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By Jamal Rostami, Tom Iseley, Saleh Behbahani

Tunnels and underground infrastructures assets, like all assets, deteriorate with time. At some point, they reach the end of their useful life. Therefore, frequent inspections, higher levels of maintenance, and rehabilitation are needed to address loss of life and safety concerns. The repair cost of tunnels will increase if maintenance of tunnels is not satisfactory and timely. Historically, tunnel inspections have primarily relied on visual and manual procedures. Due to their time-consuming nature and susceptibility to human error, there is a demand for alternative automated techniques that can enhance efficiency and reliability in tunnel inspection. By utilizing a tunnel scanning system, such as laser scanner and thermography, or photogrammetry system, tunnel inspection cost, time, and personnel can be reduced. The goal of this study is to utilize deep convolutional neural networks (CNNs) for automated identification of defects in tunnel lining inspection. This paper presents a framework to classify two types of defects in tunnel lining (water leakages and cracks) using CNNs. The CNNs were trained and tested using 4,608 images. The Precision, Recall, and F1 Score were each 99.6%, confirming the viability of this approach in the automated defect identification in tunnel lining.

Jun 23, 2024

By David J. Hatem, K. Bhattarai

Effective risk management in major subsurface projects involves ways to mitigate adverse impacts to final design and construction approaches due to changed subsurface conditions. An Early Contractor Involvement (ECI) collaborated with Observational Method will be an effective contractual tool to address risk developed due to encountering differing site conditions. Observational Method (OM) can further be supported with artificial intelligence (AI) technologies with automated data-driven decision-making features in risk mitigation and implementation of proper design and construction approaches. This paper presents collaborative applications of ECI, OM, machine learning, and risk baselining in risk management and productivity enhancement in tunneling projects.

Jun 23, 2024

By Raymond Sandiford, Kenneth Xu, Taehyun Moon

Tunnel approach structures situated in slow moving earth flows are subjected to significant earth pressures. The authors have developed a system, utilizing collapsible concrete columns, that limits such loading. The system uses an array of collapsible concrete columns in front of the structure to absorb downslope movement and limit-imposed loads. This concept has been modelled using 3D FEM analyses and a rudimental lab test. For implementation, the collapsible columns would be prefabricated in strengths to mimic the soil strength profile. This concept has merit, and analytical results demonstrate that collapsible columns are a viable means to limit loading.

Jun 23, 2024

By Victor Romero, Steve Redmond

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of individual authors and are not necessarily those of the SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2011

By Gregg Davidson, Lonnie Jacobs, Brett Zernich, Alan Howard, Robert Pintabona

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. If such services are required, the assistance of an appropriate professional should be sought. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of the authors and are not necessarily those of SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2014

By Matthew Preedy, Brett Campbell, Jim Rush, Alan Howard, Derek Penrice

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. If such services are required, the assistance of an appropriate professional should be sought. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of the authors and are not necessarily those of SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2018

By Shemek Oginski, MARK C. JOHNSON

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of individual authors and are not necessarily those of the SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2015

By Bill Mariucci, Gary Almeraris

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of individual authors and are not necessarily those of the SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2009

By Bradford F. Townsend, Marc R. Kritzer, Michael F. Roach, Dennis Ofiara

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. If such services are required, the assistance of an appropriate professional should be sought. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of the authors and are not necessarily those of SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2008

By Steven J. Schatzel, James Addis, K. Vaibhav Raj, Berk Tulu

The National Institute for Occupational Safety and Health (NIOSH) is conducting research to enhance methane control and mine ventilation practices at coal mines, as a method to mitigate hazardous work conditions. NIOSH researchers conducted case studies to investigate the effectiveness of existing systems and improve performance to decrease the potential for unplanned or excessive methane emissions. At one mine, drainage was influenced by hydrofracking inefficiencies where two of the six wells showed good frack development. Methane content was variable, from 300 ft3/t to 600 ft3/t. This paper also summarizes overburden movement during undermining and the estimated quantities of gas transported to the mine using FLAC3D and CFD modeling. The findings from this research effort highlight considerations based on specific mine conditions that may also be applicable to most longwall mines utilizing methane control systems.

Feb 1, 2025

By Connor Meinke, Shaihroz Khan, Kevin Erwin, Rajiv Chandramohan, Muhammad Usman Siddiqui

High-quality sample selection for metallurgical test work is essential to a geometallurgy study, but the large multidimensional dataset makes sample selection a daunting task, as classifying the dataset while respecting its heterogeneity is difficult. This paper presents a streamlined approach for sample selection, utilizing custom-built tools in Python to standardize the methodology, saving time and costs. This approach uses the cumulative sum method, principal component analysis, and k-means clustering method to elegantly cluster the data and select representative samples. A case study is used to demonstrate the effectiveness of the methodology by selecting 40 samples for flotation test work.

Feb 1, 2024

By Peter Zhang, Daniel Su

Following the first longwall excavation at a deep-cover gas well site, the pre-mining modeling prediction of longwallinduced casing deformations in the fully cemented production casing were in excellent agreement with post-mining Caliper survey results. However, after second panel mining, the post-mining Caliper survey revealed a large plastic deformation near the top of the Pittsburgh Seam. The focus of this paper is to identify the possible cause of such an anomalous deformation. Very high longwall-induced casing stress near a thick claystone layer at 23 feet above the Pittsburgh seam horizon was identified as the primary cause. Leaving the production casing uncemented or using softer cementing material between intermediate and production casings is identified as the best practice.

Feb 1, 2024

By H. R. Hernandez-Guerrero, S. A. Robles-Salazar, M. Marín-Pasillas, P. J. Pompilla-Rosales

Peña Colorada is a company dedicated to the exploration, exploitation, and beneficiation of iron ore, serving the national steel industry. Established in 1975 as a stateowned enterprise, it transitioned to operating as a private organization in 1991. It is jointly owned by two investors, ArcelorMittal and Ternium, each holding a 50% stake. The mining operation is situated in the municipality of Minatitlan, in the northwestern part of the state of Colima, Mexico (Figure 1). It comprises an open pit mine and a concentrator, covering an area of approximately 2,300 hectares. The pellet mill is in the town of Manzanillo, Colima state, a port on the Pacific coast, about 46 km southwest of the mine. The pellet mill occupies its own property with a total area of 60.4 hectares. A gravity-driven concentrated slurry pipeline connects the mine and the pelletizing plant, located at an average elevation of 1,020 meters above sea level and 20 meters above sea level, respectively. Currently, Peña Colorada produces 4.1 million tons of pellets and 0.4 million tons of iron concentrate annually. In 2018, due to a change in the cutoff grade, the processing volume of the beneficiation plant increased from 9 million tons to 16 million tons annually. This led to a greater amount of information to process and characterize the ore extracted from the pit before its processing in the beneficiation plant. Consequently, Peña Colorada sought new ore control technologies to enhance ore selection, optimize human resources and data management, as well as minimize discrepancies between planning and execution. To ensure adherence to quality agreements with stakeholders, it is crucial to understand the ore characteristics before initiating mining activities.

Feb 1, 2024

By Alvaro Veizaga, Samuel Cuellar

In recent years, Industry 4.0 has generated a change in the way companies in various industrial sectors design, produce and deliver products and services, and is focused on the interconnection of systems, the advanced access and management of large amounts of data in real time, and the implementation of emerging technologies such as the Internet of Things (IoT). Artificial intelligence (AI), machine learning (ML), digital twins (DT), robotics, virtual and augmented reality (VR/AR), among others [1]. DTs are accurate and dynamic virtual models that replicate physical systems, where it is possible to simulate and optimize operations before implementing real-world changes [3]. These features make it possible to reduce investment costs, minimize risks and improve strategic decision-making. These benefits are of utmost importance for tailings storage facilities (TSF), since they are facilities aimed at the safe storage of tailings and with the constant need for growth [4]. This paper evaluates the applicability of a DT in a TSF from a conceptual perspective, providing the advantages of its implementation, but also the barriers identified in the industry based on the authors’ experience.

Feb 1, 2025

By Leena Suopajärvi, Karin Käär, Marcin Szumny, Jari Joutsenvaara, Md Ariful Islam, Helmut Mischo, Georg Meissner, Ossi Kotavaara, Catalina Vrabie

This study outlines implemented tactics and results for community empowerment through participation in questionnaire surveys, educational programs, and discussion on sustainable sourcing from new critical raw materials (CRMs) projects. Utilising questionnaire surveys, including the Public Participation Geographic Information System (PPGIS), the research gathered public opinions from Estonia, Germany, Poland, and Zambia, receiving 1,068 responses. These responses addressed various social, economic, and environmental issues related to CRM projects. Feedback from educational courses with participants from over 25 nations and public events provided additional insights. The collected data and feedback offer crucial input for advancing sustainable and responsible CRM sourcing strategies in these regions.

Feb 1, 2025

By M. Portal, L. Goicochea

This study is carried out in the Zenit mining concession, which is located in the city of San Pablo in the department of Cajamarca in Peru. The Project has 33 mineralized structures and according to laboratory analyzes we have the presence of gold and silver. The geostatistical evaluation provides an analysis on the distribution of precious metals in the vein. This information is used to improve the efficiency of metal extraction and to reduce costs. The general objective is to evaluate the polymetallic veins (Au and Ag), for which the classification of resources (measured, indicated, and inferred) has been carried out, taking into account the parameters of minimum distance from the composite, corresponding volume and tonnage calculation. In addition, an inventory of estimated geological resources was carried out with the block grades obtained to generate the tonnage-grade curves.

Feb 1, 2024

By Evan J. Owen, Virginia T. McLemore

There are tens of thousands of inactive mine features in 274 mining districts in New Mexico (including coal, uranium, metals, and industrial minerals districts). However, many of these mines have not been inventoried or prioritized for reclamation. Many of these mines have existing mine wastes, generated during mineral production, which could have potential for critical minerals, especially since the actual mineral production was generally for precious and base metals and not critical minerals. The purpose of this project is to characterize and estimate the critical mineral endowment of mine wastes and “beta-test” USGS sampling procedures. This project is important to the state of New Mexico because critical mineral resources must be identified before land exchanges, withdrawals or other land use decisions are made by government officials. Future mining of mine wastes that potentially contain critical minerals will directly benefit the economy of New Mexico. Possible re-mining of mine wastes could clean up these sites and pay for reclamation. Furthermore, this project will include training of younger, professional geologists and students in economic and reclamation geology by the PIs.

Feb 1, 2024

By Joshua Cole, Joshua Sovechles, Christian Cardoso, Guillermo Bermudez, Martta Hirsi, Joshua Dettamanti, Rabia Abbasi

The implementation of technological advancements in flotation is key to optimize performance in mining operations. Consequently, flotation cell’s performance is highly dependent on the effectiveness of the mixing mechanism. A more efficient flotation mixing mechanism is likely to improve metallurgical performance and optimize energy consumption, which is the motivation for Metso’s journey to develop the latest iteration of FloatForce®. Looking to test the new design at plant scale, Metso approached the Kennecott Copperton concentrator, which is continuously looking for different venues to improve metallurgical performance. In this context, a test campaign was conducted to implement this new flotation mixing mechanism in their rougher circuit during 2024. The industrial trial consisted of several sampling campaigns assessing different operational parameters for comparison purposes around a 300m3 flotation cell. The effect of the new flotation mixing mechanism on the cell’s power draw was also studied. The results of this trial at Kennecott are presented in this paper. Overall new flotation mixing mechanism, FloatForce+ was seen to perform as well as the original FloatForce.

Feb 1, 2025

By Ahmed Alghamdi, Salem AlGharbi, Aisha AlHarbi, Owain Morton, Norah AlMuhaisen

This paper addresses the challenges in optimizing the phosphate flotation process, specifically focusing on the variability in P2O5 recovery. An artificial intelligence (AI) driven Flotation Prediction Model was developed to accurately forecast P2O5 grades. Leveraging real-time data from various operational sources, the model provides insights into how operators can opstimize key flotation parameters to enhance product quality and recovery rates. The results demonstrate the effectiveness of AI predictive modeling in addressing operational variability, marking a crucial step toward intelligent operations in the phosphate flotation process.

Feb 1, 2025

By C. Cardoso, G. Bermudez, A. Jalili

Bigger flotation cells can result in larger froth surface areas and longer froth transport distances, this has been credited to impact froth recovery. Thanks to recent advancements, the newer flotation machines can be designed with different launder and crowder arrangements to enhance froth management. Nevertheless, lower head grades, complex ores and even larger mechanical flotation cells can lead to insufficient froth collection, even if the cell is equipped with the most recent flotation advancements like the center launder design. Aforementioned issue can become critical at the end of the flotation row. Increased crowding has been proven to be a solution to overcome inadequate froth recovery. However, scaling-up crowders for larger flotation cells can rise challenges, particularly in terms of structural limits and design for service. This paper presents the development journey for the Spider Crowder Upgrade, an advancement to improve froth collection in large flotation cells that are already equipped with center launders.

Feb 1, 2024