A fuzzy and random moment-based arbitrary polynomial chaos method for response analysis of composite structural–acoustic system with multi-scale uncertainties

2021 ◽  
Vol 177 ◽  
pp. 107913
Author(s):  
Wenqing Zhu ◽  
Yingbin Hu ◽  
Ning Chen ◽  
Jian Liu ◽  
Michael Beer
Keyword(s):  
Polynomial Chaos ◽  
Response Analysis ◽  
Acoustic System ◽  
Multi Scale ◽  
Arbitrary Polynomial ◽  
Random Moment

Moment-Based Hybrid Polynomial Chaos Method for Interval and Random Uncertain Analysis of Periodical Composite Structural-Acoustic System with Multi-Scale Parameters

2020 ◽  
pp. 2050041
Author(s):  
Ning Chen ◽  
Jiaojiao Chen ◽  
Shengwen Yin
Keyword(s):  
Polynomial Chaos ◽  
Random Variable ◽  
Acoustic System ◽  
Passenger Compartment ◽  
Scale Parameters ◽  
Multi Scale ◽  
Arbitrary Polynomial ◽  
Random Moment ◽  
The Moment ◽  
Probability Density Function Pdf

An interval and random moment-based arbitrary polynomial chaos method (IRMAPCM) is proposed in this paper for the analysis of periodical composite structural-acoustic systems with multi-scale uncertain-but-bounded parameters. In IRMAPCM, the response of structural-acoustic system is approximated as moment-based arbitrary polynomial chaos (maPC) expansion. IRMAPCM can construct the polynomial basis according to the moment of the random variable without knowing the Probability Density Function (PDF), which can avoid the errors introduced by estimating the PDF. Numerical examples of a hexahedral box and an automobile passenger compartment are given to investigate the effectiveness of IRMAPCM for the prediction of the sound pressure response of structural-acoustic systems.

scholarly journals A Novel Sparse Polynomial Expansion Method for Interval and Random Response Analysis of Uncertain Vibro-Acoustic System

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Shengwen Yin ◽  
Xiaohan Zhu ◽  
Xiang Liu
Keyword(s):  
Expansion Coefficient ◽  
Polynomial Chaos ◽  
Sequential Sampling ◽  
Expansion Method ◽  
Sparse Grids ◽  
Polynomial Expansion ◽  
Acoustic System ◽  
Arbitrary Polynomial ◽  
Polynomial Expansion Method ◽  
Random Uncertainties

For the vibro-acoustic system with interval and random uncertainties, polynomial chaos expansions have received broad and persistent attention. Nevertheless, the cost of the computation process increases sharply with the increasing number of uncertain parameters. This study presents a novel interval and random polynomial expansion method, called Sparse Grids’ Sequential Sampling-based Interval and Random Arbitrary Polynomial Chaos (SGS-IRAPC) method, to obtain the response of a vibro-acoustic system with interval and random uncertainties. The proposed SGS-IRAPC retains the accuracy and the simplicity of the traditional arbitrary polynomial chaos method, while avoiding its inefficiency. In the SGS-IRAPC, the response is approximated by the moment-based arbitrary polynomial chaos expansion and the expansion coefficient is determined by the least squares approximation method. A new sparse sampling scheme combined the sparse grids’ scheme with the sequential sampling scheme which is employed to generate the sampling points used to calculate the expansion coefficient to decrease the computational cost. The efficiency of the proposed surrogate method is demonstrated using a typical mathematical problem and an engineering application.

Uncertainty Quantification and Missing Data for Turbomachinery With Probabilistic Equivalence and Arbitrary Polynomial Chaos, Applied to Scroll Compressors

2021 ◽  
Author(s):  
Nick Pepper ◽  
Francesco Montomoli ◽  
Sanjiv Sharma ◽  
Francesco Giacomel ◽  
Michele Pinelli ◽  
...  
Keyword(s):  
Missing Data ◽  
Uncertainty Quantification ◽  
Polynomial Chaos ◽  
Arbitrary Polynomial

scholarly journals An Efficient Polynomial Chaos Method for Stiffness Analysis of Air Spring Considering Uncertainties

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Feng Kong ◽  
Penghao Si ◽  
Shengwen Yin
Keyword(s):  
Orthogonal Polynomial ◽  
Polynomial Chaos ◽  
Random Variables ◽  
Expansion Method ◽  
Polynomial Expansion ◽  
Response Analysis ◽  
Air Spring ◽  
Stiffness Analysis ◽  
Orthogonal Polynomial Expansion ◽  
Sparse Quadrature

Traditional methods for stiffness analysis of the air spring are based on deterministic assumption that the parameters are fixed. However, uncertainties have widely existed, and the mechanic property of the air spring is very sensitive to these uncertainties. To model the uncertainties in the air spring, the interval/random variables models are introduced. For response analysis of the interval/random variables models of the air spring system, a new unified orthogonal polynomial expansion method, named as sparse quadrature-based interval and random moment arbitrary polynomial chaos method (SQ-IRMAPC), is proposed. In SQ-IRMAPC, the response of the acoustic system related to both interval and random variables is approximated by the moment-based arbitrary orthogonal polynomial expansion. To efficiently calculate the coefficient of the interval and random orthogonal polynomial expansion, the sparse quadrature is introduced. The proposed SQ-IRMAPC was employed to analyze the mechanic performance of an air spring with interval and/or random variables, and its effectiveness has been demonstrated by fully comparing it with the most recently proposed orthogonal polynomial-based interval and random analysis method.

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