A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling

Weizhao Zhang, Ramin Bostanabad, Biao Liang, Xuming Su, Danielle Zeng, Miguel A. Bessa, Yanchao Wang, Wei Chen, Jian Cao

Research output: Contribution to journalArticle

Abstract

Carbon fiber reinforced plastics (CFRPs) are attracting growing attention in industry because of their enhanced properties. Preforming of thermoset carbon fiber prepregs is one of the most common production techniques of CFRPs. To simulate preforming, several computational methods have been developed. Most of these methods, however, obtain the material properties directly from experiments such as uniaxial tension and bias-extension where the coupling effect between tension and shear is not considered. Neglecting this coupling effect deteriorates the prediction accuracy of simulations. To address this issue, we develop a Bayesian model calibration and material characterization approach in a multiscale finite element preforming simulation framework that utilizes mesoscopic representative volume element (RVE) to account for the tension-shear coupling. A new geometric modeling technique is first proposed to generate the RVE corresponding to the close-packed uncured prepreg. This RVE model is then calibrated with a modular Bayesian approach to estimate the yarn properties, test its potential biases against the experiments, and fit a stress emulator. The predictive capability of this multiscale approach is further demonstrated by employing the stress emulator in the macroscale preforming simulation which shows that this approach can provide accurate predictions.

LanguageEnglish (US)
Pages15-24
Number of pages10
JournalComposites Science and Technology
Volume170
DOIs
StatePublished - Jan 20 2019

Fingerprint

Preforming
Carbon fiber reinforced plastics
Thermosets
Computational methods
Carbon fibers
Yarn
Materials properties
Experiments
Calibration
Industry

Keywords

  • Bayesian calibration
  • Gaussian processes
  • Multiscale simulations
  • Preforming
  • Prepreg

ASJC Scopus subject areas

  • Ceramics and Composites
  • Engineering(all)

Cite this

Zhang, Weizhao ; Bostanabad, Ramin ; Liang, Biao ; Su, Xuming ; Zeng, Danielle ; Bessa, Miguel A. ; Wang, Yanchao ; Chen, Wei ; Cao, Jian. / A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling. In: Composites Science and Technology. 2019 ; Vol. 170. pp. 15-24.
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A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling. / Zhang, Weizhao; Bostanabad, Ramin; Liang, Biao; Su, Xuming; Zeng, Danielle; Bessa, Miguel A.; Wang, Yanchao; Chen, Wei; Cao, Jian.

In: Composites Science and Technology, Vol. 170, 20.01.2019, p. 15-24.

Research output: Contribution to journalArticle

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AU - Zhang, Weizhao

AU - Bostanabad, Ramin

AU - Liang, Biao

AU - Su, Xuming

AU - Zeng, Danielle

AU - Bessa, Miguel A.

AU - Wang, Yanchao

AU - Chen, Wei

AU - Cao, Jian

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