Dynamic iteration and model order reduction for magneto-quasistatic systems

Our world today is becoming increasingly complex, and technical devices are getting ever smaller and more powerful. The high density of electronic components together with high clock frequencies leads to unwanted side-effects like crosstalk, delayed signals and substrate noise, which are no longer n...

Szczegółowa specyfikacja

Zapisane w:
Opis bibliograficzny
1. autor: Kerler-Back, Johanna
Format: Online
Język:angielski
Wydane: Logos Verlag Berlin 2021
Hasła przedmiotowe:
Dostęp online:ONIX_20210408_9783832549107_51
Etykiety: Dodaj etykietę
Nie ma etykietki, Dołącz pierwszą etykiete!
_version_ 1869517480446132224
author Kerler-Back, Johanna
author_browse Kerler-Back, Johanna
author_facet Kerler-Back, Johanna
author_sort Kerler-Back, Johanna
collection Directory of Open Access Books
description Our world today is becoming increasingly complex, and technical devices are getting ever smaller and more powerful. The high density of electronic components together with high clock frequencies leads to unwanted side-effects like crosstalk, delayed signals and substrate noise, which are no longer negligible in chip design and can only insufficiently be represented by simple lumped circuit models. As a result, different physical phenomena have to be taken into consideration since they have an increasing influence on the signal propagation in integrated circuits. Computer-based simulation methods play thereby a key role. The modelling and analysis of complex multi-physics problems typically leads to coupled systems of partial differential equations and differential-algebraic equations (DAEs). Dynamic iteration and model order reduction are two numerical tools for efficient and fast simulation of coupled systems. Formodelling of low frequency electromagnetic field, we use magneto-quasistatic (MQS) systems which can be considered as an approximation to Maxwells equations. A spatial discretization by using the finite element method leads to a DAE system. We analyze the structural and physical properties of this system and develop passivity-preserving model reduction methods. A special block structure of the MQS model is exploited to to improve the performance of the model reduction algorithms.
format Online
id doab-20.500.12854ir-64409
institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher Logos Verlag Berlin
publisherStr Logos Verlag Berlin
record_format ojs
spelling doab-20.500.12854ir-644092024-04-04T14:41:10Z Dynamic iteration and model order reduction for magneto-quasistatic systems Kerler-Back, Johanna model order reduction dynamic iteration magneto-quasistatic systems differential algebraic equations finite element method thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis Our world today is becoming increasingly complex, and technical devices are getting ever smaller and more powerful. The high density of electronic components together with high clock frequencies leads to unwanted side-effects like crosstalk, delayed signals and substrate noise, which are no longer negligible in chip design and can only insufficiently be represented by simple lumped circuit models. As a result, different physical phenomena have to be taken into consideration since they have an increasing influence on the signal propagation in integrated circuits. Computer-based simulation methods play thereby a key role. The modelling and analysis of complex multi-physics problems typically leads to coupled systems of partial differential equations and differential-algebraic equations (DAEs). Dynamic iteration and model order reduction are two numerical tools for efficient and fast simulation of coupled systems. Formodelling of low frequency electromagnetic field, we use magneto-quasistatic (MQS) systems which can be considered as an approximation to Maxwells equations. A spatial discretization by using the finite element method leads to a DAE system. We analyze the structural and physical properties of this system and develop passivity-preserving model reduction methods. A special block structure of the MQS model is exploited to to improve the performance of the model reduction algorithms. 2021-04-08T15:34:05Z 2021-04-08T15:34:05Z 2019 book ONIX_20210408_9783832549107_51 9783832549107 https://directory.doabooks.org/handle/20.500.12854/64409 eng Augsburger Schriften zur Mathematik, Physik und Informatik image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=4910&lng=eng&id= https://www.logos-verlag.de/ebooks/OA/978-3-8325-4910-7.pdf Logos Verlag Berlin Logos Verlag Berlin 10.30819/4910 10.30819/4910 04b263a1-7fba-4491-9eae-1c394ac42fc3 9783832549107 Logos Verlag Berlin 35 164 Berlin/Germany open access
spellingShingle model order reduction
dynamic iteration
magneto-quasistatic systems
differential algebraic equations
finite element method
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis
Kerler-Back, Johanna
Dynamic iteration and model order reduction for magneto-quasistatic systems
title Dynamic iteration and model order reduction for magneto-quasistatic systems
title_full Dynamic iteration and model order reduction for magneto-quasistatic systems
title_fullStr Dynamic iteration and model order reduction for magneto-quasistatic systems
title_full_unstemmed Dynamic iteration and model order reduction for magneto-quasistatic systems
title_short Dynamic iteration and model order reduction for magneto-quasistatic systems
title_sort dynamic iteration and model order reduction for magneto quasistatic systems
topic model order reduction
dynamic iteration
magneto-quasistatic systems
differential algebraic equations
finite element method
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis
topic_facet model order reduction
dynamic iteration
magneto-quasistatic systems
differential algebraic equations
finite element method
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis
url ONIX_20210408_9783832549107_51
work_keys_str_mv AT kerlerbackjohanna dynamiciterationandmodelorderreductionformagnetoquasistaticsystems