TY - CHAP A1 - Klein, Marten A1 - Schmidt, Heiko ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Wagner, Claus T1 - Stochastic Modeling of Passive Scalars in Turbulent Channel Flows: Predictive Capabilities of One-Dimensional Turbulence T2 - New Results in Numerical and Experimental Fluid Mechanics XIII N2 - Numerical simulations of passive scalars in turbulent channel flows up to friction Reynolds number Reτ = 5200 and Schmidt number Sc = 2000 are performed by utilizing the stochastic one-dimensional turbulence (ODT) model as stand-alone tool. The model is calibrated once for the turbulent velocity boundary layer at Reτ = 5200 so that the passive scalar is a model prediction. ODT is able to reproduce with reasonable accuracy the scaling regimes of the scalar transfer and locally resolve the boundary layer structure. Albeit the model is unable to capture the emerging dissimilarity of near-wall scalar and momentum transport for high Sc, it can economically and accurately represent fluctuating wall-normal fluxes. KW - boundary layers KW - one-dimensional turbulence KW - passive scalar KW - turbulent channel flow Y1 - 2021 UR - https://link.springer.com/chapter/10.1007/978-3-030-79561-0_5 SN - 978-3-030-79561-0 U6 - https://doi.org/10.1007/978-3-030-79561-0_5 SP - 47 EP - 57 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko A1 - Kerstein, Alan R. T1 - Transition to the ultimate regime in a stochasticmodel for thermal convection with internal sources N2 - It is well established that heat transfer in turbulent Rayleigh–Bénard convection and angular momentum transfer in turbulent Taylor–Couette flow are similar in nature. This similarity manifests itself by isomorphic scaling laws for corresponding flow regimes. However, it is not clear at present if this similarity extends to flows with internal sources and different types of boundary conditions. Internal sources may occur, for example, due to radiative heating in dry or condensation in moist convection, or due to internal wave breaking and mean flow excitation in rotating Taylor–Couette-like flows. In this study, heat transfer in radiatively-driven turbulent Rayleigh–Bénard convection is investigated using the stochastic one-dimensional-turbulence model (ODT). A Boussinesq fluid of Prandtl number 1 is confined between two horizontal adiabatic no-slip walls that are located at z = 0 and H, respectively. The fluid is exposed to constant background gravity that points in vertical (−z) direction. A flow is driven by radiative heating from below yielding the local heating rate Q(z) = (P/l) exp(−z/l), where P is the prescribed mean total heat flux and l the absorption length that controls the thermal boundary layer thickness. ODT resolves all relevant scales of the flow, including molecular-diffusive scales, along a vertical one-dimensional domain, whereas stochastically sampled eddy events represent the effects of turbulent advection. ODT results reproduce and extrapolate available reference experiments of Lepot et al. (Proc. Natl. Acad. Sci. USA, 115, 2018, pp. 8937–8941) and Bouillaut et al. (J. Fluid Mech., 861, 2019, R5) in particular capturing the turbulent transition from the classical to the ‘ultimate’ regime. For these regimes, the exponent values in N u ∼ Ra^p scaling are found to be p ≈ 0.33 and p ≈ 0.55, respectively, in agreement with measured values. Joint probabilities of turbulent eddy size and location suggest that the regime transition is associated with a suppression of small-scale near-wall turbulent motions. The latter observation is found consistent with recent direct numerical simulations of heat transfer between permeable walls (Kawano et al., J. Fluid Mech., 914, 2021, A13). KW - one-dimensional turbulence KW - turbulent thermal convection KW - heat transfer KW - high Rayleigh number Y1 - 2021 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_ictw21.pdf UR - https://www.b-tu.de/media/video/Transition-to-the-ultimate-regime-in-a-stochastic-model-for-thermal-convection-with-internal-sources/52aa69a52b8ab3ef29cc1d8bf9f20243 UR - https://pof.tnw.utwente.nl/ictw/schedule.html ER - TY - GEN A1 - Klein, Marten A1 - Zenker, Christian A1 - Schmidt, Heiko T1 - Map-based stochastic modeling of turbulent mixing in transient shear flows T2 - MATH+ CECAM Discussion Meeting on Generalized Langevin Equations N2 - Map-based stochastic modeling distinguishes molecular-diffusive from turbulent-advective transport processes in fluid flows. In the one-dimensional turbulence (ODT) model, a stochastic point process with energetically constrained rejection sampling of discrete eddy events is used to economically model the effects of turbulence on all relevant scales of the flow. Here I will discuss the model formulation and its application to passive scalar mixing in a confined jet. [1] M. Klein, C. Zenker, H. Schmidt (2019) Chem. Eng. Sci. 204:186-202 KW - one-dimensional turbulence KW - stochastic modeling KW - passive scalar KW - turbulent mixing Y1 - 2021 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_abstract_public_cecam21.pdf UR - https://www.b-tu.de/media/video/Map-based-stochastic-modeling-of-turbulent-mixing-in-transient-shear-flows/5f7312768f6bcce987ed801635dcdc07 UR - https://www.cecam.org/workshop-details/1086 UR - https://www.sciencedirect.com/science/article/pii/S0009250919303896?via%3Dihub ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko A1 - Kerstein, Alan R. T1 - Stochastic modeling of transient boundary layers in high-Rayleigh-number thermal convection, 25th International Congress of Theoretical and Applied Mechanics (ICTAM 20+1) N2 - One-dimensional turbulence (ODT) modeling is used to investigate the boundary layer in high-Rayleigh-number thermal convection for a notionally infinite horizontal layer of fluid. The model formulation distinguishes between turbulent advection, which is modeled by a stochastic process, and deterministic molecular diffusion to capture relevant vertical transport processes (including counter-gradient fluxes). For this study, statistical homogenization is applied to the two horizontal dimensions so that we use ODT as stand-alone tool. We show that the model yields mean and fluctuation temperature profiles that are in several respects consistent with available reference data. Furthermore, the profile of a surrogate for the fluctuation velocity is reminiscent of canonical wall turbulence. Y1 - 2021 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_ictam21.pdf UR - https://www.b-tu.de/media/video/Stochastic-modeling-of-transient-boundary-layers-in-high-Rayleigh-number-thermal-convection/f511d6b395472dc729543db3aa02dbc9 UR - https://www.ictam2020.org/assets/pdf/ICTAM2021-Fulllist-26-08.pdf ER - TY - GEN A1 - Klein, Marten A1 - Lignell, David O. A1 - Schmidt, Heiko T1 - Stochastic modeling of transient surface scalar and momentum fluxes in turbulent boundary layers T2 - EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-79 N2 - Turbulence is ubiquitous in atmospheric boundary layers and manifests itself by transient transport processes on a range of scales. This range easily reaches down to less than a meter, which is smaller than the typical height of the first grid cell layer adjacent to the surface in numerical models for weather and climate prediction. In these models, the bulk-surface coupling plays an important role for the evolution of the atmosphere but it is not feasible to fully resolve it in applications. Hence, the overall quality of numerical weather and climate predictions crucially depends on the modeling of subfilter-scale transport processes near the surface. A standing challenge in this regard is the robust but efficient representation of transient and non-Fickian transport such as counter-gradient fluxes that arise from stratification and rotation effects. We address the issues mentioned above by utilizing a stochastic one-dimensional turbulence (ODT) model. For turbulent boundary layers, ODT aims to resolve the wall-normal transport processes on all relevant scales but only along a single one-dimensional domain (column) that is aligned with the vertical. Molecular diffusion and unbalanced Coriolis forces are directly resolved, whereas effects of turbulent advection and stratification are modeled by stochastically sampled sequence of mapping (eddy) events. Each of these events instantaneously modifies the flow profiles by a permutation of fluid parcels across a selected size interval. The model is of lower order but obeys fundamental conservation principles and Richardson's 1/4 law by construction. In this study, ODT is applied as stand-alone tool in order to investigate nondimensional control parameter dependencies of the scalar and momentum transport in turbulent channel, neutral, and stably-stratified Ekman flows up to (friction) Reynolds number Re = O(104). We demonstrate that ODT is able to capture the state-space statistics of transient surface fluxes as well as the boundary-layer structure and nondimensional control parameter dependencies of low-order flow statistics. Very good to reasonable agreement with available reference data is obtained for various observables using fixed model set-ups. We conclude that ODT is an economical turbulence model that is able to not only capture but also predict the wall-normal transport and surface fluxes in multiphysics turbulent boundary layers. KW - one-dimensional turbulence KW - stochastic modeling KW - Ekman flow KW - atmospheric boundary layer KW - roating and stratified fluids Y1 - 2021 UR - https://doi.org/10.5194/ems2021-79 UR - https://www.b-tu.de/media/video/Stochastic-modeling-of-transient-surface-scalar-and-momentum-fluxes-in-turbulent-boundary-layers/8c7baf58c040239649fb7c3b2212c1d5 U6 - https://doi.org/10.5194/ems2021-79 ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko A1 - Lignell, David O. T1 - Stochastic modeling of transient surface scalar and momentum fluxes in turbulent boundary layers, EMS Annual Meeting 2021, online, 6–10 Sep 2021 KW - one-dimensional turbulence KW - stochastic modeling KW - Ekman flow KW - atmospheric boundary layer KW - roating and stratified fluids Y1 - 2021 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_ems21.pdf UR - https://www.b-tu.de/media/video/Stochastic-modeling-of-transient-surface-scalar-and-momentum-fluxes-in-turbulent-boundary-layers/8c7baf58c040239649fb7c3b2212c1d5 ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko ED - Wagner, Claus T1 - Stochastic modeling and simulation of turbulent boundary layers in annular channel flow using one-dimensional turbulence T2 - STAB Jahresbericht 2021 N2 - In our contribution to the STAB workshop we will present the ODT model formulation with an emphasis on turbulent eddy energetics and map-based advection modeling in radial direction. After that, we will address ODT’s capabilities for simulation of turbulent boundary layers in planar and annular channel flows in terms of conventional turbulence statistics and bulk quantities. Last, we will address the effects of radius ratio and Reynolds number variations. KW - one-dimensional turbulence KW - stochastic modeling KW - spanwise curvature effects KW - radial momentum transport KW - boundary layers KW - coaxial pipe flow Y1 - 2021 UR - https://www.dlr.de/as/desktopdefault.aspx/tabid-128/268_read-1678/ UR - https://www.dlr.de/as/Portaldata/5/Resources/dokumente/veranstaltungen/stab_workshop/STAB-Jahresbericht-2021.pdf VL - 2021 SP - 39 EP - 40 PB - Deutsche Strömungsmechanische Arbeitsgemeinschaft, STAB CY - Göttingen ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko A1 - Lignell, David O. T1 - Stochastic modeling of surface scalar-flux fluctuations in turbulent channel flow using one-dimensional turbulence T2 - International Journal of Heat and Fluid Flow N2 - Accurate and economical modeling of near-surface transport processes is a standing challenge for various engineering and atmospheric boundary-layer flows. In this paper, we address this challenge by utilizing a stochastic one-dimensional turbulence (ODT) model. ODT aims to resolve all relevant scales of a turbulent flow for a one-dimensional domain. Here ODT is applied to turbulent channel flow as stand-alone tool. The ODT domain is a wall-normal line that is aligned with the mean shear. The free model parameters are calibrated once for the turbulent velocity boundary layer at a fixed Reynolds number. After that, we use ODT to investigate the Schmidt (Sc), Reynolds (Re), and Peclet (Pe) number dependence of the scalar boundary-layer structure, turbulent fluctuations, transient surface fluxes, mixing, and transfer to a wall. We demonstrate that the model is able to resolve relevant wall-normal transport processes across the turbulent boundary layer and that it captures state-space statistics of the surface scalar-flux fluctuations. In addition, we show that the predicted mean scalar transfer, which is quantified by the Sherwood (Sh) number, self-consistently reproduces established scaling regimes and asymptotic relations. For high asymptotic Sc and Re, ODT results fall between the Dittus-Boelter, Sh ∼ Re^(4/5) Sc^(2/5), and Colburn, Sh ∼ Re^(4/5) Sc^(1/3), scalings but they are closer to the former. For finite Sc and Re, the model prediction reproduces the relation proposed by Schwertfirm and Manhart (Int. J. Heat Fluid Flow, vol. 28, pp. 1204-1214, 2007) that yields locally steeper effective scalings than any of the established asymptotic relations. The model extrapolates the scalar transfer to small asymptotic Sc ≪ Re_τ^(-1) (diffusive limit) with a functional form that has not been previously described. KW - one-dimensional turbulence KW - stochastic modeling KW - fluctuation modeling KW - passive scalar KW - scalar transfer KW - Schmidt number dependence KW - surface flux Y1 - 2021 UR - https://arxiv.org/abs/2111.15359 U6 - https://doi.org/10.1016/j.ijheatfluidflow.2021.108889 SN - 0142-727X VL - 93 (2022) SP - 1 EP - 19 ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Investigating Schmidt number effects in turbulent electroconvection using one-dimensional turbulence T2 - Proc. Appl. Math. Mech. N2 - Turbulent electroconvection denotes a fluctuating multiphysical flow in which hydrodynamics and electrokinetics interact on multiple scales. The dynamical processes at work are entangled down to the molecular-diffusive scales that are determined by the Schmidt (Sc) and Reynolds (Re) number. Turbulence properties are generally nonuniversal which leads to high numerical resolution requirements. We address the numerical challenges associated with accuracy and feasibility by utilizing a stochastic one-dimensional turbulence (ODT) model. Here, ODT is applied to turbulent Couette flow of dilute electrolytes as canonical problem for turbulent electroconvection. For Sc ⩾ O(10), ODT predicts an increase of the skin friction drag due to electrohydrodynamically (EHD) enhanced small-scale eddy production once the flow is sufficiently turbulent. KW - one-dimensional turbulence KW - stochastic modeling KW - turbulent Couette flow KW - electrohydrodynamic turbulence KW - Schmidt number effects KW - skin friction drag Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1002/pamm.202100147 VL - 21 SP - 1 EP - 3 PB - Wiley CY - Weinheim ER - TY - GEN A1 - Klein, Marten A1 - Maier, Roland Erich A1 - Schmidt, Heiko T1 - Stochastic modeling of transient neutral and stably-stratified Ekman boundary layers T2 - Special Issue: 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM) N2 - Neutral and stably-stratified Ekman boundary layers (EBLs) are numerically investigated with a stochastic one-dimensional turbulence (ODT) model. EBLs achieve the bulk-surface coupling in Earth's atmosphere. They are numerically challenging due to transient and non-universal turbulence properties even at small scales. ODT addresses this problem by distinguishing turbulent-advective from molecular-diffusive transport processes for a vertical column along which all relevant scales of the flow are resolved. We demonstrate the model's capabilities for economical, accurate, and stratification regime independent simulation of EBLs for the wind-turning angle. ODT reproduces and extrapolates reference direct numerical simulation results consistent with observations. We conclude that ODT may be useful for modeling of atmospheric surface layers. KW - one-dimensional turbulence KW - stochastic modeling KW - turbulent Ekman flow KW - roating and stratified fluids KW - transition Y1 - 2021 U6 - https://doi.org/10.1002/pamm.202100146 VL - 21 SP - 1 EP - 3 PB - Wiley CY - Weinheim ER -