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Proceedings ArticleDOI

Dynamic stall utter analysis with uncertainties using Multi-Element Probabilistic Collocation

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TLDR
In this paper, the effect of uncertainty present in external torque on the bifurcation behavior of a dynamic stall utter problem is analyzed using the Multi-Element Probabilistic Collocation method.
Abstract
In this paper the eect of uncertainty present in external torque on the bifurcation behavior of a dynamic stall utter problem is analyzed using the Multi-Element Probabilistic Collocation method. A Multi-Element Probabilistic Collocation approach is followed since the bifurcation in the response causes oscillations for the ordinary Probabilistic Collocation method. Two elements are used, with one element covering the damped response and the other the period-one oscillations. This is only possible if the elements are separated near the bifurcation point, of which the location is in general not known in advance. A search algorithm is used to nd a coarse estimate of the bifurcation point to divide the domain into two elements. The stochastic bifurcation plot and the probability distribution of the bifurcation point show a large variation in the output due to the uncertain external torque.

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Citations
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Calculation of Gauss quadrature rules.

TL;DR: Two algorithms for generating the Gaussian quadrature rule defined by the weight function when: a) the three term recurrence relation is known for the orthogonal polynomials generated by $\omega$(t), and b) the moments of the weightfunction are known or can be calculated.
Proceedings ArticleDOI

Airfoil Analysis with Uncertain Geometry using the Probabilistic Collocation method

G.J.A. Loeven, +1 more
TL;DR: In this paper, uncertainties in the geometry of an airfoil are treated as parametric uncertainties, which are efficiently propagated using the Probabilistic Collocation method, and the uncertainties are propagated through the system separately to see the effect of the parameter on the solution and simultaneously to investigate combined effects.
Journal ArticleDOI

Probabilistic collocation used in a Two-Step approached for efficient uncertainty quantification in computational fluid dynamics

TL;DR: In this paper, a two-step approach is presented for uncertainty quantification for expensive problems with multiple uncertain parameters, where the first step consists of a sensitivity analysis to identify the most important parameters of the problem.
Journal ArticleDOI

Analysis of a Nonlinear Aeroelastic System with Parametric Uncertainties Using Polynomial Chaos Expansion

TL;DR: In this article, a nonlinear aeroelastic system with parametric uncertainties is considered, and a projection-based nonintrusive polynomial chaos approach is shown to be much faster than its classical Galerkin method based counterpart.
Proceedings ArticleDOI

Probabilistic Aeroelastic Analysis and Its Implications on Flutter Margin Requirements

TL;DR: In this paper, a series of Monte Carlo Simulations (MCS) were performed on a two-dimensi-onal flutter model and a generic aircraft wing to investigate the effect of uncertainty on the existing flutter avoidance specification requirements.
References
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Journal ArticleDOI

High-Order Collocation Methods for Differential Equations with Random Inputs

TL;DR: A high-order stochastic collocation approach is proposed, which takes advantage of an assumption of smoothness of the solution in random space to achieve fast convergence and requires only repetitive runs of an existing deterministic solver, similar to Monte Carlo methods.
Journal ArticleDOI

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

TL;DR: A rigorous convergence analysis is provided and exponential convergence of the “probability error” with respect to the number of Gauss points in each direction in the probability space is demonstrated, under some regularity assumptions on the random input data.
Journal ArticleDOI

Calculation of Gauss quadrature rules

TL;DR: In this paper, two algorithms for generating the Gaussian quadrature rule defined by the weight function are presented, assuming that the three term recurrence relation is known for the orthogonal polynomials generated by the weighted function.
Book

An introduction to the theory of aeroelasticity

TL;DR: An introduction to the theory of aeroelasticity, An Introduction to the Theory of Aero-Elasticity as mentioned in this paper, An introduction to aero-elasticities,
Journal ArticleDOI

A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data

TL;DR: This work demonstrates algebraic convergence with respect to the total number of collocation points and quantifies the effect of the dimension of the problem (number of input random variables) in the final estimates, indicating for which problems the sparse grid stochastic collocation method is more efficient than Monte Carlo.
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