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Disambiguierung von "Offenhäuser, Philipp"

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Deep reinforcement learning for turbulence modeling in large eddy simulations

, , und . International journal of heat and fluid flow, 99 (February): 109094 (2023)
DOI: 10.1016/j.ijheatfluidflow.2022.109094

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Um zwischen Personen mit demselben Namen zu unterscheiden, wird der akademische Grad und der Titel einer wichtigen Publikation angezeigt. Zudem lassen sich über den Button neben dem Namen einige der Person bereits zugeordnete Publikationen anzeigen.

Dipl.-Ing. Philipp Tempel

Kinematics and dynamics modeling for real-time simulation of the cable-driven parallel robot IPAnema 3, , und . Proceedings of the 14th IFToMM World Congress, Seite 117-123. Taipei, IFToMM, (2015)

Philipp Miermeister

Modelling of kinematics and dynamics of the IPAnema 3 cable robot for simulative analysis, , , und . WGP Congress 2015 : progress in production engineering ; selected, peer reviewed papers from the 2015 WGP Congress, 794, Seite 419-426. Pfaffikon, Trans Tech Publ., (2015)

Philipp Menold University of Stuttgart

Ph. D. Philipp Rathert University of Stuttgart

Philipp Marx University of Stuttgart

 

Weitere Publikationen von Autoren mit dem selben Namen

High-pressure real gas jet and throttle flow as a simplified gas injector model using a discontinuous Galerkin method, , , , , , , , und . High performance computing in science and engineering '16 : transactions of the High Performance Computing Center, Stuttgart (HLRS) 2016, Seite 289-300. Cham, Springer, (2016)GALÆXI Scaling, , , , , , , , und . Dataset, (2024)Related to: Kurz, M., Kempf, D., Blind, M., Kopper, P., Offenhäuser, P., Schwarz, A., Starr, S., Keim, J., & Beck, A. (2024). GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems. Computer Physics Communications, 109388. doi: 10.1016/j.cpc.2024.109388.Replication Data for: Realizing Joint Extreme-Scale Simulations on Multiple Supercomputers - Two Superfacility Case Studies, , und . Dataset, (2024)Related to: Pollinger, T., Craen, A. V., Offenhäuser, P., & Pflüger, D. (2024). Realizing Joint Extreme-Scale Simulations on Multiple Supercomputers—Two Superfacility Case Studies. doi: 10.1109/SC41406.2024.00104.Load-balance strategies for CFD-codes on HPC systems. 7th GACM Colloquium on Computational Mechanics for Young Scientists from Academia and Industry, Seite 99-103. Stuttgart, Institute for Structural Mechanics, (2017)Deep reinforcement learning for computational fluid dynamics on HPC systems, , , , , und . Journal of computational science, (2022)3-D visualization of transparent fluid flows from snapshot light field data, , und . Experiments in fluids, (2021)Real-Gas Jet and Throttle Flows at High Pressure as Simplified Gas Injector Models with a Discontinuous Galerkin Method, , , , , , , , und . Springer, (2016)A Method to Reduce Load Imbalances in Simulations of Solidification Processes with Free Surface 3D, , , und . Sustained Simulation Performance 2018 and 2019, Seite 163--184. Cham, Springer International Publishing, (2020)Relexi — A scalable open source reinforcement learning framework for high-performance computing, , , , und . Software Impacts, (Dezember 2022)GALÆXI Validation: Taylor-Green Vortex, , , , , , , , und . Dataset, (2024)Related to: Kurz, M., Kempf, D., Blind, M., Kopper, P., Offenhäuser, P., Schwarz, A., Starr, S., Keim, J., & Beck, A. (2024). GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems. Computer Physics Communications, 109388. doi: 10.1016/j.cpc.2024.109388.