Stable multivariate rational interpolation for parameter-dependent aerospace models

A multivariate, robust, rational interpolation method for propagating uncertainties in several dimensions is presented. The algorithm for selecting numerator and denominator polynomial orders is based on recent work that uses a singular value decomposition approach. In this paper we extend this algorithm to higher dimensions and demonstrate its efficacy in terms of convergence and accuracy, both as a method for response suface generation and interpolation. To obtain stable approximants for continuous functions, we use an L2 error norm indicator to rank optimal numerator and denominator solutions. For discontinous functions, a second criterion setting an upper limit on the approximant value is employed. Analytical examples demonstrate that, for the same stencil, rational methods can yield more rapid convergence compared to pseudospectral or collocation approaches for certain problems. © 2012 AIAA.

Rigorous finite-time guarantees for optimization on continuous domains by simulated annealing

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.

Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.

Liquid crystal based continuous phase retarder: From optically neutral to a quarter waveplate in 200 microseconds

Liquid crystal variable phase retarders have been incorporated into prototype devices for optical communications system applications, both as endless polarization controllers 1,2,3, and as holographic beam steerers 4. Nematic liquid crystals allow continuous control of the degree of retardation induced at relatively slow switching speeds, while ferroelectric liquid crystal based devices allow fast (sub millisecond) switching, but only between two bistable states. The flexoelectro-optic effect 5,6 in short-pitch chiral nematic liquid crystals allows both fast switching of the optic axis and continuous, electric field dependent control of the degree of rotation of the optic axis. A novel geometry for the flexoelectro-optic effect is presented here, in which the helical axis of the chiral nematic is perpendicular to the cell walls (grandjean texture) and the electric field is applied in the plane of the cell. This facilitates deflection of the optic axis of the uniaxial negatively birefringent material from lying along the direction of propagation to having some component in the polarization plane of the light. The device is therefore optically neutral at zero field for telecommunications wavelengths (1550nm), and allows a continuously variable degree of phase excursion to be induced, up to 2π/3 radians achieved so far in a 40μm thick cell. The retardation has been shown both to appear, on application of the field, and disappear on removal, at speeds of 100-500 μs. The direction of deflection of the optic axis is also dependent on the direction of the field, allowing the possibility, in a converging electrode "cartwheel cell", of endless rotation of the liquid crystal waveplate at a higher rate than achievable through dielectric coupling to plain nematic materials.

Continuous spectrum growth and modal instability in swirling duct flow

We present results on the stability of compressible inviscid swirling flows in an annular duct. Such flows are present in aeroengines, for example in the by-pass duct, and there are also similar flows in many aeroacoustic or aeronautical applications. The linearised Euler equations have a ('critical layer') singularity associated with pure convection of the unsteady disturbance by the mean flow, and we focus our attention on this region of the spectrum. By considering the critical layer singularity, we identify the continuous spectrum of the problem and describe how it contributes to the unsteady field. We find a very generic family of instability modes near to the continuous spectrum, whose eigenvalue wavenumbers form an infinite set and accumulate to a point in the complex plane. We study this accumulation process asymptotically, and find conditions on the flow to support such instabilities. It is also found that the continuous spectrum can cause a new type of instability, leading to algebraic growth with an exponent determined by the mean flow, given in the analysis. The exponent of algebraic growth can be arbitrarily large. Numerical demonstrations of the continuous spectrum instability, and also the modal instabilities are presented.