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Approximation and Uncertainty Quantification of Systems with Arbitrary Parameter Distributions Using Weighted Leja Interpolation

Loukrezis, Dimitrios ; De Gersem, Herbert (2021)
Approximation and Uncertainty Quantification of Systems with Arbitrary Parameter Distributions Using Weighted Leja Interpolation.
In: Algorithms, 2020, 13 (3)
doi: 10.26083/tuprints-00019220
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Item Type: Article
Type of entry: Secondary publication
Title: Approximation and Uncertainty Quantification of Systems with Arbitrary Parameter Distributions Using Weighted Leja Interpolation
Language: English
Date: 2021
Year of primary publication: 2020
Publisher: MDPI
Journal or Publication Title: Algorithms
Volume of the journal: 13
Issue Number: 3
Collation: 20 Seiten
DOI: 10.26083/tuprints-00019220
Corresponding Links:
Origin: Secondary publication via sponsored Golden Open Access
Abstract:

Approximation and uncertainty quantification methods based on Lagrange interpolation are typically abandoned in cases where the probability distributions of one or more system parameters are not normal, uniform, or closely related distributions, due to the computational issues that arise when one wishes to define interpolation nodes for general distributions. This paper examines the use of the recently introduced weighted Leja nodes for that purpose. Weighted Leja interpolation rules are presented, along with a dimension-adaptive sparse interpolation algorithm, to be employed in the case of high-dimensional input uncertainty. The performance and reliability of the suggested approach is verified by four numerical experiments, where the respective models feature extreme value and truncated normal parameter distributions. Furthermore, the suggested approach is compared with a well-established polynomial chaos method and found to be either comparable or superior in terms of approximation and statistics estimation accuracy

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-192205
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields
Date Deposited: 28 Jul 2021 08:11
Last Modified: 28 Jul 2021 08:11
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/19220
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