06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7

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Author: search.filters.author.Beck, AndreaStart date: 2023Institute: search.filters.UBSInstitut.Institut für Aerodynamik und Gasdynamik

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Now showing 1 - 4 of 4
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    A reinforcement learning based slope limiter for second‐order finite volume schemes
    (2023) Schwarz, Anna; Keim, Jens; Chiocchetti, Simone; Beck, Andrea
    Hyperbolic equations admit discontinuities in the solution and thus adequate and physically sound numerical schemes are necessary for their discretization. Second‐order finite volume schemes are a popular choice for the discretization of hyperbolic problems due to their simplicity. Despite the numerous advantages of higher‐order schemes in smooth regions, they fail at strong discontinuities. Crucial for the accurate and stable simulation of flow problems with discontinuities is the adequate and reliable limiting of the reconstructed slopes. Numerous limiters have been developed to handle this task. However, they are too dissipative in smooth regions or require empirical parameters which are globally defined and test case specific. Therefore, this paper aims to develop a new slope limiter based on deep learning and reinforcement learning techniques. For this, the proposed limiter is based on several admissibility constraints: positivity of the solution and a relaxed discrete maximum principle. This approach enables a slope limiter which is independent of a manually specified global parameter while providing an optimal slope with respect to the defined admissibility constraints. The new limiter is applied to several well‐known shock tube problems, which illustrates its broad applicability and the potential of reinforcement learning in numerics.
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    Numerical and experimental studies on high-speed stall phenomena
    (2024) Lutz, Thorsten; Beck, Andrea; Koop, Lars
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    Motivation, structure and goals of the collaborative research centre 1667 : advancing technologies of very low-altitude satellites - ATLAS
    (2025) Fasoulas, Stefanos; Pagan, Adam S.; Traub, Constantin; Annighöfer, Björn; Barz, Stefanie; Beck, Andrea; Cunis, Torbjørn; Dekorsy, Thomas; Essig, Stephanie; Fichter, Walter; Flemisch, Bernd; Herdrich, Georg; Hobiger, Thomas; Kallfass, Ingmar; Kästner, Johannes; Klinkner, Sabine; Lamanna, Grazia; Loehle, Stefan; Pfeiffer, Marcel; Poser, Rico; Roth, Johannes; Saliba, Michael; Schneider, Martin; Sneeuw, Nico; Wagner, Gerd
    The Collaborative Research Centre (CRC) 1667 “Advancing Technologies of Very Low Altitude Satellites-ATLAS” was established in April 2024 with the scientific goal of addressing the fundamental challenges of making satellite operations in Very Low Earth Orbits (VLEO) sustainable. These orbits are beneficial for satellite services that have become indispensable to our modern society. Moreover, access to VLEO offers the opportunity to operate satellites without exposure or contribution to the increasing contamination of traditional orbits with space debris. Seventeen highly interlinked research projects have been selected to investigate and advance accurate numerical and experimental methods for gas-surface interactions, novel concepts utilising the residual atmosphere and minimising the satellite sizes, and mission-related challenges of a selected scenario. In addition, support projects cover topics related to public outreach and academic exchange and assist in achieving the strategic goal of positioning the University of Stuttgart as a key contributor to this internationally very important research area. In summary, the CRC ATLAS aims to constitute a research-oriented profile-building measure at the University of Stuttgart with a strong international reputation.
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    A time-accurate inflow coupling for zonal LES
    (2023) Blind, Marcel P.; Kleinert, Johannes; Lutz, Thorsten; Beck, Andrea
    Generating turbulent inflow data is a challenging task in zonal large eddy simulation (zLES) and often relies on predefined DNS data to generate synthetic turbulence with the correct statistics. The more accurate, but more involved alternative is to use instantaneous data from a precursor simulation. Using instantaneous data as an inflow condition allows to conduct high fidelity simulations of subdomains of, e.g. an aircraft including all non-stationary or rare events. In this paper, we introduce a toolchain that is capable of interchanging highly resolved spatial and temporal data between flow solvers with different discretization schemes. To accomplish this, we use interpolation algorithms suitable for scattered data in order to interpolate spatially. In time, we use one-dimensional interpolation schemes for each degree of freedom. The results show that we can get stable simulations that map all flow features from the source data into a new target domain. Thus, the coupling is capable of mapping arbitrary data distributions and formats into a new domain while also recovering and conserving turbulent structures and scales. The necessary time and space resolution requirements can be defined knowing the resolution requirements of the used numerical scheme in the target domain.