TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Investigating the skin friction drag across electrolytes and electrical fields using one-dimensional turbulence modeling T2 - European Drag Reduction and Flow Control Meeting, EDRFCM 2019, March 26-29 2019, Bad Herrenalb, Germany KW - electrohydrodynamic flows KW - Couette flow KW - turbulence modeling Y1 - 2019 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_2019_Klein+Schmidt_ODT_EHD_Couette_EDRFCM19.pdf UR - http://www.edrfcm.science/index.php/program SP - 1 EP - 2 ER - TY - GEN A1 - Klein, Marten A1 - Lignell, David O. A1 - Schmidt, Heiko T1 - Stochastic modeling of temperature and velocity statistics in spherical-shell convection T2 - Geophysical Research Abstracts, Vol. 21, EGU2019-2220 KW - turbulent convection KW - turbulence modeling KW - spherical shell Y1 - 2019 UR - https://meetingorganizer.copernicus.org/EGU2019/EGU2019-2220.pdf ER - TY - GEN A1 - Schmidt, Heiko A1 - Klein, Marten T1 - Simulating neutrally and stably stratified turbulent Ekman flows with a stochastic turbulence model T2 - Proc. of the 17th European Turbulence Conference (ETC17), 3-6 September 2019, Torino, Italy KW - turbulent boundary layer KW - turbulence modeling KW - Coriolis effects KW - stratification effects Y1 - 2019 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_2019_etc.pdf UR - http://www.etc17.it/ ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Investigating Rayleigh-Bénard convection at low Prandtl numbers using one-dimensional turbulence modeling T2 - Proc. of the 11th International Symposium on Turbulence and Shear Flow Phenomena (TSFP11), Southampton, UK, July 30 to August 2, 2019 KW - turbulent convection KW - turbulence modeling KW - low Prandtl number KW - high Rayleigh number Y1 - 2019 UR - http://www.tsfp-conference.org/proceedings/2019/14.pdf ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Investigating thermal convection at low Prandtl numbers using one-dimensional turbulence KW - turbulent convection KW - turbulence modeling KW - low Prandtl number KW - high Rayleigh number Y1 - 2019 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_2019_poster_tsfp11_evince-print.pdf N1 - Poster shown at 11th International Symposium on Turbulence and Shear Flow Phenomena (TSFP11), 30 July - 2 August 2019, Southampton, UK ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - The transition to the ultimate regime of thermal convection from a stochastic one-dimensional turbulence perspective T2 - arXiv KW - Rayleigh-Bénard convection KW - turbulence modeling KW - low Prandtl number KW - turbulent transitions KW - heat transfer Y1 - 2019 UR - https://arxiv.org/abs/1906.06621 SP - 1 EP - 11 ER - TY - GEN A1 - Glawe, Christoph A1 - Klein, Marten A1 - Schmidt, Heiko T1 - ODT augmented RaNS T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics KW - turbulence modeling KW - one-dimensional turbulence KW - Reynolds-averaged Navier-Stokes simulation KW - boundary layer KW - stochastic post-processing Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 368 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Klein, Marten A1 - Kessler, Robert William A1 - Schmidt, Heiko T1 - Numerical investigation of drag reduction effects on a track bicycle fork using wings with a wavy leading edge T2 - Proceedings in Applied Mathematics and Mechanics N2 - Reynolds‐averaged Navier–Stokes (RANS) and large‐eddy simulations (LES) of the flow around wings with a wavy leading edge (WLE) are conducted in order to assess the capabilities of a passive flow control strategy for drag reduction. The intended application is indoor track cycling with controlled flow conditions. A section of a single fork rod is investigated in order to make the numerical simulations feasible. The present study reveals that net drag reduction is possible by a nonsinusoidal modification of the leading edge of the wing. However, the drag reduction effect remains limited to a few percent. While RANS and LES yield the same drag coefficient for a reference case, RANS underestimates the drag reduction effect for a longer wing and the WLE cases, but exhibits otherwise a qualitatively similar trend as the LES. With the aid of RANS, an optimal geometry is obtained defined by the wavelength‐to‐chord length ratio of and the amplitude‐to‐chord length ratio of . Corresponding LES results give an indication of the origin of drag reduction by a hampered vortex shedding. The generation of smaller and more streamwise oriented vortical flow structures at the trailing edge and behind the WLE wing is correlated with significantly reduced lift fluctuations and drag reduction. KW - sports aerodynamics KW - passive flow control KW - aerodynamic drag KW - drag reduction KW - computational fluid dynamics KW - turbulence modeling Y1 - 2024 U6 - https://doi.org/10.1002/pamm.202400178 SN - 1617-7061 VL - 24 SP - 1 EP - 14 PB - Wiley ER - TY - GEN A1 - Polasanapalli, Sai Ravi Gupta A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Towards stochastic subgrid-scale modeling of turbulent thermal convection in an under-resolved off-lattice Boltzmann method T2 - Proceedings in applied mathematics and mechanics : PAMM N2 - A characteristic-based Off-Lattice Boltzmann Method (OLBM) and a stochastic One-Dimensional Turbulence (ODT) model is utilized for numerical simulation of turbulent thermal convection. Standalone ODT results for low-order statistics are compared with those from various eddy-viscosity-based subgrid-scale models utilized in Large-Eddy Simulations (LES) with OLBM. The predictive capabilities of both approaches are discussed by comparison with available reference Direct Numerical Simulation (DNS) results. All turbulence models are able to predicted the mean temperature, but fail to fully capture fluctuations. While the OLBM aims to represent large-scale structures, it misses some constitutional small-scale fluctuations. By contrast, the reduced-order ODT model captures small-scale fluctuations in the vicinity of the wall, but cannot resolve the organized bulk flow. Here, the modeling capabilities of both OLBM and ODT as standalone tools are discussed. On this basis, a strategy for the incorporation of ODT as wall model in OLBM is suggested. KW - thermal convection KW - heat transfer KW - lattice Boltzmann method KW - turbulence modeling KW - one-dimensional turbulence Y1 - 2023 UR - https://onlinelibrary.wiley.com/doi/10.1002/pamm.202300223 U6 - https://doi.org/10.1002/pamm.202300223 SN - 1617-7061 SP - 1 EP - 9 ER -