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https://knowledgecommons.lakeheadu.ca/handle/2453/5071
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DC Field | Value | Language |
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dc.contributor.advisor | Runesson, Ulf | - |
dc.contributor.author | Collins, Thomas Sebastian | - |
dc.date.accessioned | 2023-01-31T18:56:08Z | - |
dc.date.available | 2023-01-31T18:56:08Z | - |
dc.date.created | 2022 | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://knowledgecommons.lakeheadu.ca/handle/2453/5071 | - |
dc.description.abstract | This study evaluates the efficacy of an Autonomous Surface Vehicle (ASV) constructed from inexpensive consumer off the shelf components for suitability in surface-based bathymetry of large-scale tailing impounds found in North Western Ontario. The ASV model will be compared with the current human operated, surfaced based model of conducting bathymetric surveys. The craft was field tested in West Oliver Lake, a shallow, warm water lake with a soft bottom. Depth data were collected at speeds of 2.5ms−1 , 3.0ms−1 , 4.0ms−1 , and 5.0ms−1 along the same transects with comparisons made to historical data. Tailings impound surveys when conducted by surface crews pose significant risk to human operators through exposure to hazardous chemicals with both short and long-term effects. Utilizing an autonomous survey vehicle would allow human crews to maintain a safe distance from the tailings impound, potentially reducing interactions with harmful substances present in and around the tailings environment. A Mokai jet kayak was selected as the instrument platform after consideration of its size, propulsion power, and robustness. [...] | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Autonomous surface vehicle (ASV) | en_US |
dc.subject | Bathymetry | en_US |
dc.subject | Geographic information systems (GIS) | en_US |
dc.title | Autonomous surface vehicle for mechanized bathymetric surveys | en_US |
dc.type | Thesis | en_US |
etd.degree.name | Master of Science | en_US |
etd.degree.level | Master | en_US |
etd.degree.discipline | Natural Resources Management | en_US |
etd.degree.grantor | Lakehead University | en_US |
Appears in Collections: | Electronic Theses and Dissertations from 2009 |
Files in This Item:
File | Description | Size | Format | |
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CollinsT2022m-1a.pdf | 40.31 MB | Adobe PDF | View/Open |
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