As largely earth-bound creatures, humans can take to the water, yet routine human-powered flight remains an elusive dream. While engineers have a well developed understanding of machine-powered flight, the realms of viscosity encountered by jets, large birds and insects differ hugely. Although viscosity effects can be disregarded on fixed wing jets, flapping birds are prey to the effects of lift, drag and turbulence, which drastically alter aerodynamic performance. Despite the apparent complexity of flapping bird flight, Geoffrey Spedding, Anders Hedenström, John McArthur and Mikael Rosén have compared the aerodynamics of birds, ranging in size from the thrush nightingale to the robin, with the forces acting on fixed wings(p. 215) and found that the birds' wakes were only slightly more complex than fixed wing wakes. The team adds that `this observation suggests that simple aerodynamic models might help to understand many features of bird flight' but warn that their results may not apply to larger birds.
Following Spedding's discussion of the aerodynamics of bird wings,Fritz-Olaf Lehmann reviews wake–wing interactions in insects to understand `how oscillating [insect] wings interact with the surrounding fluid'(p. 224). Working with large scale Plexiglas™ insect wing models immersed in mineral oil(to simulate the air viscosity experienced by an insect), Lehmann has modelled wing–airflow interactions in two and four winged insects. He explains that wing–wing and wing–wake interactions can significantly enhance lift with only minimal modifications to a wing stroke pattern,improving an insect's efficiency, and possibly contributing to the insect's flight control.
Staying with insect aerodynamics, Jane Wang discusses a theoretical study where she develops a computational model to investigate the efficiency and power output of six different hovering wing beat patterns(p. 235). Defining each wing beat in terms of four parameters Wang calculates the work each wing beat does to support a unit weight over a unit time as the parameters vary. The results are power surfaces for each wing beat pattern, revealing the most efficient combination of wing beat parameters that fall at the lowest point on the surface. While the surfaces that she generates seem to agree with recorded hovering wing beat patterns, Wang adds that for a specific wing shape, many wing beat patterns may occur close to the optimal pattern.
Taking a completely different theoretical approach, Hikaro Aono, Fuyou Liang and Hao Liu describe their ground-breaking computational fluid dynamic simulation of a hovering fruit fly(p. 239). Computationally reproducing the shape and motion of the insect's wings and body, the team simulated fluid flow patterns around the insect revealing a horseshoe-shaped vortex wrapped around the wing early in both the down- and upstrokes, which subsequently develops into a doughnut shaped ring resulting in a strong downwash jet which keeps the hovering insect aloft. According to Liu, this innovative simulation agrees well with experimental observations of hovering fruit flies.
Finally, Graham Taylor, Adrian Thomas and colleagues describe recent developments in experimental approaches in the Biomechanics of Flight in their Oxford labs. Discussing the merits and pitfalls of tethered flight analysis,the team describe a novel virtual-reality insect-flight arena that they have developed (p. 258). The arena not only simulates the insect's global view, but also stimulates all of the insect's sensory systems (including the gyroscopic halteres) by mounting the insect on a six-component force–moment balance, which moves the insect as if it were flying freely. Taylor and Thomas then go on to describe their work on free-flying birds, collecting inertial observations and combining them with photographic records of wing and tail movements during flight. Although both systems will provide state-of-the-art experimental data to produce advanced models of flight control, Taylor and Thomas add that`details of the underlying physiology remain opaque'.