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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 A. Wright, P. Lacombe, R. del Villar, D. Hodouin, C. Sepulveda

"The data acquisition from industrial plants is a fundamental step for process modelling in process optimization, process analysis and automatic control.The introduction, some years ago, of modern distributed control and data acquisition systems in concentrators imposes a new approach in designing experimental schemes for data acquisition campaigns and new criteria for the treatment of the obtained discrete information.This paper presents the methodology applied to sample a zinc flotation circuit at Les Mines Selbaie, Joutel, PQ. Values of 85 process variables were obtained form the Distributed Control and Data Acquisition System (Bailey Network 90) and transferred to the DOS environment. Another 11 variables (flowrates and valve positions) were directly sampled using an IBM-PC compatible computer equipped with a data acquisition card and a signal processing circuit.All variables, under the vector form, were processed in the PC-MATLAB environment to either filter or eliminate the non-linear disturbances and noises, producing useful data for model development. The filtering algorithms are also presented.INTRODUCTIONProcess control does not need to be justified. Whether manual or automatic, any processing plant requires some form of control to accomplish its main objectives: a good quality product and a target throughput. Process control of mineral processing plants has steadily evolved from manual control, where the operator skills and/or experience play an important role, to some level of automatic control, usually considered better, as less human subjectivity is involved, at least when actions have to be taken.The design of these control systems requires the knowledge of the dynamics of the process it is deemed to control. Process modelling is therefore an essential step in the assessment and the design of a control strategy. The choice of model will depend on the available resources and manpower."

Jan 1, 1991

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 Greg Sheppard, Eduardo Nebot

Australian researchers have developed new technologies aimed at improving safety and productivity at openpit mines. A data acquisition and feedback system for electric rope shovels has been shown to substantially reduce cycle times and decrease excessive machine duty caused by stalls. This data acquisition system was developed by the Cooperative Research Center for Mining Technology and Equipment (CMTE). It has been tested on a P&H 4100A shovel at Coal & Allied’s Hunter Valley operations and a P&H 4100XPB at BHP Billiton Mitsubishi Alliance’s Goonyella Riverside Mine in Central Queensland. In addition, CMTE member P&H Mine Pro Services has used the technology to acquire field data from a P&H 4100XPBrope shovel at RAG’s Belle Ayr Mine in Wyoming’s Powder River Basin.

Jan 1, 2002

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 G. S. Hill

A large amount of the stereological error associated with liberation studies can he eliminated by assessing areas instead of linear intercepts. The presentation of a simple geometrical model as a stereological 'worst case' allows calculation of the worst possible grade/recovery curve for a given assemblage of areas. The true results are expected to lie in the window between this worst case and the hest possible case, represented by uncorrected data. The width of this window typically corresponds to an error margin of about 5% grade at a given recovery. An indication of where the data lies within the range of possible grade/recovery results may he obtained from a qualitative analysis of the locked section complexity. Assemblages consisting of texturally complex locked sections (ie. containing many mineral nuclei) are likely to exhibit minimal stereological bias and therefore will tend to lie close to the uncorrected side of the grade/recovery window.

Jan 11, 2011

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 Richard P. Sheldon

In the last several decades, techniques of data collection have been rapidly evolving. Automated spectroscopic techniques in the chemical analysis of rocks for example have advanced to the point that we can analyze samples faster than we can grind them. Remote sensors of LANDSAT give us intensity measurements in four color bands of every acre of the U.S. every 19 days. Common depth point seismic instrumentation systems used at sea for surveying and networks of seismometers arrayed around the country for earthquake studies likewise are generating vast amounts of data. These along with many other earth science data generating systems have caused a veritable data explosion. How do we deal with these enormous amounts of geologic data presently being produced as well as those produced in the past, and to be produced in the future? There is an immediate need to acquire and utilize past and present basic data in order to address today's national earth science problems. Also data being collected and stored now must be compatible with future data in order for us to be able to undertake the wide spectrum of analysis that must be made in the future. This is a big order! In order to organize and to be able to analyze these data, the USGS has embarked on a wide ranging program of compatible data base construction and the development of computer technology, based on interactive computing, to facilitate resource assessments and analyses. These activities are analogous to two sides of a coin. One side deals with the logic, philosophy, and mechanics of information storage and retrieval; and the other side deals with the sensible application of computer technology to the treatment of data. These

Jan 1, 1977

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. Dessureault, J. Porter, M. Woodhall

Information and communication technology (ICT) is seen as a key source of future productivity improvements in mines. The information technology infrastructure (ITI) necessary to achieve these productivity improvements will come in the form of data integrated from multiple source systems throughout the mining value chain. Two pure approaches are available: supplier-controlled or operations controlled data structures; each strategy has its own advantages and disadvantages. Case studies involving the South African mining industry are used to demonstrate the advantages of using hybrid-controlled data structures. Depending on the level of operational control, new skills are also necessary to be learnt by mining professionals including: information engineering; creating consistent and quality data; and process improvement techniques that use the integrated data for improving the operation.

Jan 1, 2004

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

Today?s Topics ? Data to decision value chain ? Practical Considerations ? Example ? Before / After DSS ? Quick Decision Support Demo Practical Considerations ? More data is not necessarily better ? Organization and process silos ? Good vs. ?optimal?, but impractical Solutions

May 1, 2008

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