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

开发一种生成具有空腔监控系统 (CMS) 的自适应水密网格的方法

• 批准号: 515723-2017
• 负责人: Pourrahimian, Yashar
• 金额: $ 1.82万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640568
• 关键词: Developing; Approach; Generate; Watertight; Mesh

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.

加拿大采矿业是北美增长最快的行业之一。根据加拿大的经济行动计划，能源和矿业部门每年为政府提供超过300亿美元的收入--这些钱用于支持关键的社会项目，如医疗保健、教育和公共养老金。加拿大对可持续和优化地开发和利用其矿产资源负有全球责任。地下采矿项目的重要步骤之一是采场监测和建模。分析采场监测数据和模拟地下挖掘是从数据点集的网格划分开始的。现有的网格划分方法和应用不能很好地应用于地下采矿规划和调度中非常重要的建模和设计计算，如采矿量计算等。本研究的主要目的是提出一种采场监测数据的密闭网格划分方法。具体地说，将开发一种技术，通过投资网格生成方法来克服已确定的缺陷。在该项目的过程中，将使用解析和数值方法来检查采场监测数据的网格生成方法。为了达到最佳逼近效果，可以通过将数据的凹度系数与网格化方法相结合来提高网格化方法的能力。此外，还将使用优化方法来优化建议的采场监测数据网格化方法。该项目将在Flairbase公司的行业专家的指导下完成。它将提供与地下采场优化和设计相关的主题的详细培训，并将包括一种可应用于地下矿山采场监测的计算机算法作为主要交付内容。