{"id":{"repo_id":"queens","oai_identifier":"oai:queensu.scholaris.ca:1974/14235"},"canonical_url":"https://search.dev.ndltd.org/etd/queens/oai:queensu.scholaris.ca:1974/14235","repository":{"repo_id":"queens","name":"Queens University","base_url":"https://qspace.library.queensu.ca/server/oai/request"},"display":{"title":"Towards Estimating Friction Factors of Mine Drifts from Low Density Point Clouds","abstract":"The standard for estimating roughness for the purposes of underground mine ventilation planning is to choose values found in a variety of textbooks that attempt to match the excavation type. These values are then used in the Atkinson equation made popular in 1935 by McElroy to determine pressure drops and energy requirements. The Darcy-Weisbach equation, developed in the 1950s, has been accepted by most other engineering disciplines but lacks critical information for widespread use in underground mines, namely, the friction factor. As the mining ventilation field moves towards the use of simulations and more refined models, a simple and efficient method for extracting the friction factor is needed. This thesis proposes new LiDAR-based methods for estimating this factor in underground mining tunnels. By using a mobile LiDAR platform low density point clouds are collected then analysed to estimate the friction factor and are compared to those calculated from ventilation data gathered at Barrick Gold Corporation - Hemlo. The two original methods described, in addition to four previously published methods, are shown to be applicable to this 3D point cloud data. The original methods and the IBA method, put forward by Rønn and Skog in 1997, are consistent with both the friction factors already in use at the mine and with the ventilation data collected. Ideas for further improving this approach for friction factor estimation are also suggested.","abstract_html":"The standard for estimating roughness for the purposes of underground mine ventilation planning is to choose values found in a variety of textbooks that attempt to match the excavation type. These values are then used in the Atkinson equation made popular in 1935 by McElroy to determine pressure drops and energy requirements. The Darcy-Weisbach equation, developed in the 1950s, has been accepted by most other engineering disciplines but lacks critical information for widespread use in underground mines, namely, the friction factor. As the mining ventilation field moves towards the use of simulations and more refined models, a simple and efficient method for extracting the friction factor is needed. This thesis proposes new LiDAR-based methods for estimating this factor in underground mining tunnels. By using a mobile LiDAR platform low density point clouds are collected then analysed to estimate the friction factor and are compared to those calculated from ventilation data gathered at Barrick Gold Corporation - Hemlo. The two original methods described, in addition to four previously published methods, are shown to be applicable to this 3D point cloud data. The original methods and the IBA method, put forward by Rønn and Skog in 1997, are consistent with both the friction factors already in use at the mine and with the ventilation data collected. Ideas for further improving this approach for friction factor estimation are also suggested.","abstract_has_math":false,"creators":["Watson, Curtis W. A."],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Mining Engineering","school":null,"contributors":[],"advisors":["Marshall, Joshua A."],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-04-19","date_published":"2016-04-19","updated_at":"2026-07-27T20:35:39Z","subjects":["Point Clouds","Underground Scanning","uGPS","Mine Ventilation","Mining"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1974/14235","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Mining Engineering"]},{"key":"dc:contributor.supervisor","label":"Supervisor","values":["Marshall, Joshua A."]},{"key":"dc:creator","label":"Author","values":["Watson, Curtis W. 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These values are then used in the Atkinson equation made popular in 1935 by McElroy to determine pressure drops and energy requirements. The Darcy-Weisbach equation, developed in the 1950s, has been accepted by most other engineering disciplines but lacks critical information for widespread use in underground mines, namely, the friction factor. As the mining ventilation field moves towards the use of simulations and more refined models, a simple and efficient method for extracting the friction factor is needed. This thesis proposes new LiDAR-based methods for estimating this factor in underground mining tunnels. By using a mobile LiDAR platform low density point clouds are collected then analysed to estimate the friction factor and are compared to those calculated from ventilation data gathered at Barrick Gold Corporation - Hemlo. The two original methods described, in addition to four previously published methods, are shown to be applicable to this 3D point cloud data. The original methods and the IBA method, put forward by Rønn and Skog in 1997, are consistent with both the friction factors already in use at the mine and with the ventilation data collected. Ideas for further improving this approach for friction factor estimation are also suggested."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.A.Sc."]},{"key":"dc:title","label":"Title","values":["Towards Estimating Friction Factors of Mine Drifts from Low Density Point Clouds"]}]}],"canonical_facts":{"dc:contributor.department":["Mining Engineering"],"dc:contributor.supervisor":["Marshall, Joshua A."],"dc:creator":["Watson, Curtis W. A."],"dc:date":["2016-04-14 23:09:19.727"],"dc:date.accessioned":["2016-04-19T21:20:44Z"],"dc:date.available":["2016-04-19T21:20:44Z"],"dc:date.issued":["2016-04-19"],"dc:description":["Thesis (Master, Mining Engineering) -- Queen's University, 2016-04-14 23:09:19.727"],"dc:description.abstract":["The standard for estimating roughness for the purposes of underground mine ventilation planning is to choose values found in a variety of textbooks that attempt to match the excavation type. These values are then used in the Atkinson equation made popular in 1935 by McElroy to determine pressure drops and energy requirements. The Darcy-Weisbach equation, developed in the 1950s, has been accepted by most other engineering disciplines but lacks critical information for widespread use in underground mines, namely, the friction factor. As the mining ventilation field moves towards the use of simulations and more refined models, a simple and efficient method for extracting the friction factor is needed. This thesis proposes new LiDAR-based methods for estimating this factor in underground mining tunnels. By using a mobile LiDAR platform low density point clouds are collected then analysed to estimate the friction factor and are compared to those calculated from ventilation data gathered at Barrick Gold Corporation - Hemlo. The two original methods described, in addition to four previously published methods, are shown to be applicable to this 3D point cloud data. The original methods and the IBA method, put forward by Rønn and Skog in 1997, are consistent with both the friction factors already in use at the mine and with the ventilation data collected. Ideas for further improving this approach for friction factor estimation are also suggested."],"dc:description.degree":["M.A.Sc."],"dc:identifier.uri":["http://hdl.handle.net/1974/14235"],"dc:language.iso":["eng"],"dc:subject":["Point Clouds","Underground Scanning","uGPS","Mine Ventilation","Mining"],"dc:title":["Towards Estimating Friction Factors of Mine Drifts from Low Density Point Clouds"],"dc:type":["thesis"]},"updated_at":"2026-07-27T20:35:39Z"}