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Closing the Gap between Data Model driven Geometry Generation and HiFi CAD for Automatized and Consistent Design Analysis

Siggel, Martin and Reitenbach, Stanislaus and Banovic, Mladen and Pahs, Andreas (2024) Closing the Gap between Data Model driven Geometry Generation and HiFi CAD for Automatized and Consistent Design Analysis. In: AIAA SciTech 2024 Forum. AIAA SCITECH 2024 Forum, 2024-01-08 - 2024-01-12, Orlando, FL, USA. doi: 10.2514/6.2024-2897. ISBN 978-162410711-5.

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Official URL: https://arc.aiaa.org/doi/book/10.2514/MSCITECH24

Abstract

The design process in the aerospace industry typically consists of multiple design phases, in which the design is refined progressively. Advancing from one phase to the next often needs to be done manually, which especially makes the geometric design process difficult to automatize. This paper presents a process that closes the gap between a data model driven (preliminary) geometry generation and an initially manual geometric detail modeling in the high-fidelity phase. It introduces a method to consistently track and persist metadata like face names and colors through a complete geometry processing chain, such that this process can be automatically repeated even with changed design parameters. This process is demonstrated using the first stage of a high-pressure turbine from an aircraft engine. Annulus contour and blade geometries were designed in a standardized process. In addition, the generation of the cavity between the vanes and the rotors was added automatically by means of a CAD environment. The automated geometry generation process is finally demonstrated by a modification of the annulus design parameters, resulting in a geometry variation.

Item URL in elib:https://elib.dlr.de/209849/
Document Type:Conference or Workshop Item (Speech)
Title:Closing the Gap between Data Model driven Geometry Generation and HiFi CAD for Automatized and Consistent Design Analysis
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Siggel, Martinmartin.siggel (at) dlr.dehttps://orcid.org/0000-0002-3952-4659199046800
Reitenbach, StanislausStanislaus.Reitenbach (at) dlr.deUNSPECIFIEDUNSPECIFIED
Banovic, MladenMladen.Banovic (at) dlr.dehttps://orcid.org/0000-0002-9056-3784173499050
Pahs, AndreasAndreas.Pahs (at) dlr.dehttps://orcid.org/0009-0004-3167-5737UNSPECIFIED
Date:4 January 2024
Journal or Publication Title:AIAA SciTech 2024 Forum
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.2514/6.2024-2897
ISBN:978-162410711-5
Status:Published
Keywords:CAD, Geometry, Metadata, Exports, Parametric Modeling
Event Title:AIAA SCITECH 2024 Forum
Event Location:Orlando, FL, USA
Event Type:international Conference
Event Start Date:8 January 2024
Event End Date:12 January 2024
Organizer:American Institute of Aeronautics and Astronautics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Digital Technologies, L - Virtual Engine
Location: Köln-Porz
Institutes and Institutions:Institute of Propulsion Technology
Institute of Software Methods for Product Virtualization
Deposited By: Siggel, Dr. Martin
Deposited On:10 Dec 2024 20:48
Last Modified:24 Aug 2026 15:02

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