joining in 2009, he has expanded the group’s expertise in high-performance computing and large-eddy simulations, contributing to studies of wakes behind wind turbines, aircraft, and rotorcraft. His work bridges fluid mechanics with robotics, bio-locomotion, and control, including collaborations that led to experimental platforms such as a robotic eel and a drone airship. His research spans computational advances in vortex and particle methods, immersed interface techniques, and stochastic simulation algorithms, with a strong emphasis on multi-physics systems and flow-mediated interactions. He has developed strategies for flow sensing and exploitation using reduced-order models, data assimilation, and machine learning, and led major research efforts including an ERC Consolidator Grant on AI-driven optimization of distributed systems and a Concerted Research Action on the reverse-engineering of bird flight.