@inproceedings{MedinaMendezGlaweStaricketal., author = {Medina M{\´e}ndez, Juan Ali and Glawe, Christoph and Starick, Tommy and Sch{\"o}ps, Mark Simon and Schmidt, Heiko}, title = {IMEX-ODTLES: A multi-scale and stochastic approach for highly turbulent flows}, series = {90th Annual Meeting of the International Association of Applied Mathematics and Mechanics February 18-22, 2019 Vienna, Austria, Abstract book}, booktitle = {90th Annual Meeting of the International Association of Applied Mathematics and Mechanics February 18-22, 2019 Vienna, Austria, Abstract book}, publisher = {TU-Verlag}, address = {Wien}, isbn = {978-3-903024-84-7}, pages = {S. 540}, language = {en} } @misc{MedinaMendezGlaweStaricketal., author = {Medina M{\´e}ndez, Juan Ali and Glawe, Christoph and Starick, Tommy and Sch{\"o}ps, Mark Simon and Schmidt, Heiko}, title = {IMEX-ODTLES: A multi-scale and stochastic approach for highly turbulent flows}, series = {Proceedings in Applied Mathematics and Mechanics}, volume = {19}, journal = {Proceedings in Applied Mathematics and Mechanics}, number = {1}, issn = {1617-7061}, doi = {10.1002/pamm.201900433}, abstract = {The stochastic One-Dimensional Turbulence (ODT) model is used in combination with a Large Eddy Simulation (LES) approach in order to illustrate the potential of the fully coupled model (ODTLES) for highly turbulent flows. In this work, we use a new C++ implementation of the ODTLES code in order to analyze the computational performance in a classical incompressible turbulent channel flow problem. The parallelization potential of the model, as well as its physical and numerical consistency are evaluated and compared to Direct Numerical Simulations (DNSs). The numerical results show that the model is capable of reproducing a representative part of the DNS data at a cheaper computational cost. This advantage can be enhanced in the future by the implementation of a straightforward parallelization approach.}, language = {en} } @misc{KleinMedinaMendezSchoepsetal., author = {Klein, Marten and Medina M{\´e}ndez, Juan Al{\´i} and Sch{\"o}ps, Mark Simon and Schmidt, Heiko and Glawe, Christoph}, title = {Towards physics-based nowcasting of the instantaneous wind velocity profile using a stochastic modeling approach}, series = {STAB Jahresbericht 2024 zum 24. DGLR-Fachsymposium der STAB, 13. - 14. November 2024, Regensburg}, journal = {STAB Jahresbericht 2024 zum 24. DGLR-Fachsymposium der STAB, 13. - 14. November 2024, Regensburg}, publisher = {Deutsche Str{\"o}mungsmechanische Arbeitsgemeinschaft, STAB}, address = {Regensburg [et al.]}, pages = {162 -- 163}, abstract = {The primary objective of this contribution is to provide an overview of the regime-spanning forward modeling capabilities offered by the stochastic one-dimensional turbulence model. The focus is on the applicability of the model and its validation for neutral and stable atmospheric boundary layer flows as a prerequisite for future applications to challenging atmospheric conditions.}, language = {en} }