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Usage of Data Provenance Models in Collaborative Multi-Disciplinary Aero-Engine Design

Reitenbach, Stanislaus and Vieweg, Maximilian and Hollmann, Carsten and Becker, Richard-Gregor (2020) Usage of Data Provenance Models in Collaborative Multi-Disciplinary Aero-Engine Design. In: Proceedings of the ASME Turbo Expo. ASME. ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, 2020-06-22 - 2020-06-26, Digital. doi: 10.1115/GT2020-14139.

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The collaborative multi-disciplinary design of aircraft engines is a complex and highly iterative process. An essential characteristic of this design process is the involvement of a large number of experts from different disciplines, as well as the usage of numerous tools and workflows. Large amounts of data are produced and need to be exchanged via a multitude of interfaces. Furthermore, the data undergoes various transformations in the course of the design process. Understanding where a certain piece of data originates from and how it is connected to other datasets becomes therefore progressively essential. The purpose of this paper is to present a methodology to apply data provenance models in collaborative multi-disciplinary aero-engine design, supported by an approach for data standardization and identification. Besides the methodology, the software implementation to support this approach is presented in detail, including automated capturing and storage of provenance data, as well as methods for data investigation. In addition the presented methodology is evaluated by means of practical examples from the field of preliminary aero-engine design.

Item URL in elib:https://elib.dlr.de/139361/
Document Type:Conference or Workshop Item (Speech)
Title:Usage of Data Provenance Models in Collaborative Multi-Disciplinary Aero-Engine Design
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:22 June 2020
Journal or Publication Title:Proceedings of the ASME Turbo Expo
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Multi-Fidelity, GTlab, Multidisziplinär, multi-disciplinary, Vorentwurf, pre-design, design, Entwurf, Engine, Data Provenance, Daten Provenienz, Metadata, Metadaten, Datamodel, Datenmodell, collaborative, Kollaborativ
Event Title:ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition
Event Location:Digital
Event Type:international Conference
Event Start Date:22 June 2020
Event End Date:26 June 2020
Organizer:American Society of Mechanical Engineers
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Simulation and Validation (old), L - Virtual Engine and Validation methods (old)
Location: Köln-Porz
Institutes and Institutions:Institute of Propulsion Technology > Engine
Deposited By: Reitenbach, Stanislaus
Deposited On:10 Dec 2020 12:14
Last Modified:24 Apr 2024 20:40

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