TY - GEN A1 - Tsai, Pei-Yun A1 - Schmidt, Heiko A1 - Klein, Marten T1 - Modeling simultaneous momentum and passive scalar transfer in turbulent annular Poiseuille flow T2 - Proceedings in applied mathematics and mechanics : PAMM N2 - Simultaneous momentum and passive scalar transfer in weakly heated pressure-driven turbulent concentric annular pipe flow is numerically investigated using the cylindrical formulation of the stochastic one-dimensional turbulence (ODT) model,which is utilized here as standalone tool. In the present study, we focus on the model calibration for heated annular pipes based on recent reference direct numerical simulations (DNS) from Bagheri and Wang (Int. J. Heat Fluid Flow 86, 108725,2020; Phys. Fluids 33, 055131, 2021). It is shown that the model is able to individually capture scalar and momentum transfer, but not both equally well at the same time. We attribute this to less dissimilar scalar and momentum transport in the model at the low Reynolds number investigated. It is argued that the model prefers a fully developed turbulent state due to its construction. Nevertheless, it is demonstrated that ODT is able to reasonably capture the radial inner-outer asymmetry of the scalar and momentum boundary layers which yields better predictive capabilities than wall-function-based approaches. KW - turbulent heat and mass transfer KW - heated pipe flow KW - one-dimensional turbulence KW - stochastic turbulence modeling KW - turbulent drag KW - spanwise curvature effects Y1 - 2023 UR - https://onlinelibrary.wiley.com/doi/10.1002/pamm.202200272 U6 - https://doi.org/10.1002/pamm.202200272 SN - 1617-7061 N1 - Special Issue: 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM) VL - 22 IS - 1 ER - TY - GEN A1 - Gao, Tianyun A1 - Schmidt, Heiko A1 - Klein, Marten A1 - Liang, Jianhan A1 - Sun, Mingbo A1 - Chen, Chongpei A1 - Guan, Qingdi T1 - One-dimensional turbulence modeling of compressible flows. I. Conservative Eulerian formulation and application to supersonic channel flow T2 - Physics of Fluids N2 - Accurate but economical modeling of supersonic turbulent boundary layers is a standing challenge due to the intricate entanglement of temperature, density, and velocity fluctuations on top of the mean-field variation. Application of the van Driest transformation may describe well the mean state but cannot provide detailed flow information. This lack-in modeling coarse and fine-scale variability is addressed by the present study using a stochastic one-dimensional turbulence (ODT) model. ODT is a simulation methodology that represents the evolution of turbulent flow in a low-dimensional stochastic way. In this study, ODT is extended to fully compressible flows. An Eulerian framework and a conservative form of the governing equations serve as the basis of the compressible ODT model. Computational methods for statistical properties based on ODT realizations are also extended to compressible flows, and a comprehensive way of turbulent kinetic energy budget calculation based on compressible ODT is put forward for the first time. Two canonical direct numerical simulation cases of supersonic isothermal-wall channel flow at Mach numbers 1.5 and 3.0 with bulk Reynolds numbers 3000 and 4880, respectively, are used to validate the extended model. A rigorous numerical validation is presented, including the first-order mean statistics, the second-order root mean square statistics, and higher-order turbulent fluctuation statistics. In ODT results, both mean and root mean square profiles are accurately captured in the near-wall region. Near-wall temperature spectra reveal that temperature fluctuations are amplified at all turbulent scales as the effects of compressibility increase. This phenomenon is caused by intensified viscous heating at a higher Mach number, which is indicated by the steeper profiles of viscous turbulent kinetic energy budget terms in the very near-wall region. The low computational cost and predictive capabilities of ODT suggest that it is a promising approach for detailed modeling of highly turbulent compressible boundary layers. Furthermore, it is found that the ODT model requires a Mach-number-dependent increase in a viscous penalty parameter Z in wall-bounded turbulent flows to enable accurate capture of the buffer layer. KW - supersonic turbulent channel flow KW - stochastic turbulence modeling KW - one-dimensional turbulence KW - compressibility effects KW - turbulent boundary layer Y1 - 2023 U6 - https://doi.org/10.1063/5.0125514 SN - 1089-7666 VL - 35 IS - 3 ER - TY - GEN A1 - Gao, Tianyun A1 - Schmidt, Heiko A1 - Klein, Marten A1 - Liang, Jianhan A1 - Sun, Mingbo A1 - Chen, Chongpei A1 - Guan, Qingdi T1 - One-dimensional turbulence modeling of compressible flows: II. Full compressible modification and application to shock–turbulence interaction T2 - Physics of Fluids N2 - One-dimensional turbulence (ODT) is a simulation methodology that represents the essential physics of three-dimensional turbulence through stochastic resolution of the full range of length and time scales on a one-dimensional domain. In the present study, full compressible modifications are incorporated into ODT methodology, based on an Eulerian framework and a conservative form of the governing equations. In the deterministic part of this approach, a shock capturing scheme is introduced for the first time. In the stochastic part, one-dimensional eddy events are modeled and sampled according to standard methods for compressible flow simulation. Time advancement adjustments are made to balance comparable time steps between the deterministic and stochastic parts in compressible flows. Canonical shock–turbulence interaction cases involving Richtmyer–Meshkov instability at Mach numbers 1.24, 1.5, and 1.98 are simulated to validate the extended model. The ODT results are compared with available reference data from large eddy simulations and laboratory experiments. The introduction of a shock capturing scheme significantly improves the performance of the ODT method, and the results for turbulent kinetic energy are qualitatively improved compared with those of a previous compressible Lagrangian ODT method [Jozefik et al., “Simulation of shock–turbulence interaction in non-reactive flow and in turbulent deflagration and detonation regimes using one-dimensional turbulence,” Combust. Flame 164, 53 (2016)]. For the time evolution of profiles of the turbulent mixing zone width, ensemble-averaged density, and specific heat ratio, the new model also yields good to reasonable results. Furthermore, it is found that the viscous penalty parameter Z of the ODT model is insensitive to compressibility effects in turbulent flows without wall effects. A small value of Z is appropriate for turbulent flows with weak wall effects, and the parameter Z serves to suppress extremely small eddy events that would be dissipated instantly by viscosity. KW - shock-turbulence interaction KW - stochastic turbulence modeling KW - one-dimensional turbulence KW - Richtmyer-Meshkov instability Y1 - 2023 U6 - https://doi.org/10.1063/5.0137435 SN - 1089-7666 VL - 35 IS - 3 ER - TY - GEN A1 - Klein, Marten A1 - Schöps, Mark Simon A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko T1 - Numerical simulation and analysis of transient Ekman boundary layers using a stochastic turbulence model T2 - EGU General Assembly 2023 KW - stochastic modeling KW - one-dimensional turbulence KW - turbulent Ekman flow KW - transient boundary layer Y1 - 2023 UR - https://meetingorganizer.copernicus.org/EGU23/EGU23-9116.html U6 - https://doi.org/10.5194/egusphere-egu23-9116 PB - EGU - European Geophysical Union CY - Vienna, Austria 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 - Medina Méndez, Juan Alí A1 - Sharma, Sparsh A1 - Schmidt, Heiko A1 - Klein, Marten T1 - Towards the use of a reduced order and stochastic turbulence model for assessment of far-field sound radiation: low Mach number jet flows T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics KW - turbulent noise sources KW - reduced-order modeling KW - one-dimensional turbulence KW - turbulent jet KW - stochastic modeling and simulation Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 413 EP - 414 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Sharma, Sparsh A1 - Ayton, Lorna A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Estimation of ODT-resolved acoustic sources in high Reynolds number turbulent jets T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics KW - stochastic modeling KW - turbulent jet KW - turbulent acoustic sources KW - noise modeling KW - one-dimensional turbulence Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 414 EP - 415 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Polasanapalli, Sai Ravi Gupta A1 - Klein, Marten A1 - Schmidt, Heiko T1 - SGS modeling in lattice Boltzmann method for non-fully resolved turbulent flows T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics KW - lattice Boltzmann method KW - subgrid-scale modeling KW - model comparison KW - thermal convection Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 363 EP - 364 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Tsai, Pei-Yun A1 - Schmidt, Heiko A1 - Klein, Marten T1 - Effects of Reynolds number on turbulent concentric coaxial pipe flow using stochastic modeling T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics KW - spanwise wall curvature KW - turbulent pipe flow KW - stochastic modeling KW - boundary layer theory KW - one-dimensional turbulence Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 365 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Klein, Marten T1 - Map-based stochastic modeling of multiscale transfer processes in turbulent flows T2 - Book of Abstracts of the 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics N2 - The detailed modeling of turbulent mixing has remained a numerical challenge for a number of applications, ranging from chemically reacting flows to noise prediction in technical flows, and encompassing convection on multiple scales in the geophysical context, among others. Complications arise from the dynamical complexity of turbulence that manifests itself by emergent small-scale flow features, scaling cascades, and intermittency due to prescribed forcings, boundary and initial conditions. In order to robustly predict, for example, the occurrence of catalytic reactions, generation of mixing noise, or the heat transfer across a layer of fluid, it is crucial to represent the physical redistribution processes in the flow with a proper account of participating time and length scales. This yields scale-locality and causality constraints that can usually only be fully addressed by direct numerical simulation (DNS) based on the discretized three-dimensional (3-D) Navier-Stokes equations, which is a very costly undertaking and limited to moderate or low turbulence intensities. In order to over- come the fundamental limitations of statistical turbulence models and numerical cost of DNS, so-called map-based stochastic turbulence models have been developed and increasingly applied to various mutiphysical flows over the last couple of decades. These models utilize onedimensional (1-D) generalized Baker’s maps in order to distinguish advective filamentation from molecular diffusion processes, resolving all relevant scales of the flow along a single physical coordinate. Baker’s maps are probabilistically sampled with respect to size, location, and time of occurrence which introduces dynamical complexity into the bottom-up modeling approach. When the sampling is based on the evolving flow state, a self-contained reduced- order model with predictive capabilities for turbulent flows can be formulated. In the talk, I will summarize the map-based stochastic modeling strategy with an emphasize on the so-called One-Dimensional Turbulence (ODT) model. After that, I will discuss some recent advances in the field, demonstrating the applicability of the approach across flow configurations. I will address in more detail the flow physics representation by means of entrainment and passive scalar mixing in turbulent jets, as well as heat flux and wall shear stress fluctuations in heated channels and stably-stratified atmospheric boundary layers. KW - stochastic modeling KW - one-dimensional turbulence KW - heat and mass transfer KW - boundary layer KW - turbulent mixing Y1 - 2023 UR - https://jahrestagung.gamm-ev.de/wp-content/uploads/2023/05/20230517_BookofAbstracts_final_red.pdf SP - 362 PB - GAMM e.V. CY - Dresden ER - TY - GEN A1 - Glawe, Christoph A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Stochastic deconvolution of wall statistics in Reynolds-averaged Navier–Stokes simulations based on one-dimensional turbulence T2 - Proceedings in applied mathematics and mechanics : PAMM N2 - Reynolds-averaged Navier–Stokes simulation (RaNS) is state-of-the-art for numerical analysis of complex flows at high Reynolds number. Standalone RaNS may yield a reasonable estimate of the wall-shear stress and turbulent drag if a proper wall-function is prescribed, but detailed turbulence statistics cannot be obtained, especially at the wall. This lack in modeling is addressed here by a stochastic deconvolution strategy based on a stochastic one-dimensional turbulence (ODT) model. Here, a one-way coupling strategy is proposed in which a forcing term is computed from the balanced RaNS solution that is in turn utilized in the ODT model. The temporally developing ODT solution exhibits turbulent perturbations but relaxes toward the local RaNS solution due to resolved molecular-diffusive processes. It is demonstrated that the approach is able to recover the distribution of positive wall-shear stress fluctuations in turbulent channel flow. When formulated as post-processing tool, it is suggested that RaNS can be enhanced by ODT providing economical means for local high-fidelity numerical modeling based on a low-fidelity flow solution. KW - stochastic deconvolution KW - Reynolds-averaged Navier-Stokes simulation (RANS) KW - turbulent channel flow KW - turbulent boundary layer KW - one-dimensional turbulence Y1 - 2023 U6 - https://doi.org/10.1002/pamm.202300055 SN - 1617-7061 VL - 23 IS - 3 ER -