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Compression moulding simulations of SMC using a multi-objective surrogate-based inverse modeling approach
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0000-0002-1033-0244
2009 (English)In: Mechanics of composite materials, ISSN 0191-5665, E-ISSN 1573-8922, Vol. 45, no 5, 503-515 p.Article in journal (Refereed) Published
Abstract [en]

A multiobjective surrogate-based inverse modeling technique to predict the spatial and temporal pressure distribution numerically during the fabrication of sheet moulding compounds (SMCs) is introduced. Specifically, an isotropic temperature-dependent Newtonian viscosity model of a SMC charge is fitted to experimental measurements via numerical simulations in order to mimic the temporal pressure distribution at two spatial locations simultaneously. The simulations are performed by using the commercial computational fluid dynamics (CFD) code ANSYS CFX-10.0, and the multiobjective surrogate-based fitting procedure proposed is carried out with a hybrid formulation of the NSGA-IIa evolutionary algorithm and the response surface methodology in Matlab. The outcome of the analysis shows the ability of the optimization framework to efficiently reduce the total computational load of the problem. Furthermore, the viscosity model assumed seems to be able to re solve the temporal pressure distribution and the advancing flow front accurately, which can not be said of the spatial pressure distribution. Hence, it is recommended to improve the CFD model proposed in order to better capture the true behaviour of the mould flow.

Place, publisher, year, edition, pages
2009. Vol. 45, no 5, 503-515 p.
National Category
Fluid Mechanics and Acoustics
Research subject
Fluid Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-5852DOI: 10.1007/s11029-009-9109-2Local ID: 40a1e3f0-6bf3-11de-9f57-000ea68e967bOAI: oai:DiVA.org:ltu-5852DiVA: diva2:978728
Note

Validerad; 2009; 20090708 (stlu)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Marjavaara, DanielEbermark, SofiaLundström, Staffan
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