No description available.

No description available.

No description available.

In an underground coal mine, the measure of a communication system is the coverage area it can provide at a quality that ensures a miner can communicate with other miners in and out of the mine during normal and emergency operations.  The coverage area of a wireless mesh communication system can be calculated using the tool, COMMs, developed and discussed in this document.  This tool can also be used to explore emergency operations, or operations where the mesh infrastructure is degraded or destroyed.  Most often, the communication system is also capable of transmitting data from sensors including a set of sensors, such as Radio Frequency Identification readers, described as the tracking system. An underground tracking system is described as a system that calculates a location in a useful coordinate when a tracked device is underground.  The tracked device is a representative of a miner, group of miners or equipment, depending on state law and the mine's deployment.  The actual location of the miner or equipment being tracked is the Ground Truth Position (GTP) and the tracking system's representation in the same coordinate system at the same time is the Tracking System Position (TSP).  In an excellent tracking system the actual location, GTP, and TSP will be very close to each other.  This work also develops a set of calculated metrics that describe tracking system performance. The Tracking Coverage Area metric refers to the area within the mine that the tracking system either actively measures a tracked device's location or infers it based on the spatial limitations of the mine and information other than active measurements. Average Accuracy is the arithmetic mean of a set of distances from the TSP to the GTP associated with a tracking system. The Average Cluster Radius metric is the average distance a set of TSPs are from their center point, which is determined by the average location of a TSP relative to the GTP.  A 90% Confidence Distance is the distance from a tracked device's actual location (i.e., GTP) that is greater than 90% of the collected distance from GTP to TSP magnitudes ("90th percentile"). Regulatory guidelines in the United States currently define different tracking qualities at locations in the mine.  These can be classified in location categories of Working Face, Strategic Areas, and Escapeways and Travel-ways. All direct paths via escapeway or travel-way from the mine portal to the working face should be simplified into a one-dimensional path that is subdivided by the three regulatory categories.  Each of these subdivisions should be described using the metrics defined above. These metrics can be predicted using COMMs for a tracking system that is utilizing an underground wireless mesh system that uses Received Signal Strength Indicators (RSSI) to calculate the TSP.  Because the tracking system's algorithm to convert RSSI into a TSP is proprietary to the manufacturer, in order to develop predictions the engineer must collaborate with the manufacturer.  In this document, the predictions and calculations were obtained in conjunction with the manufacturer and proved to be accurate describing the tracking system that was designed and tested. / Ph. D.

In an underground coal mine, the measure of a communication system is the coverage area it can provide at a quality that ensures a miner can communicate with other miners in and out of the mine during normal and emergency operations.  The coverage area of a wireless mesh communication system can be calculated using the tool, COMMs, developed and discussed in this document.  This tool can also be used to explore emergency operations, or operations where the mesh infrastructure is degraded or destroyed.  Most often, the communication system is also capable of transmitting data from sensors including a set of sensors, such as Radio Frequency Identification readers, described as the tracking system. An underground tracking system is described as a system that calculates a location in a useful coordinate when a tracked device is underground.  The tracked device is a representative of a miner, group of miners or equipment, depending on state law and the mine's deployment.  The actual location of the miner or equipment being tracked is the Ground Truth Position (GTP) and the tracking system's representation in the same coordinate system at the same time is the Tracking System Position (TSP).  In an excellent tracking system the actual location, GTP, and TSP will be very close to each other.  This work also develops a set of calculated metrics that describe tracking system performance. The Tracking Coverage Area metric refers to the area within the mine that the tracking system either actively measures a tracked device's location or infers it based on the spatial limitations of the mine and information other than active measurements. Average Accuracy is the arithmetic mean of a set of distances from the TSP to the GTP associated with a tracking system. The Average Cluster Radius metric is the average distance a set of TSPs are from their center point, which is determined by the average location of a TSP relative to the GTP.  A 90% Confidence Distance is the distance from a tracked device's actual location (i.e., GTP) that is greater than 90% of the collected distance from GTP to TSP magnitudes ("90th percentile"). Regulatory guidelines in the United States currently define different tracking qualities at locations in the mine.  These can be classified in location categories of Working Face, Strategic Areas, and Escapeways and Travel-ways. All direct paths via escapeway or travel-way from the mine portal to the working face should be simplified into a one-dimensional path that is subdivided by the three regulatory categories.  Each of these subdivisions should be described using the metrics defined above. These metrics can be predicted using COMMs for a tracking system that is utilizing an underground wireless mesh system that uses Received Signal Strength Indicators (RSSI) to calculate the TSP.  Because the tracking system's algorithm to convert RSSI into a TSP is proprietary to the manufacturer, in order to develop predictions the engineer must collaborate with the manufacturer.  In this document, the predictions and calculations were obtained in conjunction with the manufacturer and proved to be accurate describing the tracking system that was designed and tested. / Ph. D.

No description available.

The subsidence characteristics of the Collie Basin sediments have been investigated to provide site specific design criteria for the Wongawilli method of coal extraction. As historical coal extraction (bord and pillar) methods did not generally give rise to large scale subsidence, there were very few details on mining subsidence in the Collie Basin available to base any design methodology on. Consequently, the investigation was conducted on a Green fields basis. Firstly, the mechanisms involved in the development of mining subsidence needed to be investigated and identified. It was then necessary to determine the effects that mining subsidence would have on mine and ground mass (specifically aquitards) structures and surface features. Once these two areas of work were completed, design criteria were formulated to manage the effects of mining subsidence by controlling the critical mechanisms of subsidence development.The results from this study have greatly enhanced the level of understanding of the subsidence mechanisms involved, and allowed for the development of predictive models which can be used for the design of coal extraction by the panel/pillar mining method in the Collie Basin. Mine planning engineers can now use this design information to derive the most cost effective methods for the extraction of coal within the Collie Basin.

Dilution and ore recovery/loss have an important role in calculation of mineral reserves. Each percent increase in dilution and decrease in recovery negatively affects economic value of the reserve. These parameters are mainly controlled by the quality of the mine design and stoping practice. This study provides an approach developed for dilution and recovery/ore loss calculations. The contribution of mine design software (MineSight) and the recent survey technique called Cavity Monitoring System (CMS) were presented in this study. The purpose was to compare the new approach with the old system where the calculations had been done according to some assumptions and to optimize mineral reserve estimation process. Results indicate that the new approach used in reserve estimation process gives ~1.6% closer tonnages to the actual numbers and the grades are both ~1.6% closer to the actual values numbers when compared with the old system.

This paper proposes a numerical finite-element-based model aimed at optimizing narrow-vein stope stability. This model combines empirical and numerical methods to develop a sequence, which may determine an acceptable stope safety factor. A stope stability analysis was conducted through the Mathews stability graph method, which requires two factors: the hydraulic radius (HR) and stability number (N'). The Mathews stability graph method is used to assess the stability of an underground design. Variations in stope dimensions are estimated by changing the HR and Factor A within the N', which is determined through numerical methods. The results of the numerical simulation indicate that the HR increases with an increase in stope dimensions, while Factor A maintains an inverse relationship with the maximum stress induced on the excavation walls. This document demonstrates the potential of combining empirical and numerical methods in stope design optimization, especially when developed in small narrow vein mines.

It is widely recognized that coal is and will continue to be a crucial element in a modern, balanced energy portfolio, providing a bridge to the future as an important low-cost and secure energy solution to sustainability challenges. The designer of coal mining operations needs to simultaneously consider legal, environmental, and sustainability goals, along with traditional mining engineering parameters, as integral parts of the design process. However, traditional coal mining planning seldom considers key “sustainability factors” such as societal impacts; dislocation of towns and residences; physical and economic impact on neighboring communities and individuals; infrastructure concerns; post-mining land use habitat disruption and reconstruction; and long-term community benefit. This work demonstrates the advantage of using a systems engineering approach based on the premise that systems can only be optimized if all factors are considered at one time. Utilizing systems engineering and optimization approaches allows for the incorporation of regulatory and sustainability factors into coal mine design. Graphical approaches, based on the use of GIS tools, are shown as examples of the development of models for the positive and negative impacts of coal mining operations. However, this work also revealed that there are significant challenges inherent in optimizing the design of large-scale surface coal mining operations in Appalachia. Regulatory and permitting programs in the United States, which give conflicting and ill-defined responsibilities to a variety of federal and state agencies, often focus on single parameters, rather than the full suite of desirable outcomes for sustainability, and serve as barriers to innovation. Sustainable development requires a delicate balance between competing economic, environmental and social interests. In the context of coal mining in the U.S., the current regulatory frameworks and policy-guidance vehicles impede this balance. To address this problem, and thus effectively and efficiently provide energy resources while protecting the communities and environments, the U.S. will likely need to fundamentally restructure regulatory programs. Ideally, revisions should be based upon the key concepts of public ecology and allow for a systems engineering approach to coal mine design. / Ph. D.