A Dimensional Reduction Approach Based on the Application of Reduced Basis Methods in the Framework of Hierarchical Model Reduction
In this article we introduce a new dimensional reduction approach which is based on the application of reduced basis (RB) techniques in the hierarchical model reduction (HMR) framework. Considering problems that exhibit a dominant spatial direction, the idea of HMR is to perform a Galerkin projectio...
Main Authors: | Ohlberger, Mario, Smetana, Kathrin |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Mechanical Engineering |
Format: | Article |
Language: | en_US |
Published: |
Society for Industrial and Applied Mathematics
2014
|
Online Access: | http://hdl.handle.net/1721.1/88243 https://orcid.org/0000-0003-4245-6586 |
Similar Items
-
High dimensional linear regression using lattice basis reduction
Published: (2021) -
High dimensional linear regression using lattice basis reduction
by: Gamarnik, David, et al.
Published: (2022) -
Optimal Local Approximation Spaces for Component-Based Static Condensation Procedures
by: Smetana, Kathrin, et al.
Published: (2017) -
Basis Reduction Algorithms and Subset Sum Problems
by: LaMacchia, Brian A.
Published: (2004) -
Basis reduction algorithms and subset sum problems
by: LaMacchia, Brian A. (Brian Andrew)
Published: (2005)