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A Simulation App based on reduced order modeling for manufacturing optimization of composite outlet guide vanes

Authors :
Ram Kumar Upadhyay
Christophe Binetruy
Domenico Borzacchiello
Jose Vicente Aguado
Chady Ghnatios
Francisco Chinesta
François Lebel
École Centrale de Nantes (ECN)
Institut de Calcul Intensif (ICI)
Institut de Recherche en Génie Civil et Mécanique (GeM)
Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)
Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)
General Electric [Schenectady]
General Electric
Département Technologie des Polymères et Composites & Ingénierie Mécanique (TPCIM)
École des Mines de Douai (Mines Douai EMD)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Ministère de l'Economie, des Finances et de l'Industrie
Source :
Advanced Modeling and Simulation in Engineering Sciences, Advanced Modeling and Simulation in Engineering Sciences, SpringerOpen, 2017
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

International audience; Composites manufacturing processes usually involve multiscale models in both space and time, highly non-linear and anisotropic behaviors, strongly coupled multiphysics and complex geometries. In this framework, the use of simulation for real-time decision making directly in the manufacturing facility is still precluded nowadays, in spite of the impressive progresses reached in numerical analysis and computer science during the last decade. In this paper, a process-specific simulation tool based on reduced order modeling is introduced, the Simulation App. This concept is presented through a practical case involving a multi-physics and coupled problem describing the manufacturing process of a composite outlet guide vane. We show that several manufacturing settings can be simulated in few seconds with the Simulation App, thus enabling fast process optimization. Finally, the advantages over general-purpose simulation software, in the context of process simulation, are discussed.

Details

Language :
English
ISSN :
22137467
Database :
OpenAIRE
Journal :
Advanced Modeling and Simulation in Engineering Sciences, Advanced Modeling and Simulation in Engineering Sciences, SpringerOpen, 2017
Accession number :
edsair.doi.dedup.....af20b849675f09da184dc427eabacd4c