Applied and Computational Mathematics (ACM)

Multirate

Highly integrated electric cicuits show a phenomenon called latency. That is, a processed signal causes activity only in a small subset of the whole circuit (imagine a central processing unit), whereas the other part of the system behaves almost constant over some time - is latent. Such an electric system can be described as coupled system, where the waveforms show different time scales, also refered to as multirate.

More generally, any coupled problem formulation due to coupled physical effects, may cause a multirate problem: image the simulation of car driving on the road, there you need a model for the wheel, the chassis, the dampers, the road,... (cf. co-simulation). Again each system is covered by their own time constant, which might vary over several orders of magnitude comparing different subsystems.

Classical methods cannot exploit this multirate potential, but resolve everything on the finest scale. This causes an over sampling of the latent components. In constrast, Co-simulation or especially dedicated multirate methods are designed to use the inherent step size to resolve the time-domain behaviour of each subystem with the required accuracy. This requires a time-stepping for each.

Group members working in that field

  • Andreas Bartel
  • Michael Günther

Former and ongoing Projects

Cooperations

Publications



2019

4117.

Hartikainen, Markus; Miettinen, Kaisa; Klamroth, Kathrin
Interactive nonconvex Pareto navigator for multiobjective optimization
European Journal of Operational Research, 275 (1) :238-251
2019

4116.

Pulch, Roland; Putek, Piotr; De Gersem, Herbert; Gillon, Renaud
Inverse modeling: Glue-Package-Die problem
In ter Maten, E. Jan W. and Brachtendorf, Hans-Georg and Pulch, Roland and Schoenmaker, Wim and De Gersem, Herbert, Editor aus Mathematics in Industry
Seite 279–289
Herausgeber: Springer Cham
2019
279–289

4115.

Ehrhardt, Matthias; Vázquez, Carlos
Jump-diffusion models with two stochastic factors for pricing swing options in electricity markets with partial-integro differential equations
Applied Numerical Mathematics, 139 :77–92
2019
Herausgeber: North-Holland

4114.

Ehrhardt, Matthias; Vázquez, Carlos
Jump-diffusion models with two stochastic factors for pricing swing options in electricity markets with partial-integro differential equations
Applied Numerical Mathematics, 139 :77--92
2019
Herausgeber: North-Holland

4113.

Ehrhardt, Matthias; Vázquez, Carlos
Jump-diffusion models with two stochastic factors for pricing swing options in electricity markets with partial-integro differential equations
Applied Numerical Mathematics, 139 :77–92
2019
Herausgeber: North-Holland

4112.

Kleefeldt, Simon; Bohrmann-Linde, Claudia
Keep Track of The Heat
2019

4111.

Griebel, M.; Rieger, C.; Zaspel, Peter
Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations
IJUQ, 9 (5)
2019

4110.

Jensen, Per
Linear and bent triatomic molecules are not qualitatively different!
Canadian Journal of Physics :1-6
2019
Herausgeber: NRC Research Press

4109.

Bolten, Matthias; Claus, L.
Local Fourier Analysis of multigrid methods for the Stokes problem
PAMM, 19 :e201900394
2019

4108.

Bolten, M.; Claus, L.
Local Fourier Analysis of multigrid methods for the Stokes problem
PAMM, 19 :e201900394
2019

4107.

Bolten, M.; Claus, L.
Local Fourier Analysis of multigrid methods for the Stokes problem
PAMM, 19 :e201900394
2019

4106.

Glück, Jochen; Wolff, Manfred P. H.
Long-term analysis of positive operator semigroups via asymptotic domination
Positivity, 23 (5) :1113--1146
2019

4105.

Ehrhardt, Matthias; Gašper, Ján; Kilianová, Sona
Mathematical Modeling of an SIR-based infectious disease model with vaccination and waning immunity
2019

4104.

Gerlach, Moritz; Glück, Jochen
Mean ergodicity vs weak almost periodicity
Studia Math., 248 (1) :45--56
2019

4103.

[german] Yurdanur, Yasemin; Tausch, Michael W.
Metamorphoses of an Experiment - From Hightech UV Immersion Lamp Reactor to Low-Cost TicTac\(^{®}\)-Cell
{CHEMKON}, 26 (3) :125--129
2019
Herausgeber: Wiley

4102.

Schulze, Britta; Stiglmayr, Michael; Klamroth, Kathrin
Multi-Objective Unconstrained Combinatorial Optimization: A Polynomial Bound on the Number of Extreme Supported Solutions
Journal of Global Optimization, 74 (3) :495–522
2019

4101.

Friedhoff, S.; Hahne, J.; Schöps, S.
Multigrid-reduction-in-time for Eddy Current problems
PAMM, 19 (1) :e201900262
2019

4100.

Friedhoff, S.; Hahne, J.; Schöps, S.
Multigrid-reduction-in-time for Eddy Current problems
PAMM, 19 (1) :e201900262
2019

4099.

Friedhoff, S.; Hahne, J.; Schöps, S.
Multigrid-reduction-in-time for Eddy Current problems
PAMM, 19 (1) :e201900262
2019

4098.

Hachtel, Christoph; Bartel, Andreas; Günther, Michael; Sandu, Adrian
Multirate implicit Euler schemes for a class of differential{\textendash}algebraic equations of index-1
JCAM :112499
September 2019
Herausgeber: Elsevier {BV}

4097.

Bartel, Andreas; Günther, Michael
Multirate Schemes
Novel Mathematics Inspired by Industrial Challenges :5
2019

4096.


Nanoelectronic Coupled Problems Solutions
In ter Maten, E. J. W. and Brachtendorf, H.-G. and Pulch, R. and Schoenmaker, W. and De Gersem, H., Editor, Band 29 aus Mathematics in Industry
Herausgeber: Springer
2019

4095.

Tischendorf, Caren; Maten, E. Jan W.; Schoenmaker, Wim
Nanoelectronic coupled problems solutions – Highlights from the nanoCOPS project
In ter Maten, E. Jan W. and Brachtendorf, Hans-Georg and Pulch, Roland and Schoenmaker, Wim and De Gersem, Herbert, Editor aus Mathematics in Industry
Seite 1–21
Herausgeber: Springer Cham
2019
1–21

4094.

Demirkan, Reşat-Anıl
Neuartige Emulgatoren und deren Eignung für Rapsöl und Rapsölmethylester Emulsionen
2019

4093.

Schöps, Sebastian; Duque Guerra, David J; De Gersem, Herbert; Bartel, Andreas; Günther, Michael; Pulch, Roland
Non-Intrusive Methods for the Cosimulation of Coupled Problems
Nanoelectronic Coupled Problems Solutions :131--159
2019
Herausgeber: Springer International Publishing