Hendrik Geisler, M. Sc.
30823 Garbsen
How to efficiently account for stochastic fluctuations in numerical simulations: Time-separated Stochastic Mechanics
In all physical measurements and production processes, random fluctuations play an unavoidable role. For example, it is not possible to exactly predict at which mechanical stress a material will fail or where a force acts on a component. To compensate for these uncertainties, engineers use safety factors in their calculations. This increases the safety of components and production processes, but at the cost of reduced resource efficiency.
To improve this situation, we at IKM develop the Time-separated Stochastic Mechanics, a new approach to efficiently incorporate the fluctuations of material parameters and loads efficiently in numerical simulations. The extremely low additional computational effort enables direct application to complex production processes in industry. Through the prediction of the stochastic behavior of components and processes even greater sustainability in mechanical engineering with reduced costs and increased reliability is achieved.
since 2021 | Research associate at the Institute of Continuum Mechanics |
2021 | Master of Science "with Distinction" |
2019 - 2020 | Stuying at the UC Berkeley, USA |
2015 - 2021 | Study of Mechanical Engineering at the TU Hamburg |
-
Publications
Showing results 1 - 7 out of 7
A new paradigm for the efficient inclusion of stochasticity in engineering simulations: Time-separated stochastic mechanics. / Geisler, Hendrik; Erdogan, Cem; Nagel, Jan et al.More...
In: Computational mechanics, 02.07.2024.Research output: Contribution to journal › Article › Research › peer review
Efficient and accurate uncertainty quantification in engineering simulations using time-separated stochastic mechanics. / Geisler, Hendrik; Junker, Philipp.More...
In: Archive of applied mechanics, Vol. 94, No. 9, 09.2024, p. 2603-2617.Research output: Contribution to journal › Article › Research › peer review
Uncertainty quantification for viscoelastic composite materials using time-separated stochastic mechanics. / Geisler, Hendrik; Junker, Philipp.More...
In: Probabilistic Engineering Mechanics, Vol. 76, 103618, 04.2024.Research output: Contribution to journal › Article › Research › peer review
A new paradigm for the efficient inclusion of stochasticity in engineering simulations. / Geisler, Hendrik; Erdogan, Cem; Nagel, Jan et al.More...
2023.Research output: Working paper/Preprint › Preprint
Time-separated stochastic mechanics for the simulation of viscoelastic structures with local random material fluctuations. / Geisler, Hendrik; Junker, Philipp.More...
In: Computer Methods in Applied Mechanics and Engineering, Vol. 407, 115916, 15.03.2023.Research output: Contribution to journal › Article › Research › peer review
U p -Net: a generic deep learning-based time stepper for parameterized spatio-temporal dynamics. / Stender, Merten; Ohlsen, Jakob; Geisler, Hendrik et al.More...
In: Computational mechanics, Vol. 71, No. 6, 06.2023, p. 1227–1249.Research output: Contribution to journal › Article › Research › peer review
Simulation of the dynamic behavior of viscoelastic structures with random material parameters using time-separated stochastic mechanics. / Geisler, Hendrik; Nagel, Jan; Junker, Philipp.More...
In: International Journal of Solids and Structures, Vol. 259, 112012, 25.12.2022.Research output: Contribution to journal › Article › Research › peer review