Meeting Abstract
Wind interactions in urban spaces generate complex flow patterns that are difficult to predict, however these heterogeneous wind fields may offer considerable opportunities for energy harvesting for flying animals. Applying Cost of Transport (CoT) theory to flight dynamics equations for flight through a wind field indicates that with the right airspeed and trajectory adjustments it is possible to harvest energy from spatiotemporal wind gradients. We tracked 11 urban nesting lesser black-backed gulls, Larus fuscus, using GPS units over 2 years as they flew through urban environments. The loggers collected a GPS fix up to every 4 seconds along with a 1 second burst of acceleration data; allowing us to determine the gulls’ trajectories and flight modes. Our initial studies found the gulls flew at velocities predicted by CoT theory in flapping and soaring flight. Furthermore, we observed the gulls perform a soar strategy not explained by static soaring techniques and hypothesized that the gulls were taking advantage of spatiotemporal gradients to soar. We tested this hypothesis using a 4D path planner in CFD generated city wind fields. A cost function was used that combined CoT velocity optimization with a flight dynamics model which included energy expenditure estimates based on Basal Metabolic Rate ratios for flapping and soaring flight. The simulated commuting flights gave trajectories with gradient soaring flight traits which corresponded to those seen in the gull flight paths. This suggests that complex wind fields, such as those present in urban environments, could provide ample opportunities for energy harvesting, and that soaring is not just limited to more structured wind fields, such as thermals or shear layers. This offers inspiration for the development of wind-aware flight control schemes to increase the range and endurance of unmanned air vehicles.
