TY - GEN
T1 - Automatic Adaptive Sampling in Parametric Model Order Reduction by Matrix Interpolation
AU - Varona, Maria Cruz
AU - Mashuq-Un-Nabi,
AU - Lohmann, Boris
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/21
Y1 - 2017/8/21
N2 - In modeling and simulation of large-scale systems, Model Order Reduction (MOR), and specifically parametric MOR (pMOR), has grown in importance recently. In this paper, a concept based on distance between subspaces has been automated and combined with the efficient parametric reduction approach Matrix Interpolation to give an automatic adaptive sampling strategy in pMOR. An algorithm is developed and its efficacy established with the help of numerical results for a parametric Timoshenko beam model.
AB - In modeling and simulation of large-scale systems, Model Order Reduction (MOR), and specifically parametric MOR (pMOR), has grown in importance recently. In this paper, a concept based on distance between subspaces has been automated and combined with the efficient parametric reduction approach Matrix Interpolation to give an automatic adaptive sampling strategy in pMOR. An algorithm is developed and its efficacy established with the help of numerical results for a parametric Timoshenko beam model.
UR - http://www.scopus.com/inward/record.url?scp=85028765485&partnerID=8YFLogxK
U2 - 10.1109/AIM.2017.8014062
DO - 10.1109/AIM.2017.8014062
M3 - Conference contribution
AN - SCOPUS:85028765485
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 472
EP - 477
BT - 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
Y2 - 3 July 2017 through 7 July 2017
ER -