Internal strain sensing in carbon fibre composites via digital volume correlation and in situ synchrotron computed tomography
Internal strain sensing in carbon fibre composites via digital volume correlation and in situ synchrotron computed tomography
Digital Volume Correlation (DVC) is a powerful non-intrusive technique capable of volumetric full-field strain mapping of internal structures via displacement tracking. This study, a combination of DVC and in situ Synchrotron Radiation Computed Tomography (SRCT), introduces Silicon Dioxide (SiO2) particles into carbon fibre-reinforced polymers to extend the utilisation of DVC technique to more industrially relevant materials, where detailed sequences of fibre breaks and their accumulation can be identified down to the individual fibre level. The DVC analysis with strain mapping explores the process of strain redistribution longitudinally from fibre breaks that occur under quasi-static tensile loading for various load levels. It is shown that the newly developed material not only exhibits a comparable level of DVC performance to the previous study using BaTiO3 particles, but also attains improved particle distribution with reduced agglomeration. The scale/extent of strain disturbances around individual fibre breaks is compared for multiple sites, suggesting reasonable consistency and confidence in mapping ineffective lengths
Lee, Y.
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Rankin, K.
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Patel, P.
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Basford, P.
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Furtado, C.
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Campos, P.
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Takeuchi, A.
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Uesugi, M.
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Wardle, B.
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Jalalvand, M.
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Mavrogordato, M.N.
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Spearing, S.M.
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Sinclair, I.
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4 August 2023
Lee, Y.
68771a14-4343-4e99-9837-832b10b6b5e7
Rankin, K.
d9516566-0ad8-473d-b99b-4683c663a2b7
Patel, P.
19a7ecc1-0a46-4008-ab0c-5624de4079ce
Basford, P.
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Furtado, C.
8fb60d13-13ac-4f9b-aa47-8a8576594e69
Campos, P.
9c86ff73-905b-4943-a00a-6456794a4412
Takeuchi, A.
fbd6a595-db98-4229-b073-824857cc3137
Uesugi, M.
39c4cddc-692e-46f7-b89c-b9ad12bad142
Wardle, B.
a79e14c1-4da6-49fa-9eaf-d13fd4f0f85e
Jalalvand, M.
21ef0df8-fc7c-4466-a2fc-ee98ed3408a2
Mavrogordato, M.N.
f3e0879b-118a-463a-a130-1c890e9ab547
Spearing, S.M.
9e56a7b3-e0e8-47b1-a6b4-db676ed3c17a
Sinclair, I.
6005f6c1-f478-434e-a52d-d310c18ade0d
Lee, Y., Rankin, K., Patel, P., Basford, P., Furtado, C., Campos, P., Takeuchi, A., Uesugi, M., Wardle, B., Jalalvand, M., Mavrogordato, M.N., Spearing, S.M. and Sinclair, I.
(2023)
Internal strain sensing in carbon fibre composites via digital volume correlation and in situ synchrotron computed tomography.
ICCM 23 International Conference on Composite Materials, The ICC Belfast, Belfast, United Kingdom.
30 Jul - 04 Aug 2023.
12 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Digital Volume Correlation (DVC) is a powerful non-intrusive technique capable of volumetric full-field strain mapping of internal structures via displacement tracking. This study, a combination of DVC and in situ Synchrotron Radiation Computed Tomography (SRCT), introduces Silicon Dioxide (SiO2) particles into carbon fibre-reinforced polymers to extend the utilisation of DVC technique to more industrially relevant materials, where detailed sequences of fibre breaks and their accumulation can be identified down to the individual fibre level. The DVC analysis with strain mapping explores the process of strain redistribution longitudinally from fibre breaks that occur under quasi-static tensile loading for various load levels. It is shown that the newly developed material not only exhibits a comparable level of DVC performance to the previous study using BaTiO3 particles, but also attains improved particle distribution with reduced agglomeration. The scale/extent of strain disturbances around individual fibre breaks is compared for multiple sites, suggesting reasonable consistency and confidence in mapping ineffective lengths
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Published date: 4 August 2023
Venue - Dates:
ICCM 23 International Conference on Composite Materials, The ICC Belfast, Belfast, United Kingdom, 2023-07-30 - 2023-08-04
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Local EPrints ID: 486780
URI: http://eprints.soton.ac.uk/id/eprint/486780
PURE UUID: 05dd86c6-f7c1-4bb6-bdf2-5d8f9197e371
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Date deposited: 06 Feb 2024 17:36
Last modified: 18 Mar 2024 03:57
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Contributors
Author:
Y. Lee
Author:
K. Rankin
Author:
P. Patel
Author:
C. Furtado
Author:
P. Campos
Author:
A. Takeuchi
Author:
M. Uesugi
Author:
B. Wardle
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