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Abstract

The discretization of random fields is the first and most important step in the stochastic analysis of engineering structures with spatially dependent random parameters. The essential step of discretization is solving the Fredholm integral equation to obtain the eigenvalues and eigenfunctions of the covariance functions of the random fields. The collocation method, which has fewer integral operations, is more efficient in accomplishing the task than the time-consuming Galerkin method, and it is more suitable for engineering applications with complex geometries and a large number of elements. With the help of isogeometric analysis that preserves accurate geometry in analysis, the isogeometric collocation method can efficiently achieve the results with sufficient accuracy. An adaptive moment abscissa is proposed to calculate the coordinates of the collocation points to further improve the accuracy of the collocation method. The adaptive moment abscissae led to more accurate results than the classical Greville abscissae when using the moment parameter optimized with intelligent algorithms. Numerical and engineering examples illustrate the advantages of the proposed isogeometric collocation method based on the adaptive moment abscissae over existing methods in terms of accuracy and efficiency.

Details

1009240
Title
Isogeometric Collocation Method for Random Field Discretization Based on Adaptive Moment Abscissae
Author
Liu, Zhenyu 1 ; Peng, Deshang 2 ; Yang, Minglong 3 ; Cheng, Jin 2   VIAFID ORCID Logo  ; Qiu, Chan 1 ; Tan, Jianrong 2 

 Zhejiang University, State Key Laboratory of CAD & CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
 Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
 Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); Jiangnan Institute of Technology, Jiangnan Shipyard (Group) Company Limited, Shanghai, China (GRID:grid.13402.34) 
Volume
38
Issue
1
Pages
120
Publication year
2025
Publication date
Dec 2025
Publisher
Springer Nature B.V.
Place of publication
Heidelberg
Country of publication
Netherlands
ISSN
10009345
e-ISSN
21928258
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-07-16
Milestone dates
2025-06-16 (Registration); 2023-12-15 (Received); 2025-06-12 (Accepted); 2025-06-05 (Rev-Recd)
Publication history
 
 
   First posting date
16 Jul 2025
ProQuest document ID
3230590955
Document URL
https://www.proquest.com/scholarly-journals/isogeometric-collocation-method-random-field/docview/3230590955/se-2?accountid=208611
Copyright
© The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-17
Database
ProQuest One Academic