A Two-Phase Monte Carlo Simulation/Non-Intrusive Polynomial Chaos (MSC/NIPC) Method for Quantification of Margins and Mixed Uncertainties (QMMU) in Flutter Analysis

Jing Yang,Baoqiang Zhang,Zhengwen Hu

doi:10.1109/access.2020.3005289

Jing Yang, Baoqiang Zhang + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.3005289

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Abstract

A two-phase Monte Carlo Simulation/Non-intrusive Polynomial Chaos (MCS/NIPC) method for quantification of margins and mixed uncertainties (aleatory and epistemic uncertainties) is proposed in this paper for the flutter speed boundary analysis. Compared with the traditional MCS/MCS method which needs lots of numerical simulations, the MCS/NIPC method can reduce the computational cost without losing accuracy due to the use of point collocation non-intrusive polynomial chaos in the inner loop. Based on the results of uncertainty quantification, a novel practical quantification of margins and mixed uncertainties (QMMU) framework is proposed considering both aleatory and epistemic uncertainties such as the parametric uncertainties in complicated models. A two-dimensional airfoil and a three-dimensional benchmark wing, the AGARD 445.6 wing, are both employed to illustrate the practical application of the proposed methods for flutter speed computation in the presence of mixed uncertainties arising from the material properties and flight conditions. Within the analysis, aleatory and mixed uncertainty quantification are conducted to prove the effectiveness and efficiency of the MCS/NIPC method. Then the QMMU metrics are accomplished for the flutter speed boundary analysis of the two airfoil models. The results demonstrate the potential of the proposed QMMU framework to analyze the stability of engineering systems.

Highlights

Flutter is the dynamic instability where the structure extracts kinetic energy from air and this energy cannot be dissipated by structural damping
Flutter analysis is conducted by using the p-k method and the flutter speed Vf calculated from the deterministic system is 39.48 m/s
The two parameters are modeled as independent Gaussian random variables, and the variations of the random variables are determined by a coefficient of variation (COV) of 5%

Summary

Introduction

Flutter is the dynamic instability where the structure extracts kinetic energy from air and this energy cannot be dissipated by structural damping. Another motivation for this paper is to construct a novel implementation framework of quantification of margins and mixed uncertainties (QMMU) for flutter speed analysis based on the results obtained by the MCS/NIPC method.

Results

Conclusion