Efficient grid deformation using deterministic sampling‐based data reduction. (23rd June 2020)
- Record Type:
- Journal Article
- Title:
- Efficient grid deformation using deterministic sampling‐based data reduction. (23rd June 2020)
- Main Title:
- Efficient grid deformation using deterministic sampling‐based data reduction
- Authors:
- Cho, Haeseong
Kim, Haedong
Shin, SangJoon - Abstract:
- Summary: Spring analogies and the point‐by‐point interpolating approaches have been widely used for the grid deformation, and both require solution of a linear system of equations. Depending on the problem, the resulting system of equations may be defined by a large‐dimensional matrix. Thus, sampling for a subset of the grids is essential in order to achieve an efficient grid deformation. This article presents an efficient grid deformation algorithm developed via deterministic data sampling. From the position data of the deformed grids, proper orthogonal decomposition and discrete empirical interpolation method are employed to define the subset of the grids. Herein, symmetric rank‐one update is considered to choose the additional grids (oversampling). And it facilitates the deterministic data sampling approach and realizes the improved stability within the data reduction procedure. Such deterministic data sampling approach is applied to the moving submesh approach and radial basis function (RBF) interpolations. Specifically, for an RBF interpolation, boundaries of a deformable body are directly introduced within the data reduction procedure to improve the computational efficiency. Two‐ and three‐dimensional examples are used to evaluate the relevant computational efficiency of the proposed methods. It is found that computational time consumed by the present method is two orders of magnitude smaller than that of the existing method while maintaining the quality of theSummary: Spring analogies and the point‐by‐point interpolating approaches have been widely used for the grid deformation, and both require solution of a linear system of equations. Depending on the problem, the resulting system of equations may be defined by a large‐dimensional matrix. Thus, sampling for a subset of the grids is essential in order to achieve an efficient grid deformation. This article presents an efficient grid deformation algorithm developed via deterministic data sampling. From the position data of the deformed grids, proper orthogonal decomposition and discrete empirical interpolation method are employed to define the subset of the grids. Herein, symmetric rank‐one update is considered to choose the additional grids (oversampling). And it facilitates the deterministic data sampling approach and realizes the improved stability within the data reduction procedure. Such deterministic data sampling approach is applied to the moving submesh approach and radial basis function (RBF) interpolations. Specifically, for an RBF interpolation, boundaries of a deformable body are directly introduced within the data reduction procedure to improve the computational efficiency. Two‐ and three‐dimensional examples are used to evaluate the relevant computational efficiency of the proposed methods. It is found that computational time consumed by the present method is two orders of magnitude smaller than that of the existing method while maintaining the quality of the deformed grids. … (more)
- Is Part Of:
- International journal for numerical methods in engineering. Volume 121:Number 18(2020)
- Journal:
- International journal for numerical methods in engineering
- Issue:
- Volume 121:Number 18(2020)
- Issue Display:
- Volume 121, Issue 18 (2020)
- Year:
- 2020
- Volume:
- 121
- Issue:
- 18
- Issue Sort Value:
- 2020-0121-0018-0000
- Page Start:
- 4028
- Page End:
- 4049
- Publication Date:
- 2020-06-23
- Subjects:
- data reduction -- moving submesh approach -- radial basis function interpolation
Numerical analysis -- Periodicals
Engineering mathematics -- Periodicals
620.001518 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/nme.6425 ↗
- Languages:
- English
- ISSNs:
- 0029-5981
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.404000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13756.xml