Thermal Coupling

The performance of high-tech circuitry such as processors and power devices also largely depends on the thermal level. Semiconductor devices loss their ability of fast switching if the temperature increases to much. Furthermore after a critical temperature is reached the device will be destroyed. Therefore monitoring temperature and regulating cooling are important issues.
In our research, we set up simulation models for semiconductor equations and integrated circuits, which incorporate transient temperature changes in the device and heat conduction between devices. That is an electric network as well as semiconductor equations have to be equipped with an appropriate model for power transfer and heat conduction.
Since this multiphysical problem of coupled electric networks and heat conduction exhibits widely separated time scales, not only the model but also the numerical algorithms need be design to enable fast simulations. Multirate cosimulation is an good choice if the coupling is appropriately set up. Please see also: (Coupled DAEs).
Publications
- 2021
4564.
Felpel, M.; Kienitz, J.; McWalter, T. A.
Effective stochastic volatility: Applications to {ZABR}-type models
Quantitative Finance, 21 (5) :837-852
2021
Herausgeber: Routledge4563.
Felpel, M.; Kienitz, J.; McWalter, T. A.
Effective stochastic volatility: applications to ZABR-type models
Quantitative Finance, 21 (5) :837–852
2021
Herausgeber: Routledge4562.
Haussmann, N.; Zang, M.; Stroka, S.; Mease, R.; Schmuelling, B.; Clemens, M.
Efficient Assessment of the Human Exposure to Low-Frequency Magnetic Fields Based on Free Space Field Measurements
23rd International Conference on the Computation of Electromagnetic Fields (COMPUMAG 2021), Cancun, Mexico, Online Conference, 16.-21.01.2022. Two-page digest submitted.
20214561.
Acu, Ana-Maria; Heilmann, Margareta; Raşa, Ioan
Eigenstructure and iterates for uniquely ergodic Kantorovich modifications of operators II
Positivity, 25 :1585-1599
20214560.
[german] Grandrath, Rebecca; Bohrmann-Linde, Claudia
Eine Lehrkräfte-Fortbildung im Portrait: Lowcost Experimente zu verschiedenen Brennstoffzelltypen für den Einsatz im Chemieunterricht.
CHEMKON
20214559.
Alameddine, Jean-Marco; others
Electromagnetic Shower Simulation for CORSIKA 8
PoS, ICRC2021 :428
20214558.
Viviani, Emma; Di Persio, Luca; Ehrhardt, Matthias
Energy markets forecasting. From inferential statistics to machine learning: The German case
Energies, 14 (2) :364
2021
Herausgeber: MDPI4557.
Viviani, Emma; Di Persio, Luca; Ehrhardt, Matthias
Energy markets forecasting. From inferential statistics to machine learning: The German case
Energies, 14 (2) :364
2021
Herausgeber: MDPI4556.
Viviani, Emma; Di Persio, Luca; Ehrhardt, Matthias
Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case
Energies, 14 (2) :364
Januar 2021
Herausgeber: MDPI
ISSN: 1996-10734555.
Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case. Energies 2021, 14, 364
20214554.
Kossaczk{\'a}, Tatiana; Ehrhardt, Matthias; Günther, Michael
Enhanced fifth order {WENO} shock-capturing schemes with deep learning
Res. Appl. Math., 12 :100201
2021
Herausgeber: Elsevier4553.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Enhanced fifth order WENO shock-capturing schemes with deep learning
Results in Applied Mathematics, 12 :100201
2021
Herausgeber: Elsevier4552.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Enhanced fifth order WENO shock-capturing schemes with deep learning
Results in Applied Mathematics, 12 :100201
2021
Herausgeber: Elsevier4551.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Enhanced fifth order WENO shock-capturing schemes with deep learning
Results in Applied Mathematics, 12 :100201
2021
Herausgeber: Elsevier4550.
Kossaczká, Tatiana; Ehrhardt, Matthias; Günther, Michael
Enhanced fifth order WENO shock-capturing schemes with deep learning
Results in Applied Mathematics, 12 :100201
2021
Herausgeber: Elsevier4549.
Farkas, Bálint; Csomós, Petra; Kovács, Balázs
Error estimates for a splitting integrator for semilinear boundary coupled systems
IMA J. Numerical Analysis
20214548.
Stapmanns, J.; Hahne, J.; Helias, M.; Bolten, Matthias; Diesmann, M.; Dahmen, D.
Event-based update of synapses in voltage-based learning rules
Front. Neuroinform., 15 :15
20214547.
Stapmanns, J.; Hahne, J.; Helias, M.; Bolten, M.; Diesmann, M.; Dahmen, D.
Event-based update of synapses in voltage-based learning rules
Front. Neuroinform., 15 :15
20214546.
Stapmanns, J.; Hahne, J.; Helias, M.; Bolten, M.; Diesmann, M.; Dahmen, D.
Event-based update of synapses in voltage-based learning rules
Front. Neuroinform., 15 :15
20214545.
Glück, Jochen; Mugnolo, Delio
Eventual domination for linear evolution equations
Math. Z., 299 (3-4) :1421--1443
20214544.
Abreu, Pedro; others
Expected performance of the AugerPrime Radio Detector
PoS, ICRC2021 :262
20214543.
Tovar, Carmen M.; Haack, Alexander; Barnes, Ian; Bejan, Iustinian Gabriel; Wiesen, Peter
Experimental and theoretical study of the reactivity of a series of epoxides with chlorine atoms at 298 K
Physical Chemistry Chemical Physics, 23 (9) :5176-5186
20214542.
Tovar, Carmen M.; Haack, Alexander; Barnes, Ian; Bejan, Iustinian Gabriel; Wiesen, Peter
Experimental and theoretical study of the reactivity of a series of epoxides with chlorine atoms at 298 K
Physical Chemistry Chemical Physics, 23 (9) :5176-5186
20214541.
Tovar, Carmen M.; Haack, Alexander; Barnes, Ian; Bejan, Iustinian Gabriel; Wiesen, Peter
Experimental and theoretical study of the reactivity of a series of epoxides with chlorine atoms at 298 K
Physical Chemistry Chemical Physics, 23 (9) :5176-5186
20214540.
Grandrath, Rebecca; Bohrmann-Linde, Claudia
Experimentalkurs zu Biologischen Brennstoffzellen. Begleitendes E-Book für die Sekundarstufe II [Schülerversion]
2021