Peter Förster

Peter Förster M.Sc.

Working area(s)

AI powered Digital Twin for lighting infrastructure in the context of front-end Industry 4.0


work +49 6151 16-24379

Work S2|17 38
Schloßgartenstr. 8
64289 Darmstadt

Self-learning multiphysical digital twins of lighting systems are researched. They will be used to predict product performance and lifetime in the context of infrastructure design and management in an autonomous world. The twins will be tested in selected application areas, such as automotive, horticultural, general, and street lighting.


Förster, Peter (2021):
ParaROCK: Parallelized Orthogonal Runge-Kutta-Chebyshev method. Technische Universität Darmstadt, Darmstadt. [Master's Thesis]


Förster, Peter ; Schöps, Sebastian ; Enders, Joachim ; Herbert, Maximilian ; Simona, Abele (2020):
Freeform shape optimization of a compact DC photo-electron gun using isogeometric analysis.
Cornell University, ARXIV: 2012.04372. [Preprint].


Förster, Peter (2018):
Particle Tracking in an Electron Gun using Isogeometric Analysis. Technische Universität Darmstadt, Darmstadt. [Bachelors's Thesis]

Cortes Garcia, Idoia ; De Gersem, Herbert ; Förster, Peter ; Kulchytska-Ruchka, Iryna ; Moskalew, Artem ; Quetscher, Frederik ; Schöps, Sebastian (2018):
Time parallelised Waveform Relaxation for Field/Circuit Coupled Systems.
In: 5th STEAM Collaboration Meeting, CERN, Geneva. URL: [Talk]