Abstract
Parametric modeling as well as parametric model order reduction (PMOR) of parametric systems are being widely researched in many micro- and nano-electrical(-mechanical) problems as well as in coupled micro- and nano-electro-thermal problems. We propose an adaptive technique for automatically implementing PMOR, so as to automatically construct the reduced-order models. The adaptive technique is based on a posteriori error estimation and is realized through a greedy algorithm which uses the error estimation as a stopping criteria.
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Acknowledgements
This work is supported by the collaborative project nanoCOPS, Nanoelectronic COupled Problems Solutions, supported by the European Union in the FP7-ICT-2013-11 Program under Grant Agreement Number 619166.
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Feng, L., Antoulas, A.C., Benner, P. (2016). Automatic Generation of Reduced-Order Models for Linear Parametric Systems. In: Russo, G., Capasso, V., Nicosia, G., Romano, V. (eds) Progress in Industrial Mathematics at ECMI 2014. ECMI 2014. Mathematics in Industry(), vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-23413-7_113
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DOI: https://doi.org/10.1007/978-3-319-23413-7_113
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