Reduced Order Modeling for Thermal Problems with Temperature-dependent Conductivities using Matrix Interpolation

2021 ◽  
Author(s):  
Meinhard Paffrath
Keyword(s):  
Reduced Order Modeling ◽  
Temperature Dependent ◽  
Reduced Order ◽  
Matrix Interpolation

scholarly journals Matrix Interpolation-Based Reduced-Order Modeling of a Levitation Device With Eddy Current Effects

2018 ◽  
Vol 54 (6) ◽  
pp. 1-7 ◽  
Author(s):  
MD. Rokibul Hasan ◽  
Laurent Montier ◽  
Thomas Henneron ◽  
Ruth V. Sabariego
Keyword(s):  
Eddy Current ◽  
Reduced Order Modeling ◽  
Reduced Order ◽  
Matrix Interpolation

scholarly journals A Component-Based Parametric Reduced-Order Modeling Method Combined with Substructural Matrix Interpolation and Automatic Sampling

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Ying Liu ◽  
Hongguang Li ◽  
Yun Li ◽  
Huanyu Du
Keyword(s):  
Parameter Space ◽  
Optimal Parameter ◽  
Synthesis Method ◽  
Sampling Procedure ◽  
Reduced Order Modeling ◽  
Modeling Method ◽  
Reduced Basis ◽  
Reduced Order ◽  
Automatic Sampling ◽  
Matrix Interpolation

An efficient parametric reduced-order modeling method combined with substructural matrix interpolation and automatic sampling procedure is proposed. This approach is based on the fixed-interface Craig-Bampton component mode synthesis method (CMS). The novel parametric reduced-order models (PROMs) are developed by interpolating substructural reduced-order matrices. To guarantee the compatibility of the coordinates, we develop a three-step adjustment procedure by reducing the local interface degrees of freedom (DOFs) and performing congruence transformation for the normal modes and interface reduced basis, respectively. In addition, an automatic sampling process is also introduced to dynamically fulfill the predefined error limits. It proceeds by first exploring the parameter space and identifying the sampling points with maximum error indicators for all the parameter-dependent substructures. The exact error of the assembled model at the optimal parameter point is subsequently calculated to determine whether the automatic sampling procedure reaches a desired error tolerance. The proposed framework is then applied to the moving coil of electrical-dynamic shaker to illustrate the advantage and validity. The results indicate that this new approach can significantly reduce both the offline database construction time and online calculation time. Besides, the automatic procedure can sample the parameter space efficiently and fulfill the stopping criterion dynamically with assurance of the resulting PROM accuracy.

Lattice Boltzmann Flow Simulations With Applications of Reduced Order Modeling Techniques.

2014 ◽  
Author(s):  
Donald L. Brown ◽  
Jun Li ◽  
Victor M. Calo ◽  
Mehdi Ghommem ◽  
Yalchin Efendiev
Keyword(s):  
Lattice Boltzmann ◽  
Reduced Order Modeling ◽  
Reduced Order ◽  
Flow Simulations ◽  
Modeling Techniques
Sign in / Sign up

Export Citation Format

Share Document