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Bayesian Models for Uncertainty Estimation in Aerodynamic Databases of Reusable Launch Vehicles

Krummen, Sven and Schraad, Jan Michael and Ecker, Tobias and Ertl, Moritz and Reimann, Bodo and Klevanski, Josef and Riehmer, Johannes and Eichel, Silas and Sagliano, Marco and Briese, Lale Evrim and Dumont, Etienne (2024) Bayesian Models for Uncertainty Estimation in Aerodynamic Databases of Reusable Launch Vehicles. In: AIAA SciTech 2024 Forum, pp. 1-28. AIAA SciTech Forum and Exposition 2024, 2024-01-08 - 2024-01-12, Orlando, USA. doi: 10.2514/6.2024-0574. ISBN 978-162410631-6.

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Official URL: https://arc.aiaa.org/doi/abs/10.2514/6.2024-0574


The definition of Aerodynamic Databases (AEDBs) is an important yet very complex and labor-intensive task during the design of new aerospace vehicles. This is particularly true for Reusable Launch Vehicles (RLVs), as it has been observed during the development of CALLISTO, a demonstrator for a Vertical-Takeoff Vertical-Landing (VTVL) first stage which is jointly developed, manufactured and tested by DLR, JAXA and CNES. In this paper, we present an Inference-based methodology to define various types of Bayesian models exemplarily for a subset of CALLISTO's AEDB to assess their usability and prediction qualities. First, a short introduction to the underlying aerodynamic dataset will be given which has been aggregated from various Computational Fluid Dynamics (CFD) and Wind Tunnel Test (WTT) campaigns. Then, the different Bayesian models will be defined and their inference results compared against each other, according to common error metrics. It will be shown that, within the limits and assumptions of this study, several types of Bayesian AEDB models provide better accuracy in the prediction of uncertain aerodynamic coefficients compared to classical expert-fitted models for the given CALLISTO dataset. Generally, it can be concluded that Bayesian models are not only a promising new method for the definition of AEDBs, but could also find many potential applications in other engineering domains.

Item URL in elib:https://elib.dlr.de/202266/
Document Type:Conference or Workshop Item (Speech)
Title:Bayesian Models for Uncertainty Estimation in Aerodynamic Databases of Reusable Launch Vehicles
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Krummen, SvenUNSPECIFIEDhttps://orcid.org/0000-0002-4126-688XUNSPECIFIED
Ecker, TobiasUNSPECIFIEDhttps://orcid.org/0000-0001-7134-1185UNSPECIFIED
Ertl, MoritzUNSPECIFIEDhttps://orcid.org/0000-0002-1900-5122UNSPECIFIED
Reimann, BodoUNSPECIFIEDhttps://orcid.org/0000-0001-7765-7295151655900
Klevanski, JosefUNSPECIFIEDhttps://orcid.org/0009-0002-4336-1116151655901
Briese, Lale EvrimUNSPECIFIEDhttps://orcid.org/0000-0003-0900-2005UNSPECIFIED
Dumont, EtienneUNSPECIFIEDhttps://orcid.org/0000-0003-4618-0572UNSPECIFIED
Date:January 2024
Journal or Publication Title:AIAA SciTech 2024 Forum
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-28
EditorsEmailEditor's ORCID iDORCID Put Code
Keywords:CALLISTO, RLV, VTVL, AEDB, Bayes, Uncertainty
Event Title:AIAA SciTech Forum and Exposition 2024
Event Location:Orlando, USA
Event Type:international Conference
Event Start Date:8 January 2024
Event End Date:12 January 2024
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Project CALLISTO [SY]
Location: Braunschweig , Bremen , Göttingen , Köln-Porz , Oberpfaffenhofen , Stuttgart
Institutes and Institutions:Institute of Space Systems > Systems Engineering and Project Office
Institute for Aerodynamics and Flow Technology > Spacecraft, BS
Institute for Aerodynamics and Flow Technology > Spacecraft, GO
Institute for Aerodynamics and Flow Technology > Supersonic and Hypersonic Technology
Institute of Structures and Design > Space System Integration
Institute of Space Systems > Navigation and Control Systems
Institute of System Dynamics and Control > Space System Dynamics
Deposited By: Krummen, Sven
Deposited On:26 Jan 2024 12:40
Last Modified:24 Apr 2024 21:02

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