ORCID
- Alison Raby: 0000-0002-8959-0080
Abstract
This study employs the Bubble Image Velocimetry (BIV) technique to characterise the flow velocity of individual extreme waves that overtop sea dikes. Physical experiments were conducted in the small-scale wave flume at the Marine Engineering Laboratory (LIM) of the Universitat Politècnica de Catalunya –BarcelonaTech (UPC). The objective of the experimental campaign was to develop methods to enhance predictive models for wave overtopping volumes of structures with emergent toes. Focused wave groups were used to simulate extreme individual wave overtopping under realistic random sea states. In addition, the campaign prioritized the development of non-intrusive measurement techniques to quantify overtopping volumes and associated flow velocities, leveraging the data gathered throughout the study. To this extent, the present study, in particular, examines the potential of employing the BIV technique for non-intrusive measurements and offers preliminary insights into the characterisation of overtopping flow velocity for the selected structure. The study demonstrates that overtopping flow fields are highly non-uniform, which challenges the assumptions of simplified models such as Boussinesq or non-linear shallow-water models. The BIV technique is therefore crucial in capturing the complex spatial and temporal variations in flow velocities.
Publication Date
2025-05-19
Publication Title
JOURNAL OF COASTAL AND HYDRAULIC STRUCTURES
Volume
5
Issue
44
ISSN
2667-047X
Keywords
Wave Overtopping, Flow velocity, Bubble Image Velocimetry, Sea Dikes, Focused Wave Groups, Physical Modelling
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Altomare, C., Chen, X., Raby, A., Gironella, X., & Suzuki, T. (2025) 'Bubble Image Velocimetry application to flow characterization for incipient overtopping events@ challenges and opportunities', JOURNAL OF COASTAL AND HYDRAULIC STRUCTURES, 5(44). Retrieved from https://pearl.plymouth.ac.uk/secam-research/2118