Visco-thermo-elastic simulation approach for prediction of cure-induced residual stresses in fiber reinforced composites

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Liquid composite molding (LCM) has established as a high quality manufacturing process for fiber reinforced composite structures. In order to reduce cycle times significantly, novel fast curing matrix resins are being introduced into series production. These put high requirements on process control and part reproducibility. Problems that may be encountered in this context involve process-induced distortion and surface waviness resulting from anisotropic and cure-dependent material properties. Numerical simulations represent a powerful approach to avoid the use of costly trial-and-error methods. For this reason, a simulation approach is being developed which aims at the prediction of residual stresses and accompanying effects on different length scales. Based on a resin characterization comprising reaction kinetics, cure-dependent relaxation modulus as well as thermal expansion and pressure-dependent chemical shrinkage, a generalized MAXWELL model is selected to describe the process-related mechanical behavior of the thermoset. Taking into account the influence of the process parameters on the resin properties enables a detailed analysis of process-property-relationships. By this, the developed simulation approach offers the possibility of a comprehensive analysis of both local and global process-induced phenomena and hence prevention of flaws.

Details

OriginalspracheEnglisch
TitelProceedings ESAFORM 2021
ErscheinungsortLiège, Belgique
ISBN (elektronisch)9782870193020
PublikationsstatusVeröffentlicht - 1 Apr. 2021
Peer-Review-StatusJa

Konferenz

Titel24th International ESAFORM Conference on Material Forming
KurztitelESAFORM 2021
Veranstaltungsnummer24
Dauer14 - 16 April 2021
Webseite
BekanntheitsgradInternationale Veranstaltung
Ortonline
StadtLiège
LandBelgien

Externe IDs

Scopus 85119319800
ORCID /0000-0002-0169-8602/work/142242243
ORCID /0000-0003-1370-064X/work/142243423
ORCID /0000-0002-0820-8936/work/142245859
ORCID /0000-0003-3624-3242/work/142255791

Schlagworte

Schlagwörter

  • Cure Dependence, Experimental, Numerical Modelling