Developing an Approach to Generate a Watertight Mesh Adaptive with Cavity Monitoring System (CMS)

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The Canadian mining industry is one of the fastest growing sectors in North America. According to Canada'sEconomic Action Plan, the energy and mining sector provides over $30 billion a year in revenue togovernments-money that supports critical social programs such as health care, education, and public pensions.Canada has a global responsibility to develop and utilize its mineral resources sustainably and optimally.One of the important steps of the underground mining projects is the stope monitoring and modeling.Analyzing stope monitoring data and modeling underground excavations is started with mesh generation on thedata point sets. Current mesh generation methods and applications do not work accurately and pose errors inmodeling and design calculation such as mining volume calculation that is very important in underground mineplanning and scheduling.The main goal of this research is proposing an approach for watertight mesh generation for stope monitoringdata. Specifically, a technique will be developed to overcome the identified drawbacks by investing meshgeneration methods.During the course of this project, analytical and numerical methods will be employed to examine the meshgeneration methods for stope monitoring data. To achieve the best approach, the competency of meshgeneration method can be increased by engaging the concavity coefficient of data with the meshing method. Inaddition, an optimization method would be employed to optimize the proposed meshing approach for stopemonitoring data.This project will be completed with guidance from industry experts at Flairbase Inc. It will provide detailedtraining on topics related to underground stope optimization and design and will include as its majordeliverable a computer algorithm that can be applied in underground mines' stope monitorings.