scholarly journals Uncertainty Quantification of Subcritical Nonlinear Aeroelastic System Using Integrated Interpolation Method and Polynomial Chaos Expansion

2016 ◽  
Vol 144 ◽  
pp. 982-989 ◽  
Author(s):  
M.T. Thanusha ◽  
Sunetra Sarkar
Keyword(s):  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Interpolation Method ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion ◽  
Aeroelastic System

scholarly journals Uncertainty Quantification of a Nonlinear Aeroelastic System Using Polynomial Chaos Expansion With Constant Phase Interpolation

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Ajit Desai ◽  
Jeroen A. S. Witteveen ◽  
Sunetra Sarkar
Keyword(s):  
Dynamical System ◽  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Turbine Blades ◽  
Flexible Structures ◽  
Period Doubling ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion ◽  
Aeroelastic System ◽  
Phase Interpolation

The present study focuses on the uncertainty quantification of an aeroelastic instability system. This is a classical dynamical system often used to model the flow induced oscillation of flexible structures such as turbine blades. It is relevant as a preliminary fluid-structure interaction model, successfully demonstrating the oscillation modes in blade rotor structures in attached flow conditions. The potential flow model used here is also significant because the modern turbine rotors are, in general, regulated in stall and pitch in order to avoid dynamic stall induced vibrations. Geometric nonlinearities are added to this model in order to consider the possibilities of large twisting of the blades. The resulting system shows Hopf and period-doubling bifurcations. Parametric uncertainties have been taken into account in order to consider modeling and measurement inaccuracies. A quadrature based spectral uncertainty tool called polynomial chaos expansion is used to quantify the propagation of uncertainty through the dynamical system of concern. The method is able to capture the bifurcations in the stochastic system with multiple uncertainties quite successfully. However, the periodic response realizations are prone to time degeneracy due to an increasing phase shifting between the realizations. In order to tackle the issue of degeneracy, a corrective algorithm using constant phase interpolation, which was developed earlier by one of the authors, is applied to the present aeroelastic problem. An interpolation of the oscillatory response is done at constant phases instead of constant time and that results in time independent accuracy levels.

Heat Transfer Modeling of Spent Nuclear Fuel Using Uncertainty Quantification and Polynomial Chaos Expansion

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Imane Khalil ◽  
Quinn Pratt ◽  
Harrison Schmachtenberger ◽  
Roger Ghanem
Keyword(s):  
Heat Transfer ◽  
Fuel Assembly ◽  
Uncertainty Quantification ◽  
Nuclear Fuel ◽  
Polynomial Chaos ◽  
Spent Nuclear Fuel ◽  
Polynomial Chaos Expansion ◽  
Complex Case ◽  
Chaos Expansion ◽  
Input Parameters

A novel method that incorporates uncertainty quantification (UQ) into numerical simulations of heat transfer for a 9 × 9 square array of spent nuclear fuel (SNF) assemblies in a boiling water reactor (BWR) is presented in this paper. The results predict the maximum mean temperature at the center of the 9 × 9 BWR fuel assembly to be 462 K using a range of fuel burn-up power. Current related modeling techniques used to predict the heat transfer and the maximum temperature inside SNF assemblies rely on commercial codes and address the uncertainty in the input parameters by running separate simulations for different input parameters. The utility of leveraging polynomial chaos expansion (PCE) to develop a surrogate model that permits the efficient evaluation of the distribution of temperature and heat transfer while accounting for all uncertain input parameters to the model is explored and validated for a complex case of heat transfer that could be substituted with other problems of intricacy. UQ computational methods generated results that are encompassing continuous ranges of variable parameters that also served to conduct sensitivity analysis on heat transfer simulations of SNF assemblies with respect to physically relevant parameters. A two-dimensional (2D) model is used to describe the physical processes within the fuel assembly, and a second-order PCE is used to characterize the dependence of center temperature on ten input parameters.

Uncertainty quantification and sensitivity analysis of thermoacoustic stability with non-intrusive polynomial chaos expansion

2018 ◽  
Vol 189 ◽  
pp. 300-310 ◽  
Author(s):  
Alexander Avdonin ◽  
Stefan Jaensch ◽  
Camilo F. Silva ◽  
Matic Češnovar ◽  
Wolfgang Polifke
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion
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