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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ali, MA | - |
| dc.contributor.author | Khan, T | - |
| dc.contributor.author | Khan, K | - |
| dc.contributor.author | Umer, R | - |
| dc.date.accessioned | 2026-06-10T10:54:33Z | - |
| dc.date.available | 2026-06-10T10:54:33Z | - |
| dc.date.issued | 2022-09-01 | - |
| dc.identifier.citation | Ali, M.A. et al. (2022) Micro CT Based Stochastic Design and Flow Analysis of Dry Fiber Preforms Manufactured by Automated Fiber Placement. SSRN Preprint. Available at: https://doi.org/10.2139/ssrn.4182154 | en_US |
| dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/33410 | - |
| dc.description.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. This work investigates the correlation between 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. | en_US |
| dc.description.sponsorship | The authors acknowledge the funding received from Khalifa University of Science and Technology, internal research fund CIRA-2020-007 grant number 8474000275. The authors would also like to thank Dr. Xuesen Zeng from the University of Southern Queensland, Australia for helping in stochastic modeling and Dr. RA Alia for helping in the permeability measurements. | en_US |
| dc.language | en | - |
| dc.language.iso | en | en_US |
| dc.publisher | SSRN | en_US |
| dc.subject | X-ray Computed Tomography | en_US |
| dc.subject | Automated fiber placement | en_US |
| dc.subject | Resin flow | en_US |
| dc.subject | Process Modeling | en_US |
| dc.title | Micro CT Based Stochastic Design and Flow Analysis of Dry Fiber Preforms Manufactured by Automated Fiber Placement | en_US |
| dc.identifier.doi | http://dx.doi.org/10.2139/ssrn.4182154 | - |
| Appears in Collections: | Brunel Composites Centre | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | 1.8 MB | Adobe PDF | View/Open |
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