Stochastic multiscale approach to predict failure initiation and progression in composite materials

Seyed Hamid Reza Sanei, Ray S. Fertig

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Presence of large variability in composite properties have resulted in overdesign of composites offsetting their light weight advantage. While such variability can be captured by experimental testing, the prediction of such variability using virtual testing remain a challenge. The variability in transverse composite properties was determined by finite element analysis of computer simulated microstructures. Such microstructures were generated based on the statistics provided by image analysis of actual microstructures. The generated microstructures were modified to match both short and large length scale statistics of actual microstructures. This will enable generation of theoretically infinite realizations of microstructures that are statistically the same but stochastically different (have the same statistics but different configurations). Image-based finite element models were developed based on both pixel-based and morphology-based meshing. The extended finite element method was implemented in ABAQUS to predict failure initiation and progression. The results show that different realizations of microstructures have different transverse strengths but similar elastic properties.

Original languageEnglish (US)
Title of host publication58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624104534
StatePublished - Jan 1 2017
Event58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017 - Grapevine, United States
Duration: Jan 9 2017Jan 13 2017

Other

Other58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017
CountryUnited States
CityGrapevine
Period1/9/171/13/17

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Architecture
  • Civil and Structural Engineering
  • Building and Construction

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  • Cite this

    Sanei, S. H. R., & Fertig, R. S. (2017). Stochastic multiscale approach to predict failure initiation and progression in composite materials. In 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017 American Institute of Aeronautics and Astronautics Inc, AIAA.