Improved image-based deformation measurement for geotechnical applications
View / Open Files
Authors
Stanier, SA
Blaber, J
Take, WA
White, DJ
Publication Date
2016Journal Title
Canadian Geotechnical Journal
ISSN
0008-3674
Publisher
Canadian Science Publishing
Volume
53
Issue
5
Pages
727-739
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Stanier, S., Blaber, J., Take, W., & White, D. (2016). Improved image-based deformation measurement for geotechnical applications. Canadian Geotechnical Journal, 53 (5), 727-739. https://doi.org/10.1139/cgj-2015-0253
Abstract
<jats:p> This paper describes and benchmarks a new implementation of image-based deformation measurement for geotechnical applications. The updated approach combines a range of advances in image analysis algorithms and techniques best suited to geotechnical applications. Performance benchmarking of the new approach has used a series of artificial images subjected to prescribed spatially varying displacement fields. An improvement by at least a factor of 10 in measurement precision is achieved relative to the most commonly used particle image velocimetry (PIV) approach for all deformation modes, including rigid-body displacements, rotations, and strains (compressive and shear). Lastly, an example analysis of a centrifuge model test is used to demonstrate the capabilities of the new approach. The strain field generated by penetration of a flat footing and an entrapped sand plug into an underlying clay layer is computed and compared for both the current and updated algorithms. This analysis demonstrates that the enhanced measurement precision improves the clarity of the interpretation. </jats:p>
Keywords
image analysis, model tests, particle image velocimetry, digital image correlation
Identifiers
External DOI: https://doi.org/10.1139/cgj-2015-0253
This record's URL: https://www.repository.cam.ac.uk/handle/1810/286950
Rights
Licence:
http://www.rioxx.net/licenses/all-rights-reserved
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk