1,419 research outputs found

    Elasticity, fluctuations and vortex pinning in ferromagnetic superconductors: A "columnar elastic glass"

    Get PDF
    We study the elasticity, fluctuations and pinning of a putative spontaneous vortex solid in ferromagnetic superconductors. Using a rigorous thermodynamic argument, we show that in the idealized case of vanishing crystalline pinning anisotropy the long-wavelength tilt modulus of such a vortex solid vanishes identically, as guaranteed by the underlying rotational invariance. The vanishing of the tilt modulus means that, to lowest order, the associated tension elasticity is replaced by the softer, curvature elasticity. The effect of this is to make the spontaneous vortex solid qualitatively more susceptible to the disordering effects of thermal fluctuations and random pinning. We study these effects, taking into account the nonlinear elasticity, that, in three dimensions, is important at sufficiently long length scales, and showing that a ``columnar elastic glass'' phase of vortices results. This phase is controlled by a previously unstudied zero-temperature fixed point and it is characterized by elastic moduli that have universal strong wave-vector dependence out to arbitrarily long length scales, leading to non-Hookean elasticity. We argue that, although translationally disordered for weak disorder, the columnar elastic glass is stable against the proliferation of dislocations and is therefore a topologically ordered {\em elastic} glass. As a result, the phenomenology of the spontaneous vortex state of isotropic magnetic superconductors differs qualitatively from a conventional, external-field-induced mixed state. For example, for weak external fields HH, the magnetic induction scales {\em universally} like B(H)B(0)+cHαB(H)\sim B(0)+ c H^{\alpha}, with α0.72\alpha\approx 0.72.Comment: Minor editorial changes, version to be published in PRB, 39 pages, 7 figure

    Data driven low-bandwidth intelligent control of a jet engine combustor

    Get PDF
    This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system\u27s operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a good or bad operating mode. A data-driven predictor is also designed that monitors the combustion process in real time and provides a prediction of what operating mode the flame will be in for the next measurement. A path planning algorithm is then discussed for planning an input trajectory from the current operating condition to the desired operating condition that avoids regions of instability or blow-out in the input space. An adaptive layer is incorporated into the path planning algorithm to ensure that the path planner can update its trajectory when new information about the operating space becomes available
    corecore