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https://knowledgecommons.lakeheadu.ca/handle/2453/5454
Title: | Computational investigations of integrated Vortex-Odor dynamics in the wake of fish for underwater sensing |
Authors: | Kamran, Maham |
Issue Date: | 2025 |
Abstract: | This research investigates the interplay between vortex dynamics and odor transport in undulatory swimming using high-fidelity computational fluid dynamics (CFD) simulations. Building upon initial two-dimensional (2D) analyses, we extend our study to three-dimensional (3D) simulations to quantify odor effectiveness and the role of kinematics and morphology in chemical dispersion. Our results reveal that odor transport is strongly coupled with vortex structures, with convection dominating over diffusion in aquatic environments. Kinematics, rather than body shape, primarily dictate odor transport, with anguilliform swimmers generating broader and more persistent odor trails than carangiform swimmers. Swapping kinematics between Jackfish and Eel models confirms that swimming motion, not morphology, governs odor dispersal. Increasing undulation amplitude enhances odor transport by increasing momentum transfer, reinforcing the dominance of vortex-driven convection. Expanding our study to fish schooling, we analyze odor dispersion across different group configurations. While lateral odor spread intensifies with group size, downstream transport remains largely unaffected beyond a critical distance. Quantitative analysis shows that odor effectiveness decreases linearly with increased schooling, indicating that collective swimming suppresses, rather than enhances, chemical cue propagation. These insights advance our understanding of biological chemosensory mechanisms and inform the design of bio-inspired robotic systems with enhanced chemical sensing and navigation capabilities. |
URI: | https://knowledgecommons.lakeheadu.ca/handle/2453/5454 |
metadata.etd.degree.discipline: | Engineering : Mechanical |
metadata.etd.degree.name: | Master of Science in Mechanical Engineering |
metadata.etd.degree.level: | Master |
metadata.dc.contributor.advisor: | Khalid, Muhammad Saif Ullah |
metadata.dc.contributor.committeemember: | Pakzad, Leila Tarokh, Ali |
Appears in Collections: | Electronic Theses and Dissertations from 2009 |
Files in This Item:
File | Description | Size | Format | |
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KamranM2025m-1a.pdf | 15.97 MB | Adobe PDF | ![]() View/Open |
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