TY - GEN A1 - Klein, Marten A1 - Starick, Tommy A1 - Zenker, Christian A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko T1 - Reduced order stochastic modeling of turbulent mixing based on conservative baker’s maps T2 - Proceedings of the 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements (ETMM-14) N2 - The detailed numerical representation of turbulent mixing processes is a standing challenge for non-premixed chemically reacting flows. The full range of relevant flow scales needs to be captured and it is also necessary to distinguish turbulent advective from molecular diffusive processes in order to represent Reynolds and Schmidt number effects. These requirements are addressed here by utilizing two different map-based stochastic turbulence modeling strategies. The one-dimensional turbulence (ODT) model utilizes event-based turbulence modeling, whereas the hierarchical parcel-swapping (HiPS) model is a fully event-based mixing model. ODT provides full-scale resolution at affordable costs by dimensional model reduction based on the boundary-layer approximation to shear flow. HiPS is far less costly than ODT but currently limited to locally homogeneous isotropic turbulence. The physics-compatible modeling capabilities with respect to phase-space representation of turbulent mixing are demonstrated for two canonical cases using standalone model formulations. KW - turbulent mixing KW - one-dimensional turbulence (ODT) KW - hierarchical parcel swapping (HiPS) KW - stochastic turbulence modeling KW - round jet KW - passive scalar Y1 - 2023 UR - https://etmm.ercoftac.org/etmm/program/conference-program/ UR - https://drive.google.com/file/d/1q2BDOO5bXfqq0Y4z4HCGndiFI033bPyg/view?usp=drive_link SP - 613 EP - 618 PB - ERCOFTAC CY - Barcelona, Spain ER - TY - GEN A1 - Klein, Marten A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko T1 - Stochastic modeling of electrohydrodynamically enhanced drag in one-way and fully coupled turbulent Poiseuille and Couette flow T2 - Technische Mechanik N2 - Joint predictive modeling of hydrodynamics and electrokinetics is a standing numerical challenge but crucial for various applications in electrochemistry and power engineering. The present lack in modeling of electrohydrodynamic (EHD) turbulent flows lies in the treatment of small-scale processes and scale interactions. To overcome these limitations, a stochastic one-dimensional turbulence (ODT) model is utilized. The model aims to resolve all scales of the flow, but only on a notional line-of-sight, modeling turbulent advection by a stochastically sampled sequence of eddy events that punctuate deterministic molecular diffusive advancement. In this study, two canonical flow configurations are investigated that address different coupling strategies and flow physics. First, EHD effects in a variable-density vertical pipe flow of an ideal gas with an inner concentric electrode are investigated with a one-way coupled model formulation. Electric fields are generated by means of a corona discharge and the corresponding effect of a fixed ionic charge density field. Second, in order to reduce physical complexity, EHD effects the turbulent boundary layers in plane Couette flow of an isothermal univalent ionic liquid are investigated with a fully coupled model formulation. Both application cases demonstrate that ODT has predictive capabilities due to multiscale resolution of transport processes. Present results suggest that more expensive fully than one-way coupling of electrokinetics is crucial when charge relaxation times are significantly larger than the mean advection time scale. KW - turbulent drag enhancement KW - electrohydrodynamic turbulence KW - high Schmidt number KW - multiphysical boundary layers KW - one-dimensional turbulence Y1 - 2023 U6 - https://doi.org/10.24352/UB.OVGU-2023-049 SN - 0232-3869 N1 - This article is part of the "Special Issue for CMFF’22". VL - 43 IS - 1 SP - 111 EP - 127 ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Klein, Marten A1 - Schöps, Mark Simon A1 - Schmidt, Heiko T1 - Predicting volatile wind energy: Stochastic forward modeling and machine learning T2 - 86. Jahrestagung der DPG (86th Annual Conference of the DPG), DPG-Frühjahrstagung 2023, (DPG Spring Meeting 2023 of the Matter and Cosmos Section (SMuK), 20-24 March 2023, Technische Universität Dresden Y1 - 2023 UR - https://smuk23.dpg-tagungen.de/programm/assets/verhandlungen-smuk23.pdf UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_dpg23.pdf SN - 2751-0522 SP - S. 343 PB - Deutsche Physikalische Gesellschaft CY - Bad Honnef ER - TY - GEN A1 - Klein, Marten A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko T1 - Simulating Volatile Wind Energy: Stochastic Forward Modeling and Machine Learning N2 - The transformation of the energy sector is based on the integration of various renewable sources, such as wind and solar energy. One of the key challenges for the integration of these sources into the existing power grid is their erratic and sometimes discontinuous availability (volatility). Wind energy is one of the most relevant sources of CO2 neutral electric energy, but volatile due to fluctuating wind fields on multiple scales. This has already been realized so that senors provide real-time information on the scale of individual wind turbines. However, fore- casting remains an unresolved problem since numerical weather prediction models cannot provide the necessary level of detail. New modeling strategies are required that integrate turbine-scale and meso-scale information for accurate site-specific short-term prediction. Present and forthcoming research aims to incorporate fluctuations on multiple levels of fidelity, depending on the abstraction layer KW - AI transfer KW - AI teaching KW - stochastic modeling KW - machine learning KW - wind energy KW - volatility modeling and prediction Y1 - 2022 UR - https://ai-science-atlas.innohub13.de/files/pdf/NSGSimulatingVolatileWindEnergyBTUpdf.pdf UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Klein_poster_KI-Atlas22.pdf PB - Innovation Hub 13, TH Wildau CY - Wildau ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Klein, Marten A1 - Peeters, Jurriaan W. R. A1 - Schmidt, Heiko T1 - Evaluating turbulent channel flows with rough walls : homogeneous roughness parameterization for use in a map-based turbulence model T2 - International journal of heat and fluid flow N2 - This work is focused on modeling the effects of homogeneous roughness on low-order velocity statistics in turbulent channel flows. Hydrodynamic effects due to the roughness are characterized on the basis of volume-averaging theory (VAT) and a discrete roughness element method. This theory exploits the homogeneous character of the roughness in order to reduce the complexity of the flow to its one-dimensional statistics. The formulated VAT-based roughness forcing is best suited for drag dominated surfaces. Turbulence modeling closure is achieved with a map-based turbulence model, the One-Dimensional Turbulence (ODT) model. This avoids the prescription of laws of the wall or other ad-hoc scalings, unlike in more traditional filter-based turbulence models. The modeling framework is applied on selected Reynolds number flows for likewise selected roughness topologies. Results are compared to direct numerical simulation (DNS) data available from the literature. Among others, model results are compared with those of a previously formulated parametric forcing approach (PFA) for roughness drag which involved a costly coefficient calibration linked to the roughness topology model. In ODT, the only calibration process required is the same one involved for the turbulence model parameters, i.e., similar to the ODT model application for smooth-wall flows. Despite all of the inherently implied shortcomings of a 1-D model, some appealing properties of ODT are discussed. Notably, the model is able to predict the roughness function, as well as the wall-normal profile of the Reynolds shear stress across the entire boundary layer thickness. KW - Turbulent channel KW - Roughness KW - ODT KW - Volume-averaging Y1 - 2026 UR - https://www.sciencedirect.com/science/article/pii/S0142727X25003716#d1e18585 U6 - https://doi.org/10.1016/j.ijheatfluidflow.2025.110113 VL - 117, Part B SP - 1 EP - 21 PB - Elsevier BV CY - Amsterdam ER - TY - GEN A1 - Medina Méndez, Juan Alí A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Fractal roughness representation in a stochastic one-dimensional turbulence modeling approach T2 - Proceedings of the 13th International Symposium on Turbulence and Shear Flow Phenomena (TSFP13), Montréal, Canada, June 25-28, 2024 Y1 - 2024 UR - http://www.tsfp-conference.org/proceedings/2023/171.pdf SP - 1 EP - 6 ER - TY - CHAP A1 - Klein, Marten A1 - Glawe, Christoph A1 - Ehlert, Mark Simon A1 - Medina Méndez, Juan Alí A1 - Schmidt, Heiko ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Breitsamer, Christian ED - Wagner, Claus ED - Krenkel, Lars T1 - Stochastic modeling of intermittent inflow turbulence in the atmospheric boundary layer T2 - New Results in Numerical and Experimental Fluid Mechanics XV : contributions to the 24th STAB/DGLR Symposium, Regensburg, Germany, 2024 N2 - Wind turbine predesign is challenged by the representation of site-specific wind conditions. A good deal of that challenge lies in the modeling of the inflow turbulence in the atmospheric boundary layer (ABL). A stochastic one-dimensional turbulence (ODT) model is applied to an idealized neutrally stratified ABL and evolves the instantaneous velocity profile with full-scale resolution. The model is able to reproduce the law of the wall consistently after an initial calibration with the surface drag law. Investigating turbulent time series of the horizontal velocity components it is demonstrated that the model generates physically justified intermittency features with increasing turbulence intensity. KW - Atmospheric boundary layer KW - Intermittency KW - Stochastic modeling KW - Turbulent inflow Y1 - 2026 SN - 978-3-032-11115-9 U6 - https://doi.org/10.1007/978-3-032-11115-9_63 SN - 1612-2909 SP - 684 EP - 693 PB - Springer Nature Switzerland CY - Cham ER - TY - CHAP A1 - Naik Burye, Nishidh Shailesh A1 - Medina Méndez, Juan Alí A1 - Klein, Marten A1 - Schmidt, Heiko ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Breitsamer, Christian ED - Wagner, Claus ED - Krenkel, Lars T1 - Revisiting near-wall modeling of fully developed turbulent flow in concentric annuli T2 - New Results in Numerical and Experimental Fluid Mechanics XV : contributions to the 24th STAB/DGLR Symposium, Regensburg, Germany, 2024 N2 - We report on a systematic study for Reynolds–Averaged Navier-Stokes (RANS) modeling and simulations of turbulent annular pipe flow. Several simulations were performed using the most readily-available RANS models in the open-source library OpenFOAM. A customized 1-D RANS solver was also developed for ease of analysis. The focus of the study is on the reproduction of the mean velocity profile, its maximum, and maximum radial location, as well as modeled low-order fluctuation statistics. The flow in the annular gap is characterized by a radius ratio of 0.1, and a friction Reynolds number equal to 600 that is based on a mean friction velocity. Deviations from the mean velocity profile are observed for all RANS models investigated when compared with Direct Numerical Simulation (DNS) reference data. The representation of the near-wall outer cylinder flow is better than that of the near-wall inner cylinder flow. KW - Annular pipe flow KW - HRN and LRN wall model formulations KW - Wall function KW - Reynolds-averaged Navier-Stokes (RANS) modeling Y1 - 2026 SN - 978-3-032-11115-9 U6 - https://doi.org/10.1007/978-3-032-11115-9_68 SN - 1612-2909 SP - 737 EP - 747 PB - Springer Nature Switzerland CY - Cham ER -