Open AccessComparison Study on Linear Interpolation and Cubic B-Spline Interpolation Proper Orthogonal Decomposition Methods
Author(s) -
Xiaolong Wang,
Yi Wang,
Zhizhu Cao,
Weizhong Zou,
Liping Wang,
Guojun Yu,
Bo Yu,
Jinjun Zhang
Publication year - 2013
Publication title -
advances in mechanical engineering/advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1155/2013/561875
Subject(s) - monotone cubic interpolation , spline interpolation , interpolation (computer graphics) , linear interpolation , mathematics , nearest neighbor interpolation , multivariate interpolation , stairstep interpolation , cubic hermite spline , trilinear interpolation , bicubic interpolation , spline (mechanical) , thin plate spline , bilinear interpolation , mathematical analysis , algorithm , computer science , statistics , engineering , artificial intelligence , structural engineering , polynomial , motion (physics)
In general, proper orthogonal decomposition (POD) method is used to deal with single-parameter problems in engineering practice, and the linear interpolation is employed to establish the reduced model. Recently, this method is extended to solve the double-parameter problems with the amplitudes being achieved by cubic B-spline interpolation. In this paper, the accuracy of reduced models, which are established with linear interpolation and cubic B-spline interpolation, respectively, is verified via two typical examples. Both results of the two methods are satisfying, and the results of cubic B-spline interpolation are more accurate than those of linear interpolation. The results are meaningful for guiding the application of the POD interpolation to complex multiparameter problems