Dimension-adaptive algorithm-based PCE for models with many model parameters. Issue 2 (3rd September 2019)

• Record Type: Journal Article
• Authors: Li, Yangtian; Li, Haibin; Wei, Guangmei
• Is Part Of: Engineering computations. Volume 37:Issue 2(2020)
• Page Start: 522
• Page End: 545
• Publication Date: 2019-09-03
• Subjects: Non-uniform grid -- Polynomial chaos expansion -- Dimension-adaptive algorithm -- Model with many model parameters -- Uncertainty quantification (UQ) -- Sparse polynomial chaos expansion; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-12-2018-0595
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: To present the models with many model parameters by polynomial chaos expansion (PCE), and improve the accuracy, this paper aims to present dimension-adaptive algorithm-based PCE technique and verify the feasibility of the proposed method through taking solid rocket motor ignition under low temperature as an example. Design/methodology/approach: The main approaches of this work are as follows: presenting a two-step dimension-adaptive algorithm; through computing the PCE coefficients using dimension-adaptive algorithm, improving the accuracy of PCE surrogate model obtained; and applying the proposed method to uncertainty quantification (UQ) of solid rocket motor ignition under low temperature to verify the feasibility of the proposed method. Findings: The result indicates that by means of comparing with some conventional non-invasive method, the proposed method is able to raise the computational accuracy significantly on condition of meeting the efficiency requirement. Originality/value: This paper proposes an approach in which the optimal non-uniform grid that can avoid the issue of overfitting or underfitting is obtained.