Zobrazeno 1 - 10
of 527
pro vyhledávání: '"Peter Benner"'
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 11, Iss 1, Pp 1-34 (2024)
Abstract This survey discusses a posteriori error estimation for model order reduction of parametric systems, including linear and nonlinear, time-dependent and steady systems. We focus on introducing the error estimators we have proposed in the past
Externí odkaz:
https://doaj.org/article/a0224ff6d8684e3c8b562ecd3046629f
Publikováno v:
Boundary Value Problems, Vol 2023, Iss 1, Pp 1-12 (2023)
Abstract We investigate the existence of solutions of weakly nonlinear periodic boundary value problems for systems of ordinary differential equations with switchings and the construction of these solutions. We consider the critical case where the eq
Externí odkaz:
https://doaj.org/article/f8a0ac2240ad40548cbb03d74a62a1f1
Autor:
Mohammad S. Khorrami, Jaber R. Mianroodi, Nima H. Siboni, Pawan Goyal, Bob Svendsen, Peter Benner, Dierk Raabe
Publikováno v:
npj Computational Materials, Vol 9, Iss 1, Pp 1-10 (2023)
Abstract The purpose of this work is the development of a trained artificial neural network for surrogate modeling of the mechanical response of elasto-viscoplastic grain microstructures. To this end, a U-Net-based convolutional neural network (CNN)
Externí odkaz:
https://doaj.org/article/dd6344fcbb0b40e585ce83212f4777ba
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 9, Iss 1, Pp 1-14 (2022)
Abstract We propose an adaptive moment-matching framework for model order reduction of quadratic-bilinear systems. In this framework, an important issue is the selection of those shift frequencies where moment-matching is to be achieved. So far, the
Externí odkaz:
https://doaj.org/article/bca53c90ecb94dadbe0ee2de58701e25
Autor:
Pawan Goyal, Peter Benner
Publikováno v:
Royal Society Open Science, Vol 10, Iss 7 (2023)
Measurement noise is an integral part of collecting data of a physical process. Thus, noise removal is necessary to draw conclusions from these data, and it often becomes essential to construct dynamical models using these data. We discuss a methodol
Externí odkaz:
https://doaj.org/article/844daf775a1549b0b67fca02cd23bcb4
Publikováno v:
Journal of Mathematics in Industry, Vol 11, Iss 1, Pp 1-46 (2021)
Abstract To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, ha
Externí odkaz:
https://doaj.org/article/218fe3b852014f9f93962e0e84abd612
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 8 (2022)
The control of general nonlinear systems is a challenging task in particular for large-scale models as they occur in the semi-discretization of partial differential equations (PDEs) of, say, fluid flow. In order to employ powerful methods from linear
Externí odkaz:
https://doaj.org/article/3e0168b4143a4285a7df5ca3997e6242
Publikováno v:
Data-Centric Engineering, Vol 3 (2022)
Mathematical models are essential to analyze and understand the dynamics of complex systems. Recently, data-driven methodologies have gotten a lot of attention which is leveraged by advancements in sensor technology. However, the quality of obtained
Externí odkaz:
https://doaj.org/article/023bf0d775154731af0457ac76487a37
Autor:
Sara Espinoza, David Linke, Christoph Wulf, Sonja Schimmler, Stephan Andreas Schunk, Peter Benner, Ralph Kraehnert, Udo Kragl, Regine Palkovits, Stefan Palkovits, Mehtap Oezaslan, Roger Gläser, Thomas Bönisch, Nils Bohmer, Michael Resch, Matthias Beller, Olaf Deutschmann, Uwe Bornscheuer, Mark Greiner, Walter Leitner, Wagemann Kurt
Publikováno v:
Bausteine Forschungsdatenmanagement, Iss 2 (2021)
Die Katalyse ist ein sehr komplexes und interdisziplinäres wissenschaftliches Gebiet, das die effiziente Herstellung einer Vielzahl von Produkten für verschiedene Branchen und in unterschiedlichen Produktionsgrößen ermöglicht. Somit ist die Kata
Externí odkaz:
https://doaj.org/article/b9d61b904fd04f4895ef3d089c256918
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 6, Iss 1, Pp 1-33 (2019)
Abstract This paper studies parametric reduced-order modeling via the interpolation of linear multiple-input multiple-output reduced-order, or, more general, surrogate models in the frequency domain. It shows that realization plays a central role and
Externí odkaz:
https://doaj.org/article/e4cb76bb1f5f4806a3223649b5934a4a