Electric Networks

From the fully automatic coffee machine to the central processing units, electronic circuits and computer chips enhance the quality of our daily life. Since these circuits consist of millions of network elements, like resistors, capacitors, inductors and transistors, chip design relies strongly on circuit simulation. The computed electric behavior is used by the designer to rate and validate new developements before production.
Miniaturization of single elements and ultra high integration is the ongoing trend to enhance the performance of all electronic devices. It leads to smaller devices driven by higher frequencies and smaller signals and overall it leads from micro- to nanotechnolgy.
In turn, modern circuit simulators have to face several challenges: higher packing densities result in larger systems with increased power density, and smaller signals result in larger noise/signal ratio and thus stronger influence of parasitic effects, which could have been neglected before.
This leads to our ongoing research in the field of circuit simulation:
- Speed up of circuit simulation by identification of active and latent parts in electric circuits (Multirate)
- Model Order Reduction for parasitic circuits
- Coupling of circuit simulators with distributed device models (Dynamic Iteration, Semiconductors, Electromagnetic Field Devices)
Former and ongoing projects
Cooperations
- Academic
- Markus Clemens, Bergische Universität Wuppertal
- Herbert de Gersem, K.U. Leuven, Belgium
- Caren Tischendorf, Universität zu Köln, Germany
- Industrial
Publications
- 2024
5260.
Kossaczká, Tatiana; Jagtap, Ameya D; Ehrhardt, Matthias
Deep smoothness WENO method for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators
Physics of Fluid, 36 (3) :036603
2024
Herausgeber: AIP Publishing5259.
Kossaczká, Tatiana; Jagtap, Ameya D; Ehrhardt, Matthias
Deep smoothness WENO method for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators
Physics of Fluid, 36 (3) :036603
2024
Herausgeber: AIP Publishing5258.
Stiglmayr, Michael; Uhlemeyer, Svenja; Uhlemeyer, Björn; Zdrallek, Markus
Determining Cost-Efficient Controls of Electrical Energy Storages Using Dynamic Programming
Journal of Mathematics in Industry
20245257.
Ehrhardt, M.; Kruse, T.; Tordeux, A.
Dynamics of a Stochastic port-{H}amiltonian Self-Driven Agent Model in One Dimension
ESAIM: Math. Model. Numer. Anal.
20245256.
Efficient and Simple Extraction Protocol for Triterpenic Acids from Apples
Journal of Chemical Education, 101 :2087-2093
April 2024
Herausgeber: ACS5255.
Santos, Daniela Scherer; Klamroth, Kathrin; Martins, Pedro; Paquete, Luís
Ensuring connectedness for the Maximum Quasi-clique and Densest $k$-subgraph problems
20245254.
Holzenkamp, Matthias; Lyu, Dongyu; Kleinekathöfer, Ulrich; Zaspel, Peter
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials.
20245253.
Gaul, Daniela
Exact and Heuristic Methods for Dial-a-Ride Problems
Dissertation
Dissertation
Bergische Universität Wuppertal
20245252.
Lyu, Dongyu; Holzenkamp, Matthias; Vinod, Vivin; Holtkamp, Yannick M.; Maity, Sayan; Salazar, Carlos R.; Kleinekathöfer, Ulrich; Zaspel, Peter
Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine Learning.
20245251.
Kienitz, Jörg
Exciting times are ahead - Gaussian views and yield curve extrapolation
Wilmott, 2024 (134) :46–50
2024
Herausgeber: Wilmott Magazine5250.
[german] Zeller, Diana; Bohrmann-Linde, Claudia
Falschinformationen in Videos? Mit dem Konzept KriViNat die Kompetenz der Informationsbewertung stärken
In Bohrmann-Linde, C.; Gökkus, Y.; Meuter, N.; Zeller, D., Editor, Band Netzwerk Digitalisierter Chemieunterricht. Sammelband NeDiChe-Treff 2022
Seite 9-15
Herausgeber: Chemiedidaktik. Bergische Universität Wuppertal
2024
9-155249.
Bartel, Andreas; Schaller, Manuel
Goal-oriented time adaptivity for port-{H}amiltonian systems
20245248.
Schäfers, Kevin; Finkenrath, Jacob; Günther, Michael; Knechtli, Francesco
Hessian-free force-gradient integrators
20245247.
Hosfeld, René; Jacob, Birgit; Schwenninger, Felix; Tucsnak, Marius
Input-to-state stability for bilinear feedback systems
SIAM Journal on Control and Optimization, 62 (3) :1369-1389
20245246.
Jamil, Hamza
Intrusive and non-intrusive uncertainty quantification methodologies for pyrolysis modeling
Fire Safety Journal, 143 :104060
2024
ISSN: 0379-71125245.
Vinod, Vivin; Zaspel, Peter
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
20245244.
Botchev, M. A.; Knizhnerman, L. A.; Schweitzer, M.
Krylov subspace residual and restarting for certain second order differential equations
SIAM J. Sci. Comput., 46 (2) :S223-S253
20245243.
Hastir, Anthony; Jacob, Birgit; Zwart, Hans
Linear-Quadratic optimal control for boundary controlled networks of waves
20245242.
Xu, Zhuo; Tucsnak, Marius
LQR control for a system describing the interaction between a floating solid and the surrounding fluid
Mathematical Control and Related Fields, 14(4) :1477-1500
Dezember 20245241.
Costa, G Morais Rodrigues; Ehrhardt, Matthias
Mathematical analysis and a nonstandard scheme for a model of the immune response against COVID-19
Band 793
Seite 251–270
Herausgeber: AMS Contemporary Mathematics
2024
251–2705240.
Costa, G Morais Rodrigues; Ehrhardt, Matthias
Mathematical analysis and a nonstandard scheme for a model of the immune response against COVID-19
Band 793
Seite 251–270
Herausgeber: AMS Contemporary Mathematics
2024
251–2705239.
Bolten, Matthias; Kilmer, Misha E.; MacLachlan, Scott
Multigrid preconditioning for regularized least-squares problems
SIAM J. Sci. Comput., 46 (5) :s271—s295
2024
ISSN: 1064-82755238.
Schultes, Johanna
Multiobjective optimization of shapes using scalarization techniques
Dissertation
Dissertation
Bergische Universität Wuppertal
20245237.
Allmendinger, Richard; Fonseca, Carlos M.; Sayin, Serpil; Wiecek, Margaret M.; Stiglmayr, Michael
Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361)
2024
Herausgeber: Schloss Dagstuhl – Leibniz-Zentrum für Informatik5236.
Bolten, M.; Doganay, O. T.; Gottschalk, H.; Klamroth, K.
Non-convex shape optimization by dissipative Hamiltonian flows
Eng. Optim. :1—20
2024