LEADER 03159oam 2200481 450 001 9910418317803321 005 20230621141355.0 010 $a9783832549107 024 8 $ahttps://doi.org/10.30819/4910 035 $a(CKB)4100000011479705 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/64409 035 $a(ScCtBLL)f38abb35-344e-463c-832c-4253f46564b7 035 $a(EXLCZ)994100000011479705 100 $a20210223h20192019 fy 0 101 0 $aeng 135 $aur||#|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDynamic iteration and model order reduction for magneto-quasistatic systems /$fJohanna Kerler-Back 210 $aBerlin/Germany$cLogos Verlag Berlin$d2019 210 1$aBerlin, Germany :$cLogos Verlag Berlin GmbH,$d[2019] 210 4$dİ2019 215 $a1 online resource (ix, 140 pages) $cillustrations, charts; digital file(s) 225 0 $aAugsburger Schriften zur Mathematik, Physik und Informatik ;$vBand 35 300 $aAuthor's doctoral thesis, Universita?t Augsburg. 311 08$aPrint version: 3832549102 320 $aIncludes bibliographical references. 330 $aOur 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. 606 $aTechnology 610 $amodel order reduction 610 $adynamic iteration 610 $amagneto-quasistatic systems 610 $adifferential algebraic equations 610 $afinite element method 615 0$aTechnology. 676 $a537.015186 700 $aKerler-Back$b Johanna$0964824 712 02$aUniversita?t Augsburg, 801 0$bUkMaJRU 912 $a9910418317803321 996 $aDynamic iteration and model order reduction for magneto-quasistatic systems$92189035 997 $aUNINA