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By Marco Quirion

The Daniel-Johnson dam, formerly named Manicouagan-5 (Manic-5), is located 800 km northeast of Montreal (Quebec) in Canada. This is the largest multiple-arch concrete dam in the world consisting in 13 arches and 14 buttresses. Since its construction in 1969, various type of cracks have appeared on both downstream and upstream faces of almost all the arches of this concrete dam. As a part of the Daniel- Johnson’s dam safety assessment program, Hydro-Québec is currently performing structural analysis of the dam with advanced numerical models to better understand and predict the dam behaviour. Because the buttresses transmit all the arch loads to the rock mass, determination of the properties of the dam foundation should not be neglected in dam global safety analysis and also to insure that reliable input parameters are used in the dam numerical simulations. This paper summarizes the past and the more recent investigations of this foundation used to assess its safety and stability. Moreover, the use of rock mass classification to estimate the deformation modulus, based on empirical equations, gives values in the range of 30 to 40 GPa that are higher than expected values. Using those values in the numerical simulations for dam structural analysis gives an excellent correlation with displacements monitoring of the buttresses.

Jan 1, 2015

Dartbrook mine is a new greenfields thermal coal longwall mine located n the Upper Hunter Valley ten kilometres north of Muswellbrook Figure 1). Construction began in April 1993 with coal extraction starting n October 1994. Longwall production is scheduled to commence in the first quarter of 1996 with production expected to exceed 3.5 million onnes per annum. The permanent workforce will number 150 full-time ,mployees and productivity rates will be 22 000 per employee per annum m a ROM basis. Being a greenfield site Dartbrook has had the opportunity to develop and operate the mine using the best practices and latest technology available to meet high standards of safety, quality and production.

Jan 1, 1995

By D Bruce

OZ Minerals’ Carrapateena mine is a Sublevel cave mine located in South Australia, approximately 160 km north of the regional centre of Port Augusta. Carrapateena commenced underground development in 2016, with production commencing in 2019 and ramping up to 4.25 Mtpa by December 2020. In pursuit of continual improvement, the Carrapateena mining team sought to identify how it could better interrogate its current productivity levels and its drivers (root causes). During this process the team were confronted by a disconcerting number of different opinions (which often conflicted) on our actual productivity performance which led to a need for review. Although reliable data and a well-designed time utilisation model (TUM) existed, it was still unclear what actions needed to be put in place to improve productivity. This was for the following reasons: • Data sources were disparate unless significant effort was applied to compile them. • Data sources were not available in a format that could be easily viewed or analysed. • General understanding of the data which was collected and how it could be used was poor. • Process of regularly analysing performance and forming tangible actions to improve was lacking rigour. A project was then started with the goal to fix the areas stated above. An initial requirements gathering exercise was undertaken to identify key data sources for site which returned a staggering 42 known systems which were then shortlisted to the key systems that contained operational data and could generate tangible improvements when analysed. This paper discusses the approach to selecting the OZ Minerals Insights Hub as the chosen platform, and the effort and collaboration between cross-functional departments that was involved in transforming the data so it could be displayed in a useful way. The data sources identified included a fleet management system, two planning databases, a control system historian, and a mobile fleet machine data system. New processes were also introduced to digitally capture daily commentary; this was achieved utilising SharePoint Forms. Data pipelines were then developed in the Insights Hub platform to automate the ingestion and transformation of the raw mining data into curated data models for end user consumption. Tableau dashboard packages have been created to support facilitation of short interval control, daily review meetings, and weekly review meetings as well as data analysis of key equipment and locations. These dashboards visualise the mining data models in a form that provides the user a clear picture of what has occurred, why it has occurred, and where to focus improvement efforts. This has resulted in a team which is more accountable, more equipped to assess the root cause of performance, and more regularly able to make data driven decisions. The next step? To build this out from Mine to Mill and create a data indexing tool which will drive self-service reporting, a data agnostic platform and predictive tools that help our people continue to be one step in front.

Mar 29, 2023

By G. A. Witwicki

"The Thyssen Mining Group of Companies has successfully applied ground freezing technology to numerous projects throughout Europe and North America for over 100 years. Recently, the aspect of data acquisition and data verification has received greater focus.Thyssen Mining has been engaged in several relatively deep shaft sinking projects over the past five (5) years, all of which have required ground freezing to successfully sink through water bearing rock. To safely and economically sink through a quantity of water similar to Saskatchewan’s Potash Mines, it is imperative to understand freeze wall thickness and growth rate.Critical to understanding freeze wall thickness and growth rate, is the collection of accurate data as well as the interpretation of those data. The data can then be utilized to gain a better understanding of the freeze wall growth rate in active projects as well as to provide data to be utilized in modeling for future projects.This paper elaborates on the installation and operation of the data acquisition system utilized at the Newmont Leeville project, Nevada’s first frozen shaft project. In addition, this paper elaborates on the methodology developed by Thyssen Mining to manipulate the freeze wall data derived through the data acquisition system.The successful incorporation of the new system of collection and analysis of freeze wall data for the Leeville Project has given Thyssen Mining a high degree of confidence in the understanding, as well as prediction, of the ground conditions during shaft sinking.This paper will include:•,A brief description of ground freezing and its objective;•,An overview of previous data acquisition methods employed;•,Current data acquisition methods;•,Installation requirements; and,•,Data manipulation and presentation methods."

Jan 1, 2015

By I Canbulat, J Emery, L Yao and C Zhang

This paper documents a process of data analytics and machine learning applied to coalmine roof convergence data. It follows a publication documenting the formation of the database. For each set of analyses Python scripts were utilised to extract data from an SQL database, with subsequent analyses also executed in Python, utilising open-source tools such as scikit-learn. Preliminary analyses with classic machine learning algorithms included multiple logistic regression, K-nearest neighbours, decision tree, random forest, support vector machine, kernel support vector machine, artificial neural network (ANN), naïve Bayes and multiple linear regression. Results indicated that relationships were complex and non-linear, with the artificial neural network most suitable. An ANN model was then refined through a standard process of hyperparameter optimisation and data augmentation to arrive at a final model. Due to the black box nature of the ANN further insight into how the parameters interacted was sought and found with Shapley additive explanations (SHAP values). SHAP values utilise Game Theory, where each input parameter or feature is a ‘player’ while the data set is the ‘team’. The SHAP value is the impact of each player on the target value, essentially establishing the contribution of each input parameter. The results from all analyses are delivered in the paper, together with insights, applications, strengths, and limitations of the methodology.

Nov 29, 2022

By Y Tang, G Si

The analysis of rock fragment sizes plays a pivotal role in various stages of geotechnical and mining engineering. Traditional case-based methods often falter in addressing the variability in rock fragment images due to fluctuating geological conditions and imaging environments. To counter this challenge, AI-based models necessitate training on expansive and diverse data sets, encompassing a wide range of conditions and fragment types. However, the creation of such data sets is often hampered by financial and environmental constraints. This paper introduces a novel approach for rock fragment recognition, which leverages the power of AI for data augmentation, automated annotation and prediction. The methodology integrates three key components: Style-Based Generator Architecture for Generative Adversarial Networks (StyleGAN) for data augmentation, the Segment Anything Model (SAM) for automated annotation, and the multiscale version of you only look once (YOLO-MS) real-time instance segmentation model. The proposed method begins by training a new StyleGAN model using the original data set. It then delves into exploring the latent vectors of different rock fragment images to generate specific ‘style representations’. These latent vectors form the foundational elements of each image in a high-dimensional space, encapsulating critical features such as size, shape, texture, and colour variations. The next step involves conducting quality checks on the generated images to ensure their realism and suitability as training data. Subsequently, the augmented image set is annotated using modified SAM module, followed by training the YOLO-MS real-time instance segmentation model. The performance of this model, trained on the augmented data set, is compared with a model trained on the original data set, particularly in terms of generalisation abilities in new scenarios. The results exhibit a significant enhancement in accuracy, robustness, and generalisability of the model trained on the augmented data set, underscoring the potential of StyleGAN as a powerful tool for data augmentation in geotechnical engineering image analysis.

Sep 1, 2024

By Dan Chun

Abstract-To facilitate the efficient handling of large volumes of information generated by logging exploration drill cores, a computer data bank system (GEOBANK) has been developed to store and retrieve the normally difficult to handle geologic information as well as the physical testing data. The data bank systematized the logging of drill core by first developing a standard list of adjectives or descriptors (with the corresponding assigned numerical codes) for the various stratigraphic categories that are also assigned numerical codes. The system uses the "floating-slot" concept and handles the data bank with one single input form.

Jan 9, 1978

By Márcio Aurélio dos Santos

A Automação Industrial utiliza de forma intensiva os mesmos equipamentos e softwares de TI como servidores, historiadores, switches, firewall, dentre outros. No entanto, são poucas as áreas de automação que aplicam de forma eficaz todos os controles e cuidados que esses ativos requerem. Neste cenário, a garantia de altos níveis de disponibilidade dos sistemas de automação inicia-se pelo ambiente físico no qual tais sistemas estão instalados. É comum a improvisação de ambientes inadequados dentro das áreas industriais ou a instalação em subestações elétricas que não foram construídas com o rigor necessário para receber os ativos de TI Industrial utilizados nos sistemas automação. A solução para manter elevados os índices de disponibilidade destes ativos é, sem dúvida, instalá-los em Data Centers, comumente utilizados nas áreas de TI, o que é facilmente justificável pelo fato de que a indisponibilidade dos ativos de automação representa um impacto maior aos resultados das indústrias ao se comparar com a indisponibilidade dos ativos de “TI Corporativa”. Assim, este trabalho conceitua um ambiente de Data Center, discute as particularidades relacionadas à Automação Industrial (projetos de cabeamento estruturado e as interligações entre os níveis 1 e 2 de Automação) e apresenta as estratégias que a Samarco Mineração está adotando com relação ao tema.

Jul 30, 2018

By Reinaldo J. Villa, Joshua C. Adams

The I-395/SR-836/I-95 reconstruction project is an $818-million design-build construction effort that includes construction of viaduct, segmental and signature bridges in Miami leading into Miami Beach in Florida. Based on the load testing performed during the design phase, the design-build team determined that conventional driven pile and drilled shaft foundations were not feasible for support of segmental and signature bridges. Due to the weak limestone formation and successful use of auger cast-in-place (ACIP) piles in the Downtown Miami area on commercial developments, ACIP piles were selected as a foundation system to support bridges. This is the first time in history where the bridges will be supported by ACIP pile foundations in an interstate highway in the State of Florida. The design build-team worked closely with the Florida Department of Transportation to develop requirements for the load test program. The paper will provide an overview of the geotechnical data collected, results of dynamic/bi-directional load testing performed on test piles, data collected, installation of piles, and lessons learned. The load test program included a total of fifteen test piles with dynamic, bi-directional, and lateral load testing on 30 and 36-inch diameter ACIP piles and instrumented with thermal integrity profiling wires.

Sep 8, 2021

By S Versace, D Arnott, D Bojcevs, A Shaw

The George Fisher deposit is a significant sediment hosted silver-leadzinc resource located 2 km north of the Hilton Mine in NW Queensland. The George Fisher feasibility project involved the completion of underground and surface drilling programs to delineate Measured and Indicated Resource which could be converted to an Ore Reserve through mining and commercial studies. The geological information which was collected and used for the feasibility study included a major program of diamond drilling, predominantly from underground sites, but with some drilling also completed from surface. All drillcore was geologically and geotechnically logged, sampled and assayed. Data was also collected from underground cross-cut and drive development which was mapped for rocktype, ore distribution, structure and geotechnical condition. This new geological data, generated during the Pre-Feasibility and Feasibility stages, was combined with results of all previous drilling campaigns in the George Fisher area to produce a comprehensive database on which geological modelling and Resource estimation could be based. To allow fast and accurate collection and utilisation of data from the drilling program, digital collection processes were used where possible. This resulted in rapid data entry into the project database, significantly enhanced data quality, 100 per cent data ownership within the project team and increased productivity levels. Processes used during the project data collection program are described, lessons learned are related and suggestions for ænext timeÆ are listed using the benefit of hindsight.

Jan 1, 1998

By Jeonghwan Kim

Intelligent Excavation System (IES) has been considered to be one of the desirable solutions to improve the productivity, quality and safety of the current earthwork processes. IES is composed of various hardware and software modules including task planner (work command generator), local and global work environment sensors, GPS and other sensors to acquire the excavator?s status, robotic controller and electronic valves, and the manipulator (excavator). A data communication manager was required to coordinate the signal or data-flow in between these modules considering the operational status of IES such as; excavation start/completion, truck detection, terrain model update, emergency stop, local sensing, GPS/motion sensor data handling, and so on. This paper presents the role and functions of this data communication manager. After every possible operational status of IES operation was identified, a protocol of each communication process in the form of string-type was made. The components of IES are connected with either wired or wireless network. Therefore, they can communicate with the manager using socket (TCP/IP) communication. The data communication manager is also capable of accessing a web-based project management information system, which constantly updates the performance of excavation robot to online database.

Aug 1, 2013

By D W. Evans

Research into the dynamic properties of ground support elements continues to grow at a global level, given the increasing importance of this field of application within underground hard rock mining. Measuring the mechanical response of such elements under the rapid onset of simulated rock burst loads forms the basis for this experimental work, typically utilising gravitational drop testing methods. This field of research is fundamentally driven by an increasing need for dynamic performance data, given the constant evolution of rock bolting product designs, materials selection, combination testing and specific application needs based on ground types and loading scenarios. A smaller number of globally recognised dynamic test facilities have predominantly lead research within this arena, typically in association with academic institutes, larger industry groups and government research institutes. However, due to the increasing requirement for dynamic performance data, additional facilities have now emerged in order to satisfy the overall demand for test work. These newer facilities are more typically associated with suppliers to the underground hard rock industry, with experimental designs looking to replicate, at least in part, the work of the primary facilities. For standardisation, repeatability and calibration purposes, the cross validation of test data between primary and secondary facilities becomes an obvious and important consideration across this field of research. This paper outlines the development of a new dynamic drop test facility for testing rock bolts, including the structural design and associated high speed data capture system. Based on the utilisation of identical bolt types, material grades, anchoring systems and decoupled ‘free-lengths’, comparative data has been generated to provide cross validation of the new test facility against data generated by a globally recognised primary facility. The cross validation of data provides increasing confidence in the repeatability and accuracy of the new facility as activity continues towards the provision of further experimental test work.

Nov 29, 2022

By Aaron Samuel Young, Hiago Antunes Amador de Oliveira, William Pratt Rogers

Low commodity prices and lack of new high-grade deposits are pushing the mining industry for innovation. Lean mining has been vastly discussed in the past decades as a way to continuously improve mining efficiency. Although very theoretical, lean mining presents a set of new solutions enabled by the digital transformation that the mining industry is going through. This paper proposes a framework for a short interval control system with the purpose to allow timely responses by front line supervisors upon operational deviations. In the first part, the author briefly reviews concepts of short-range planning and lean mining. Then, the materials and methods used for the development of the short interval control system are discussed. Finally, alpha trial results are presented, and next steps discussed.

Oct 3, 2019

By Michael Arnold, Jignyash Manyam, Yoav Rappaport

The USACE required construction of over 13 miles of cutoff wall at an average depth of 65 feet for the Herbert Hoover Dike (HHD). To meet project requirements, to provide quality control and make sound operational decisions, automated data capture, retention and visualization is crucial. Accurate and complete data management allows the authors to deliver critical business insights and to improve operational efficiencies. The author’s understood the necessity of capturing all their data, and efficiently processing and displaying it for multiple stake holders, for both internal and external purposes. The authors realized early in the project life cycle that data ownership and management is one of the fundamental features of the construction process. The authors developed their own software and use two in house applications; WEB-BGM online portal and, b-project which store rig production information combined with field quality control. b-project is used to create and deliver the Enterprise Database (EDB) to the USACE. Another biproduct of capturing the production data is the generation of the Geographic Information Systems (GIS) and also business analytics visual interactive display, developed through Microsoft Power BI. The paper focuses on the business process workflow and various technologies employed and lessons learned from the field operator perspective to achieve higher returns on business software operations.

Oct 1, 2022

By S. Möllerherm

"The evaluation of data and information provided by the existing traditional indicators in sustainability assessments is most important. Therefore the Institute of Mining Engineering I from the RWTH Aachen University developed indicators and an assessment system for the mineral raw materials industry on operation, company and sector level on behalf of the Federal Ministry of Economics and Labour (Bundesministerium für Wirtschaft und Arbeit, BMWA) and the Federal Institute for Geosciences and Natural Resources (Bundesanstalt für Geowissenschaften und Rohstoffe, BGR). In the course of the development of indicators for the raw materials industry quality indicators on different levels of the sustainability assessment procedure have been identified and developed. The following paper describes some of the results focussing on the development and integration of quality indicators into sustainability assessment systems."

Jan 1, 2005

By Rudolf E. Greuer, Linneas W. Laage, Xinton Chang

Data or input files are used to describe the mine's ventilation system and physical characteristics necessary for ventilation calculations as well as the physical or mechanical disturbance to be modeled and simulated Data files are organized into lines of categories or groups of information Each line contains multiple sets of information or data items Data lines are read by the program, and the data items provide information to the program variables The data file is in American Standard Code for Informa¬tion Interchange (ASCII) format, sometimes called a DOS text format Creation or modification of a data file is accomplished with text editor software Most word pro¬cessors are also capable of making the required ASCII type files A sample data file and its associated output are included in appendix B. When selecting software for editing the data files, the user should be aware that the software will also be used for viewing the output of the simulation The output file can be quite large (several megabytes), if a lengthy simulation is performed The output can be sent to a printer for a hardcopy fisting, however, the user should also be aware that most printers currently used with PC's print at rates of 100 to 300 characters per second and large output files may take several hours to print Viewing the output with a text editor can save much time and paper DATA FILE MANAGEMENT The data files describing the event and mine to be simulated can reside either on a floppy disk or in a directory on the hard disk drive When the program starts, the user is prompted for the data file location and name The user response is in the form of a standard DOS path and file name For example, if the data file is on a floppy disk located in drive B and the disk has a directory MYMINE with the data file MYDATA DAT in that directory, then, at the prompt

Jan 1, 1990

By Christoph Muller, Geoffrey Liggins, Mohan Hensman

Modern commercial blasting is as much a technical process as it is a business one. As with most processes both aspects of blasting are driven by and generate new data. The time-critical nature of commercial blasting in mining and construction projects, dictate the timely exchange of information so as not to impede production or commerce. Up-to-date information about the blast to be undertaken can help suppliers: meet customers’ expectations to address challenging ground conditions; react to a market where quickly changing orders occur regularly; and address as-drilled blast patterns as opposed to baseline plans. “Real-time” data exchange into and out of the blasting process supports the whole-of-mine data management that the industry is migrating to.

Jan 1, 2010

By S. Goodman

Successful exploration for and exploitation of a mineral deposit requires an accurate understanding of the deposit architecture in 3D, and of the development of the mineralizing system through time, which requires a thorough comprehension of the structural framework of the deposit. The integration of geological, geophysical and geochemical datasets to arrive at a 4D structural framework is well-established and has been successfully applied by SRK Consulting in projects from deposit to regional scale. In some cases, we can go beyond this, applying the SEEBASETM technique, which utilizes a ?bottom-up? approach to basin analysis. SRK?s approach primarily relies on the interpretation of magnetic and gravity data, calibrated with many other datasets including mapped geology, topography, event histories, wells/drillholes and seismic data. The SEEBASETM model is a culmination of this data integration and is produced through an iterative process of structural interpretation and geophysical modeling, where an interpretation of basement composition and 4D structure is used to constrain depth-to-basement geophysical modeling, and the modeled depths are then used in conjunction with the structural interpretation to constrain contouring of the basement topography. The result is a rigorously calibrated, 3D view of the basement surface, which can be used to understand the basement and basin architecture, and thus serves as a predictive exploration model. This technique, which was developed for use in the petroleum industry, is now finding success as a predictive tool in mineral exploration.

May 1, 2003

By Laurel E. Blackman

The DFI Project Information Management Systems (PIMS) Committee cooperated with the US Army Corps of Engineers (USACE) to develop a specification for PIMS used on USACE projects. Once completed the Committee developed a more generic version of this specification for general use, which is contained in this document. This first edition has simply removed the USACE-related requirements from the document. The committee will continue to work on this specification to enhance the content and also incorporate recent technological development for these systems. It is the Committee's intention that a second edition will be issued in 2022.

Jan 1, 2021

By E Ben-Dor, D Bakun-Mazor, Y Ben-Ari

Determining the mechanical properties of rocks is important for various civil engineering fields, including the mining of raw materials for aggregates used in the construction and paving industries. Traditionally, the mechanical properties of rocks are obtained through in situ and laboratory tests during geotechnical surveys. However, these time-consuming surveys involve many resources. In contrast, hyperspectral remote sensing methods make it possible to identify the mineralogical composition and crystallographic structure of the rock; properties that control the mechanical properties of the rocks. In this work, we characterise the mechanical properties of carbonate rocks by using a hyperspectral sensor in laboratory conditions. We collected about 150 cylindrical samples of carbonate rock, with a wide range of strength values from several rock outcrops in Israel. We used a point spectrometer in the range of 0.4–2.5 μm and a spectral image sensor in the range of 3.0–12.0 μm, scanning the samples to obtain the signature of their light reflections and spectral emissivity. We then measured the samples’ density, porosity, water absorption, and uniaxial compressive strength (UCS). We used sophisticated data mining to find statistical relationships between the hyperspectral signatures of the samples and their mechanical properties. We used this data to identify the most dominant wavelengths for predicting mechanical properties. We found that the density, porosity, and water absorption of carbonate rocks could be confidently predicted based on spectroscopy data, while the UCS of the rock could also be predicted, but less significantly. The results of the study pave the way for the development of measuring tools for the mechanical properties of rock, based on non-destructive tests of quarrying materials.

Nov 29, 2022