TY  - JOUR
AB  - Purpose This paper aims to describe a method for efficient frequency domain model order reduction. The method attempts to combine the desirable attributes of Krylov reduction and proper orthogonal decomposition (POD) and is entitled Krylov enhanced POD (KPOD).Design/methodology/approach The KPOD method couples Krylov’s moment-matching property with POD’s data generalization ability to construct reduced models capable of maintaining accuracy over wide frequency ranges. The method is based on generating a sequence of state- and frequency-dependent Krylov subspaces and then applying POD to extract a single basis that generalizes the sequence of Krylov bases.Findings The frequency response of a pre-stressed microelectromechanical system resonator is used as an example to demonstrate KPOD’s ability in frequency domain model reduction, with KPOD exhibiting a 44 per cent efficiency improvement over POD.Originality/value The results indicate that KPOD greatly outperforms POD in accuracy and efficiency, making the proposed method a potential asset in the design of frequency-selective applications.
VL  - 34
IS  - 2
SN  - 0264-4401
DO  - 10.1108/EC-11-2015-0344
UR  - https://doi.org/10.1108/EC-11-2015-0344
AU  - Binion David
AU  - Chen Xiaolin
PY  - 2017
Y1  - 2017/01/01
TI  - A Krylov enhanced proper orthogonal decomposition method for frequency domain model reduction
T2  - Engineering Computations
PB  - Emerald Publishing Limited
SP  - 285
EP  - 306
Y2  - 2024/04/23
ER  -