TY - GEN A1 - Klein, Marten A1 - Zenker, Christian A1 - Hertha, Katja A1 - Schmidt, Heiko T1 - Modeling One and Two Passive Scalar Mixing in Turbulent Jets Using One-Dimensional Turbulence T2 - 14th WCCM-ECCOMAS Congress 2020 N2 - Turbulent mixing of two passive scalars is investigated in a constant-property jets using stochastic one-dimensional turbulence (ODT). Scalars are separately injected by a central round and a surrounding annular jet that issue into a uniform co-flow of low velocity. These scalars are transported downstream and dispersed in radial direction by turbulent advection and molecular diffusion. The jet as well as the turbulent inflow are numerically simulated with ODT as stand-alone tool using a temporal (T-ODT) and spatial (S-ODT) formulation. We show that ODT captures key properties of the turbulent mixing for one scalar by performing individual scalar statistics and for two scalars by computation of joint probabilities. Some limitations of the one-dimensional modeling approach are also discussed. KW - one-dimensional turbulence KW - stochastic turbulence modeling KW - turbulent mixing KW - round jet KW - passive scalars Y1 - 2021 UR - https://www.scipedia.com/public/Klein_et_al_2021a U6 - https://doi.org/10.23967/wccm-eccomas.2020.205 SP - 1 EP - 12 PB - Scipedia 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 - Zenker, Christian A1 - Starick, Tommy A1 - Schmidt, Heiko T1 - Stochastic modeling of three-scalar mixing in a coaxial jet using one-dimensional turbulence T2 - 12th International Symposium on Turbulence and Shear Flow Phenomena (TSFP12), Osaka, Japan (Online), July 19-22, 2022 N2 - Modeling complex mixing processes is a standing challenge for a number of applications ranging from chemical to mechanical and environmental engineering. Here, the gas-phase turbulent mixing in a three-stream concentric coaxial jet is investigated as a canonical problem. Reynolds-averaged Navier–Stokes simulations (RANS) suggest that the gas-phase mixing can be accurately modeled by air doped with passive scalars, for which small-scale resolving numerical simulations are performed with the one-dimensional turbulence (ODT) model as stand-alone tool. We show that both the spatial (S-ODT) and temporal (T-ODT) model formulations yield qualitatively similar results exhibiting reasonable to good agreement with available reference experiments, Reynolds-averaged and large-eddy simulations, as well as mixing models. This is demonstrated for low-order statistics, like the scalar variance and dissipation, but also the two-scalar joint probability density functions that can not be obtained with RANS. Our results suggest that S-ODT has better capabilities than T-ODT to model the mixing processes in the jet which we attribute to the account of local advective time scales. KW - stochastic modeling KW - one-dimensional turbulence KW - concentric coaxial round jet KW - multiple passive scalars KW - turbulent mixing KW - co-flow entrainment Y1 - 2022 UR - http://www.tsfp-conference.org/proceedings/2022/208.pdf UR - http://www.tsfp-conference.org/proceedings/proceedings-of-tsfp-12-2022-osaka.html N1 - Contribution No. 6 of 7 in Session 13C: Jets II SP - 1 EP - 6 ER - TY - GEN A1 - Klein, Marten A1 - Zenker, Christian A1 - Starick, Tommy A1 - Schmidt, Heiko T1 - Stochastic modeling of multi-stream mixing based on one-dimensional turbulence T2 - 77th Annual Meeting of the Division of Fluid Dynamics N2 - Measurements of multiple scalar mixing in a turbulent jet show a strong location dependence of the scalar fluctuations and mixing processes. Mixing is quantitatively described by the state space of scalar fluctuations in terms of a joint probability density function (JPDF). The JPDF evolves in the downstream and radial directions and has non-Gaussian shape which is a burden for mixing modeling since factoring into marginal distribution functions is not permissible. Stochastic simulations based on one-dimensional turbulence (ODT) are able to reasonably reproduce the JPDF and its spatial evolution by a parabolic marching problem that circumvents constraints of the underlying elliptic problem. The model reproduces the inertial-advective range (exponent -5/3) and predicts the emergence of the viscous-advective range (exponent -1) at higher wavenumbers as the Schmidt number increases. The model offers full-scale resolution at affordable cost providing means to reasonably capture state-space statistics of turbulent mixing. KW - turbulent mixing KW - one-dimensional turbulence KW - coaxial jet KW - multi-stream mixing Y1 - 2024 UR - https://meetings.aps.org/Meeting/DFD24/Session/ZC40.4 PB - American Physical Society ER - TY - GEN A1 - Klein, Marten A1 - Zenker, Christian A1 - Starick, Tommy A1 - Schmidt, Heiko T1 - Stochastic modeling of multiple scalar mixing in a three-stream concentric coaxial jet based on one-dimensional turbulence T2 - International Journal of Heat and Fluid Flow N2 - Modeling turbulent mixing is a standing challenge for nonpremixed chemically reacting flows. Key complications arise from the requirement to capture all relevant scales of the flow and the necessity to distinguish between turbulent advective transport and molecular diffusive transport processes. In addition, anisotropic mean shear, variable advection time scales, and the coexistence of turbulent and nonturbulent regions need to be represented. The fundamental issues at stake are addressed by investigating multi-scalar mixing in a three-stream coaxial jet with a map-based stochastic one-dimensional turbulence model. ODT provides full-scale resolution at affordable costs by a radical reduction of complexity compared to high-fidelity Navier–Stokes solvers. The approach is partly justified by an application of the boundary-layer approximation, but neglects fluctuating axial pressure gradients. It is demonstrated that low-order scalar statistics are reasonably but not fully captured. Despite this shortcoming, it is shown that the model is able to reproduce experimental state-space statistics of multi-stream multi-scalar mixing. The model therefore offers physics-compatible improvements in multi-stream mixing modeling despite some fundamental limitations that remain from unjustified assumptions. KW - map-based stochastic advection modeling KW - multiple passive scalars KW - one-dimensional turbulence KW - turbulent jet KW - turbulent mixing Y1 - 2023 U6 - https://doi.org/10.1016/j.ijheatfluidflow.2023.109235 SN - 0142-727X N1 - This article is part of the "TSFP12 Special Issue". VL - 104 SP - 1 EP - 17 ER -