Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data

2021 ◽  
Author(s):  
Huan Zhao ◽  
Zhenghong Gao ◽  
Fang Xu ◽  
Lu Xia
Keyword(s):  
Polynomial Chaos ◽  
Global Approximation ◽  
Sparse Polynomial ◽  
Kriging Metamodeling

Uncertainty Study of Periodic-Grating Wideband Filters With Sparse Polynomial-Chaos Expansions

2019 ◽  
Vol 31 (18) ◽  
pp. 1499-1502
Author(s):  
A. D. Papadopoulos ◽  
T. T. Zygiridis ◽  
E. N. Glytsis ◽  
N. V. Kantartzis ◽  
C. S. Antonopoulos
Keyword(s):  
Polynomial Chaos ◽  
Sparse Polynomial ◽  
Periodic Grating ◽  
Polynomial Chaos Expansions ◽  
Wideband Filters

An adaptive sparse polynomial-chaos technique based on anisotropic indices

2020 ◽  
Vol 39 (3) ◽  
pp. 691-707
Author(s):  
Christos Salis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros Zygiridis
Keyword(s):  
Polynomial Chaos ◽  
Computational Cost ◽  
Uncertainty Assessment ◽  
Design Parameters ◽  
Test Problems ◽  
Content Type ◽  
Sparse Polynomial ◽  
Index Sets ◽  
The Mean ◽  
Expansion Coefficients

Purpose The fabrication of electromagnetic (EM) components may induce randomness in several design parameters. In such cases, an uncertainty assessment is of high importance, as simulating the performance of those devices via deterministic approaches may lead to a misinterpretation of the extracted outcomes. This paper aims to present a novel heuristic for the sparse representation of the polynomial chaos (PC) expansion of the output of interest, aiming at calculating the involved coefficients with a small computational cost. Design/methodology/approach This paper presents a novel heuristic that aims to develop a sparse PC technique based on anisotropic index sets. Specifically, this study’s approach generates those indices by using the mean elementary effect of each input. Accurate outcomes are extracted in low computational times, by constructing design of experiments (DoE) which satisfy the D-optimality criterion. Findings The method proposed in this study is tested on three test problems; the first one involves a transmission line that exhibits several random dielectrics, while the second and the third cases examine the effects of various random design parameters to the transmission coefficient of microwave filters. Comparisons with the Monte Carlo technique and other PC approaches prove that accurate outcomes are obtained in a smaller computational cost, thus the efficiency of the PC scheme is enhanced. Originality/value This paper introduces a new sparse PC technique based on anisotropic indices. The proposed method manages to accurately extract the expansion coefficients by locating D-optimal DoE.

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