{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/9813"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/9813","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"A GPGPU implementation of the discrete element method applied to modeling the dynamic particulate environment inside a tumbling mill","abstract":"Tumbling mills have been an integral part of the comminution circuit for more than a century. With the advent of better computing, discrete element modeling (DEM) has taken on the challenge to model the dynamic particulate environment inside these devices in the search for understanding and hence improving the process of the size reduction of ore. This process represents a large percentage of the energy consumption of a mine. In this work, a discrete element modeling tool was built on a GPU-based platform to perform simulations on a single commodity hardware PC. With a view to elucidating the governing mechanisms inside such devices, the extreme capabilities of the GPU are utilised to provide performance and accurate simulation. The simulation environment offers control that can never be achieved in an experimental setup. Notwithstanding, when agreement with physical experiment is achieved, confidence can be gained in the computational results. In this work the foundations and framework for a large scale GPU based discrete element modeling tool have been built with an emphasis on strict physics requirements, rather than on performance or appearance. In this regard we demonstrate the validity of the GPU implementation of a Hertz-Mindlin-based contact model.","abstract_html":"Tumbling mills have been an integral part of the comminution circuit for more than a century. With the advent of better computing, discrete element modeling (DEM) has taken on the challenge to model the dynamic particulate environment inside these devices in the search for understanding and hence improving the process of the size reduction of ore. This process represents a large percentage of the energy consumption of a mine. In this work, a discrete element modeling tool was built on a GPU-based platform to perform simulations on a single commodity hardware PC. With a view to elucidating the governing mechanisms inside such devices, the extreme capabilities of the GPU are utilised to provide performance and accurate simulation. The simulation environment offers control that can never be achieved in an experimental setup. Notwithstanding, when agreement with physical experiment is achieved, confidence can be gained in the computational results. In this work the foundations and framework for a large scale GPU based discrete element modeling tool have been built with an emphasis on strict physics requirements, rather than on performance or appearance. In this regard we demonstrate the validity of the GPU implementation of a Hertz-Mindlin-based contact model.","abstract_has_math":false,"creators":["Hromnik, Marius"],"institution":"Department of Physics","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Govender, Indresan","Wheaton, Spencer"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013","date_published":"2013","updated_at":"2026-07-22T22:23:14Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/9813","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Govender, Indresan","Wheaton, Spencer"]},{"key":"dc:creator","label":"Author","values":["Hromnik, Marius"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-11-28T09:56:05Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-11-28T09:56:05Z"]},{"key":"dc:date.issued","label":"Date","values":["2013"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Physics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/9813"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["Tumbling mills have been an integral part of the comminution circuit for more than a century. With the advent of better computing, discrete element modeling (DEM) has taken on the challenge to model the dynamic particulate environment inside these devices in the search for understanding and hence improving the process of the size reduction of ore. This process represents a large percentage of the energy consumption of a mine. In this work, a discrete element modeling tool was built on a GPU-based platform to perform simulations on a single commodity hardware PC. With a view to elucidating the governing mechanisms inside such devices, the extreme capabilities of the GPU are utilised to provide performance and accurate simulation. The simulation environment offers control that can never be achieved in an experimental setup. Notwithstanding, when agreement with physical experiment is achieved, confidence can be gained in the computational results. In this work the foundations and framework for a large scale GPU based discrete element modeling tool have been built with an emphasis on strict physics requirements, rather than on performance or appearance. In this regard we demonstrate the validity of the GPU implementation of a Hertz-Mindlin-based contact model."]},{"key":"dc:title","label":"Title","values":["A GPGPU implementation of the discrete element method applied to modeling the dynamic particulate environment inside a tumbling mill"]}]}],"canonical_facts":{"dc:contributor.advisor":["Govender, Indresan","Wheaton, Spencer"],"dc:creator":["Hromnik, Marius"],"dc:date.accessioned":["2014-11-28T09:56:05Z"],"dc:date.available":["2014-11-28T09:56:05Z"],"dc:date.issued":["2013"],"dc:description":["Includes bibliographical references."],"dc:description.abstract":["Tumbling mills have been an integral part of the comminution circuit for more than a century. With the advent of better computing, discrete element modeling (DEM) has taken on the challenge to model the dynamic particulate environment inside these devices in the search for understanding and hence improving the process of the size reduction of ore. This process represents a large percentage of the energy consumption of a mine. In this work, a discrete element modeling tool was built on a GPU-based platform to perform simulations on a single commodity hardware PC. With a view to elucidating the governing mechanisms inside such devices, the extreme capabilities of the GPU are utilised to provide performance and accurate simulation. The simulation environment offers control that can never be achieved in an experimental setup. Notwithstanding, when agreement with physical experiment is achieved, confidence can be gained in the computational results. In this work the foundations and framework for a large scale GPU based discrete element modeling tool have been built with an emphasis on strict physics requirements, rather than on performance or appearance. In this regard we demonstrate the validity of the GPU implementation of a Hertz-Mindlin-based contact model."],"dc:identifier.uri":["http://hdl.handle.net/11427/9813"],"dc:language.iso":["eng"],"dc:publisher.department":["Department of Physics"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["A GPGPU implementation of the discrete element method applied to modeling the dynamic particulate environment inside a tumbling mill"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:14Z"}