STOchastic Multi-scale Modeling Methodologies for the Assessment of failure performance of Composite materials - STOMMMAC

Objectives
Although composite materials offer many advantages, such as high strength-to-weight ratio, enhanced potentials for material and structure design, and many others, their potential is not realized in practice because their properties after manufacturing suffer from scatter, leading to over-designed structures. The aim of STOMMMAC is to develop an integrated stochastic multi-scale approach able to predict the failure probability of composite materials using uncertainty quantification (UQ) of the micro-scale constituents and microstructure, and by propagating them up to the macro-scale.

Publications 

  • An incremental-secant mean-field-homogenization method with second statistical moments for elasto-visco-plastic composite materials, Ling Wu  (ULiege), Laurent Adam (e-Xstream), I. Doghri (e-Xstream), Ludovic Noels (ULiege), Mechanics of Materials 114 (2017) 180–200
  • From SEM images to elastic responses: a stochastic multiscale analysis of UD fiber reinforced composites, Ling Wu (ULiege), Chi Nghia Chung (JKU),  Zoltan Major (JKU), Laurent Adam (e-Xstream), Ludovic Noels (ULiege), Composite Structures, Revised version Submitted.
  • Micro-mechanics based order reduction for uncertainty analysis of UD-fiber reinforced composites. Ling Wu (ULiege), Laurent Adam (e-Xstream), Ludovic Noels (ULiege), In Preparation.


Project Details:
In order to propagate micro-structural uncertainties to the macro-scale STOMMMAC develops an original stochastic mean-field homogenization (MFH)  able to predict the probabilistic distribution of the material response at an intermediate scale, called the mesoscale. The method will be able to predict the probability distribution of:

  • The properties of the homogenized composite material;
  • The stress/strain state reached in each constituent;
  • Failure states from the stress/strain level distribution in the micro-constituents.

The distribution of the meso-scale material properties can then be exploited at the macro-scale, i.e. the structural level, to study composite structures in a non-deterministic way. The project focuses on two types of composite materials, namely short fiber reinforced polymers (SFRP) and continuous fiber reinforced polymers (CFRP), as well as two performance indicators: isothermal static and fatigue failure (high number of cycles and low frequency loads).

Project Details

Publication date 2018/02/21
Call Topic Integrated Computational Materials Engineering (ICME) (Call 2014)
Duration in months 36
Partners
  • e-Xstream engineering, MSC Software Belgium S.A., Belgium (Coordinator)
  • University of Liège (ULiege), Belgium (Partner)
  • University of Luxembourg (UL), Luxembourg (Partner)
  • Johannes Kepler Universität (JKU), Austria (Partner)
  • ACTION COMPOSITES GmbH (AC), Austria (Partner)
  • BATZ, S.Coop, Basque Country,, Spain (Partner)
Funded by
Total project cost € 1,579,214
Contact e-Xstream engineering, MSC Software Belgium S.A.

Axis Park – Building H
9, Rue Emile Francqui
B-1435 Mont-Saint-Guibert
Belgium

R&D Director Laurent ADAM
Email:
Link to ERA-LEARN View on ERA-LEARN website