Isogeometric Collocation Method for Random Field Discretization Based on Adaptive Moment Abscissae

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Publicado en:Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao vol. 38, no. 1 (Dec 2025), p. 120
Autor principal: Liu, Zhenyu
Otros Autores: Peng, Deshang, Yang, Minglong, Cheng, Jin, Qiu, Chan, Tan, Jianrong
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Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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024 7 |a 10.1186/s10033-025-01293-9  |2 doi 
035 |a 3230590955 
045 2 |b d20251201  |b d20251231 
100 1 |a Liu, Zhenyu  |u Zhejiang University, State Key Laboratory of CAD & CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
245 1 |a Isogeometric Collocation Method for Random Field Discretization Based on Adaptive Moment Abscissae 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Eigenvalues 
653 |a Accuracy 
653 |a Stochastic processes 
653 |a Fields (mathematics) 
653 |a Random variables 
653 |a Integral equations 
653 |a Computer aided design--CAD 
653 |a Collocation methods 
653 |a Galerkin method 
653 |a Parameters 
653 |a Discretization 
653 |a Fredholm equations 
653 |a Efficiency 
653 |a Computer aided engineering--CAE 
653 |a Eigenvectors 
700 1 |a Peng, Deshang  |u Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
700 1 |a Yang, Minglong  |u 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) 
700 1 |a Cheng, Jin  |u Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
700 1 |a Qiu, Chan  |u Zhejiang University, State Key Laboratory of CAD & CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
700 1 |a Tan, Jianrong  |u Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
773 0 |t Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao  |g vol. 38, no. 1 (Dec 2025), p. 120 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3230590955/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3230590955/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3230590955/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch