SoSe 24: NumerikI IV: Modellierung, Simulation, und Optimierung
Christof Schütte, Stefanie Winkelmann
Kommentar
Inhalt:
Abstract:
Modeling, Simulation, and Optimization (MSO) is one of the cornerstones of application-oriented mathematics.
It covers a broad spectrum of research activities, ranging from the design of mathematical models for real-world processes, via efficient numerical simulation algorithms, to the solution of optimization problems for finding optimal scenarios or controls for the process under consideration. This lecture will give an overview over the techniques used in MSO and its application in different areas (life science, mobility, energy, sustainability, …). The lecture will be complemented by several pilot projects in which student groups will develop MSO solutions for realistic (but not too complex) application problems.
Zielpublikum:
Master Mathematik
Literaturhinweise
- Brokate and J. Sprekels: Hysteresis and Phase Transitions. Springer (1996)
- K. Deckelnick, G. Dziuk, and Ch.M. Elliott: Computation of geometric partial differential equations and mean curvature flow. Acta Numerica, p. 1-94 (2005)
- G. Dziuk and Ch.M. Elliott: Finite elements on evolving surfaces. IMA J. Numer. Anal. 27, p. 262-292 (2007)
- J.A. Sethian: Level Set Methods and Fast Marching Methods, CambridgeUniversity Press (1999)
- T.J. Willmore: Riemannian Geometry, Clarendon, Oxford (1993)
- Winkelmann, Stefanie, and Christof Schütte. Stochastic dynamics in computational biology. Vol. 645. Berlin/Heidelberg, Germany: Springer, 2020.
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