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...
Sparad:
| Huvudupphov: | |
|---|---|
| Materialtyp: | Online |
| Språk: | engelska |
| Utgiven: |
Logos Verlag Berlin
2022
|
| Ämnen: | |
| Länkar: | OCN: 1266667707 |
| Taggar: |
Inga taggar, Lägg till första taggen!
|
| _version_ | 1869519401569484800 |
|---|---|
| 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-84288 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Logos Verlag Berlin |
| publisherStr | Logos Verlag Berlin |
| record_format | ojs |
| spelling | doab-20.500.12854ir-842882025-07-31T06:51:11Z Dynamic iteration and model order reduction for magneto-quasistatic systems Kerler-Back, Johanna Technology & Engineering Electronics Mathematics Science Physics 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. 2022-06-19T04:05:23Z 2022-06-19T04:05:23Z 2022-06-18T05:31:25Z 2019 book OCN: 1266667707 https://library.oapen.org/handle/20.500.12657/56720 9783832549107 https://directory.doabooks.org/handle/20.500.12854/84288 eng open access image/jpeg image/jpeg image/jpeg image/jpeg image/jpeg n/a n/a n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/56720/1/external_content.pdf https://library.oapen.org/bitstream/20.500.12657/56720/1/external_content.pdf https://library.oapen.org/bitstream/20.500.12657/56720/1/external_content.pdf https://library.oapen.org/bitstream/20.500.12657/56720/1/external_content.pdf https://library.oapen.org/bitstream/20.500.12657/56720/1/external_content.pdf Logos Verlag Berlin Logos Verlag Berlin https://doi.org/10.30819/4910 https://doi.org/10.30819/4910 04b263a1-7fba-4491-9eae-1c394ac42fc3 Knowledge Unlatched 9783832549107 Knowledge Unlatched (KU) KU Open Services Logos Verlag Berlin open access |
| spellingShingle | Technology & Engineering Electronics Mathematics Science Physics 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 | Technology & Engineering Electronics Mathematics Science Physics |
| topic_facet | Technology & Engineering Electronics Mathematics Science Physics |
| url | OCN: 1266667707 |
| work_keys_str_mv | AT kerlerbackjohanna dynamiciterationandmodelorderreductionformagnetoquasistaticsystems |