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 - 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 - 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 - 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 - TY - GEN A1 - Reible, Benedikt A1 - Hille, Julian F. A1 - Hartmann, Carsten A1 - Delle Site, Luigi T1 - Finite size effects and thermodynamic accuracy in many-particle systems T2 - Physical Review Research Y1 - 2023 U6 - https://doi.org/10.1103/PhysRevResearch.5.023156 SN - 2643-1564 VL - 5 IS - 2 SP - 023156-1 EP - 023156-8 ER - TY - GEN A1 - Reible, Benedikt A1 - Hartmann, Carsten A1 - Delle Site, Luigi T1 - Two-sided Bogoliubov inequality to estimate finite-size effects in quantum molecular simulations T2 - Letters in Mathematical Physics Y1 - 2022 U6 - https://doi.org/10.1007/s11005-022-01586-3 SN - 1573-0530 SN - 0377-9017 VL - 112 IS - 5 SP - 1 EP - 17 ER - TY - GEN A1 - Beisegel, Jesse A1 - Köhler, Ekkehard A1 - Scheffler, Robert A1 - Strehler, Martin T1 - Certifying Fully Dynamic Algorithms for Recognition and Hamiltonicity of Threshold and Chain Graphs T2 - Algorithmica Y1 - 2023 U6 - https://doi.org/10.1007/s00453-023-01107-1 SN - 0178-4617 VL - 85 IS - 8 SP - 2454 EP - 2481 ER - TY - GEN A1 - Vallem, Rishindra A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Numerical modeling and simulation of two-phase internal flow instabilities using Smoothed Particle Hydrodynamics (SPH) T2 - STAB Jahresbericht 2023 KW - Smoothed Particle Hydrodynamics (SPH) KW - Kelvin-Helmholtz instability KW - linear stability analysis KW - two-phase flow Y1 - 2023 UR - https://www.dlr.de/as/Portaldata/5/Resources/dokumente/veranstaltungen/stab_workshop/Jahresbericht2023.pdf UR - https://www.dlr.de/as/desktopdefault.aspx/tabid-128/268_read-1678/ VL - 21/2023 SP - 158 EP - 159 PB - Deutsche Strömungsmechanische Arbeitsgemeinschaft (STAB) CY - Göttingen, Germany ER - TY - GEN A1 - Tsai, Pei-Yun A1 - Schmidt, Heiko A1 - Klein, Marten T1 - Stochastic modeling of asymmetric turbulent boundary layers in annular pipe flow Y1 - 2023 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Tsai_2023_poster_PragueSummerSchoolX.pdf U6 - https://doi.org/10.13140/RG.2.2.18789.78567 N1 - Stochastics in Fluids Summer School and Workshop 2023, Czech Academy of Sciences Institute of Mathematics, Prague, Czech Republic ER - TY - GEN A1 - Klein, Marten A1 - Schmidt, Heiko T1 - Capturing features of turbulent Ekman–Stokes boundary layers with a stochastic modeling approach T2 - Advances in Science and Research N2 - Atmospheric boundary layers (ABLs) exhibit transient processes on various time scales that range from a few days down to seconds, with a scale separation of the large-scale forcing and the small-scale turbulent response. One of the standing challenges in modeling and simulation of ABLs is a physically based representation of complex multiscale boundary layer dynamics. In this study, an idealized time-dependent ABL, the so-called Ekman–Stokes boundary layer (ESBL), is considered as a simple model for the near-surface flow in the mid latitudes and polar regions. The ESBL is driven by a prescribed temporal modulation of the bulk–surface velocity difference. A stochastic one-dimensional turbulence (ODT) model is applied to the ESBL as standalone tool that aims to resolve all relevant scales of the flow along a representative vertical coordinate. It is demonstrated by comparison with reference data that ODT is able to capture relevant features of the time-dependent boundary layer flow. The model predicts a parametric enhancement of the bulk–surface coupling in the event of a boundary layer resonance when the flow is forced with the local Coriolis frequency. The latter reproduces leading order effects of the critical latitudes. The model results suggest that the bulk flow decouples from the surface for high forcing frequencies due to a relative increase in detached residual turbulence. KW - turbulent boundary layer KW - stochastic modeling KW - periodic forcing KW - one-dimensional turbulence KW - rotating flow Y1 - 2023 UR - https://asr.copernicus.org/articles/20/55/2023/ U6 - https://doi.org/10.5194/asr-20-55-2023 SN - 1992-0636 SN - 1992-0628 N1 - This article is part of the special issue “EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2022”. N1 - This research is supported by the German Federal Government, the Federal Ministry of Education and Research and the State of Brandenburg within the framework of the joint project EIZ: Energy Innovation Center with funds from the Structural Development Act (Strukturstärkungsgesetz) for coal-mining regions. VL - 20 SP - 55 EP - 64 ER -