Coupled DAE Problems

A circuit (DAE model) coupled to a magnetostatic field device (PDE model)
Coupled Problems of differential-algebraic equations (DAEs) arise typically from either multiphysical modeling (e.g. in circuit simulation with heating) or from refined modeling, where crucial parts of the original problem are replaced by a better, but computational more expensive model (e.g. circuits refined by field models). Furthermore splitting methods may turn a monolithic DAE problem into coupled subproblems, e.g. because of different time scales (multirate). In any case the DAEs arise from network approaches or space-discretization of PDAEs (Partial Differential Algebraic Equations).
Often the coupled equations have quite different properties, i.e., symmetries, definiteness or time scales. Thus the coupled system must be analyzed (e.g. the index) and tailored methods have to be developed (e.g. dynamic iteration).
Details
Publications
- 2023
5150.
Dehne, Tobias
Assessment of horizontal flame spread with solid pyrolysis modelling in the Fire Dynamics Simulator
Bergische Universität Wuppertal
20235149.
Schäfers, Torben; Teng, Long
Asymmetry in stochastic volatility models with threshold and time-dependent correlation
Studies in Nonlinear Dynamics & Econometrics, 27 (2) :131–146
2023
Herausgeber: De Gruyter5148.
Hastir, Anthony; Hosfeld, René; Schwenninger, Felix L.; Wierzba, Alexander A.
BIBO stability for funnel control: semilinear internal dynamics with unbounded input and output operators
20235147.
Gorski, Jochen; Klamroth, Kathrin; Sudhoff, Julia
Biobjective optimization problems on matroids with binary costs
Optimization, 72 (7) :1931-1960
2023
Herausgeber: Taylor & Francis5146.
[german] Grandrath, Rebecca
CapCut – intuitive und vollständige Videobearbeitung
:1-2
2023
Herausgeber: Friedrich-Schiller-Universität Jena, Institut für Anorganische und Analytische Chemie5145.
Hosfeld, René; Jacob, Birgit; Schwenninger, Felix L.
Characterization of Orlicz admissibility
Semigroup Forum, 106 :633–661
20235144.
Bohrmann-Linde, Claudia; Siehr, Ilona
Chemie Qualifikationsphase Nordrhein-Westfalen
Herausgeber: C.C.Buchner Verlag, Bamberg
2023ISBN: 978-3-661-06002-6
5143.
Albrecht, Johannes; others
Comparison and efficiency of GPU accelerated optical light propagation in CORSIKA\textasciitilde{}8
PoS, ICRC2023 :417
20235142.
Carrillo, Jose Antonio; Totzeck, Claudia; Vaes, Urbain
Consensus-based Optimization and Ensemble Kalman Inversion for Global Optimization Problems with Constraints
, Modeling and Simulation for Collective Dynamics,Lecture Notes Series, Institute for Mathematical Sciences, NUS Band 40
20235141.
Halim, A. Abdul; others
Constraining the sources of ultra-high-energy cosmic rays across and above the ankle with the spectrum and composition data measured at the Pierre Auger Observatory
JCAP, 05 :024
20235140.
Yue, Baobiao; others
Constraints on BSM particles from the absence of upward-going air showers in the Pierre Auger Observatory
PoS, ICRC2023 :1095
20235139.
Abdul Halim, Adila; others
Constraints on UHECR characteristics from cosmogenic neutrino limits with the measurements of the Pierre Auger Observatory
PoS, ICRC2023 :1520
20235138.
Abdul Halim, Adila; others
Constraints on upward-going air showers using the Pierre Auger Observatory data
PoS, ICRC2023 :1099
20235137.
Acu, Ana-Maria; Heilmann, Margareta; Raşa, Ioan; Seserman, Andra
Convergence of linking Durrmeyer type modifications of generalized Baskakov operators
Bulletin of the Malaysian Math. Sciences Society, 46 (3)
20235136.
Jacob, Birgit; Mironchenko, Andrii; Partington, Jonathan R.; Wirth, Fabian
Corrigendum: Noncoercive Lyapunov functions for input-to-state stability of infinite-dimensional systems
SIAM J. Control Optim., 61 (2) :723-724
20235135.
Aerdker, S.; others
CRPropa 3.2: a public framework for high-energy astroparticle simulations
PoS, ICRC2023 :1471
20235134.
Günther, Michael; Jacob, Birgit; Totzeck, Claudia
Data-driven adjoint-based calibration of port-Hamiltonian systems in time domain
arXiv preprint arXiv:2301.03924
20235133.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Deep FDM: Enhanced finite difference methods by deep learning
Franklin Open, 4 :100039
2023
Herausgeber: Elsevier5132.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Deep FDM: Enhanced finite difference methods by deep learning
Franklin Open, 4 :100039
2023
Herausgeber: Elsevier5131.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Deep FDM: Enhanced finite difference methods by deep learning
Franklin Open, 4 :100039
2023
Herausgeber: Elsevier5130.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Deep finite difference method for solving Asian option pricing problems
Preprint IMACM
2023
Herausgeber: Bergische Universität Wuppertal5129.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Deep finite difference method for solving Asian option pricing problems
Preprint IMACM
2023
Herausgeber: Bergische Universität Wuppertal5128.
Kapllani, Lorenc; Teng, Long
Deep Learning algorithms for solving high-dimensional nonlinear Backward Stochastic Differential Equations
Discrete Contin. Dyn. Syst. - B
2023
ISSN: 1531-34925127.
Kapllani, Lorenc; Teng, Long
Deep Learning algorithms for solving high-dimensional nonlinear backward stochastic differential equations
Discrete Contin. Dyn. Syst. - B
20235126.
Ackermann, Julia; Jentzen, Arnulf; Kruse, Thomas; Kuckuck, Benno; Padgett, Joshua Lee
Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense
2023