Optimal Cross-Wind Towing and Power Generation with Tethered Kites

Non-powered flight vehicles such as kites can provide a means of transmitting wind energy from higher altitudes to the ground via tethers. Although there have been many proposals for systems to extract wind energy from higher altitudes, this paper focuses on the use of a light lifting body at the end of a tether to generate useful power. Two major configurations are studied: 1) the kite is used to tow a ground vehicle in the cross-wind direction, 2) the kite is flown to generate power using a ground generator. In both cases, the useful work done by the kite is transmitted to the ground through the tether. Both applications require automatic control of the kite. A simplified system model is used to study the nature of the optimal trajectories of the system for different wind speeds. Numerical results illustrate that optimal power generation requires complex three-dimensional kite trajectories, whereas cross-wind towing requires much simpler trajectories. A feedback tracking controller is demonstrated for tracking the kite trajectories in the presence of unsteady winds

Characterizing the evolution of genetic variance using genetic covariance tensors

Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance–covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations