Micro Computed Tomography based stochastic design and flow analysis of dry fiber preforms manufactured by automated fiber placement

Muhammad A. Ali, Tayyab Khan, Kamran A. Khan, Rehan Umer

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The effective design of channels in dry tape preforms is crucial for achieving desired preform permeability for successful resin injection for composites manufacturing using Automated Fiber Placement (AFP) process. Achieving target gaps and their locations in the AFP layup is extremely challenging. This work investigates the correlation between the spatial variability of the preforms and the in-plane permeability using an X-ray Computed Tomography (XCT) based characterization framework. The tomographic images of two different dry carbon tape preforms with different tape widths were used to generate realistic and XCT based stochastic models to be used for numerical permeability predictions. The variability in the tape placement by the robotic head and its effect on preform permeability was also examined through stochastic geometric modeling of the laid preform. A benchmark transient permeability measurement set-up was utilized to obtain experimental in-plane preform permeability through 2D radial mold filling. The in-plane numerical permeability values showed significant scatter, with a coefficient of variance of 75%–130%, which deviated from the experimental measurements by approximately one order of magnitude. These findings strongly re-affirm that the experimental permeability measurement technique based on transient mold filling of dry fiber AFP preforms is complex however, the XCT based stochastic modeling technique is an effective way to estimate the permeability of dry fiber AFP preforms virtually.

Original languageBritish English
Pages (from-to)2075-2090
Number of pages16
JournalJournal of Composite Materials
Volume57
Issue number12
DOIs
StatePublished - May 2023

Keywords

  • automated fiber placement
  • process modeling
  • resin flow
  • X-ray computed tomography

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