The growing importance of rare earth elements (REEs) in sustainable technologies necessitates anefficient assessment of potential resource targets within the European Union. Traditional analyticaltechniques for REE determination have drawbacks like destructive and time-consuming samplepreparation, but hyperspectral imaging (HSI) and laser-induced fluorescence (LiF) offer promisingalternatives. This project aims to use a combined HSI and LiF method to qualitatively characterizeREE mineralization and alteration in drill core samples from the Storkwitz deposit, Germany. The goal is to develop a transferrable mapping approach for REEs, while enhancing our understanding of the Storkwitz deposit. It aims to check the robustness of HSI conducted across the extendedwavelength range as a tool in effectively characterizing the lithologies associated with REEmineralization in the Storkwitz breccia. It also tests if the combined HSI-LiF can provide newinsights into the presence of REEs and its associated minerals in the Storkwitz breccia.The proposed workflow involves acquiring hyperspectral data of the Storkwitz drill core and blocksections in three wavelength ranges (VNIR-SWIR, MWIR, and LWIR). Automatic and manualendmember extraction is performed on the smaller subsection of data to create spectral libraries,which are then used for spectral unmixing and mapping of the entire hyperspectral dataset toidentify lithologies. LiF is used to identify and map rare earth elements (REEs) in selected REErichzones identified from the hyperspectral data.The results indicated that the Storkwitz Breccia is primarily composed of ankerite in the matrix,along with minor amounts of white mica, clay, iron oxides, and REE-fluorcarbonates. The brecciacontains different clasts, including granitoid clasts rich in orthoclase and quartz-albite-biotite, aswell as carbonatitic clasts dominated by ankerite, dolomite, and ankerite-calcite. The breccia alsounderwent four alteration phases, including fenitization, biotite alteration, white mica-clayalteration, and ferric alteration. Laser-induced spectroscopy confirmed the presence of REEs, withapatite and REE-fluorcarbonates, particularly bastnäsite, being the main REE-bearing minerals.The specific REEs identified include Nd3+, Sm3+, Pr3+, and possibly Eu3+. The comprehensiveworkflow combining hyperspectral imaging and laser-induced fluorescence spectroscopy provedto be a successful approach for characterizing lithologies and mapping rare earth elementmineralization in the Storkwitz breccia. The study opens up new possibilities for efficient REEexploration in similar geological settings, providing valuable information for geological loggingand interpretation.

The implementation of autonomous haulage systems in open-pit mines is a progressive step in the industry, but it brings potential safety risks that need careful evaluation. This study developed a discrete event simulation model to analyze and evaluate these risks in different operating scenarios -fully autonomous, hybrid (a mix of autonomous and human-operated vehicles), and non-autonomous operations.The simulation model was developed using the HAULSIM and Anylogic software, integrated mine layout, haulage operations, and various fleet compositions. It provided insights into collision risks, a significant concern in mining safety literature. Results showed that collisions were inversely proportional to the number of autonomous vehicles in operation, indicating the potential safety advantages of fully autonomous operations. However, certain high-traffic intersections were identified as high-risk areas, emphasizing the need for targeted risk mitigation strategies. Further, a profile risk matrix was developed to provide a comprehensive view of collision severity and likelihood in each scenario. This highlighted the impact of collisions on both human safety and project operations. Based on the results, risk mitigation strategies were proposed, with a focus on redesigning intersections, implementing strict rules for human-operated trucks in autonomous zones, and improving autonomous vehicle capabilities. The study, while insightful, was limited by assumptions and the generic nature of operational data used in the simulation. Therefore, future research should seek to incorporate more detailed, mine-specific data and empirical insights from projects that have implemented autonomous haulage systems. Continuous advancements in autonomous technology and simulation modeling will be key to ensuring a safe and productive mining environment.

The importance of decarbonization in various industries is growing significantly, especially when it comes to LHD equipment in the minerals and metals industry. Conventional diesel load and haul (LHD) equipment used in quarrying and mining operations have drawbacks that result in the emissions of hydrocarbon and greenhouse gases that need to be reduced to reach the Net Zero Emissions scenario. Decarbonization options that could replace diesel equipment include battery electric vehicles, green hydrogen, and alternative fuels. This project aims to give an overview of current and near future available decarbonization methods and to analyse the environmental benefit, cost effectiveness and technological feasibility of these alternatives to diesel fuel. The case study used to simulate and compare the three different decarbonization options is a mountaintop marble quarry based in Ipoh, Malaysia. A comparison has been made with Ipoh located in Malaysia and a hypothetical situation of Ipoh located in France to show the true potential of decarbonization as Malaysia does not incentivize businesses to reduce emissions due to their subsidies on the use of fossil fuel. Malaysia’s energy mix consist of primarily unabated fossil fuels.
The proposed workflow involves an extensive literature review of current and near-future decarbonisation technologies to replace diesel equipment and to create a haulage network based on block model data using the software Xpac Quarry solutions and its Haulnet package. Diesel equipment is imported from the Quarry solutions database and used as a base case to compare BEV and trolley assist simulations. Hydrogen and HVO fuel consumption have been calculated manually to obtain NPVs and associated emissions. An investigation into required infrastructure and energy requirements has been done to accurately define costs and resulting total CO2eq emissions.
The results indicate that replacing diesel at Ipoh with any of the decarbonization methods will result in a negative NPV as the infrastructure requirements need extensive capital investment of which the payback period often exceeds the life of mine. The least expensive method to implement HVO fuels, followed by BEVs and green hydrogen. Furthermore, it has been found that using BEVs instead of diesel at Ipoh is more environmentally polluting because producing 1 kWh of electricity is more polluting than producing the same energy worth of diesel. Green hydrogen is the least polluting method with no greenhouse gas emissions associated with it, followed by alternative fuels. When investigating the technological feasibility of the three main decarbonization options, hydrogen is the furthest away of being technologically feasible as from now. No green hydrogen using water electrolysers has been produced at an industrial scale, and a lack of technical expertise and infrastructure is present regarding distribution, transportation, and storage. Currently, no hydrogen LHD equipment is commercially available currently, and the same applies to BEVs that could replace the current equipment used at Ipoh. To bridge this gap, alternative fuels are the best option, but the market is competitive, and supply is limited. This project has given a good overview of current possibilities and clearly shows today’s options for decarbonisation and where industries stand with respect to infrastructure and equipment.

The frequent occurrence of catastrophic tailings dam failures underscores the urgent need to improve safety practices and minimise associated risks. This study introduces an advanced tool to evaluate the total Probability of Failure (PoF) of existing tailings dams systematically and effectively, supporting the rational prioritisation of mitigation efforts and minimise risk within the 'As Low As Reasonably Practicable' (ALARP) principle.

The tool utilises a semi-quantitative approach, combining observation frequency and expert judgment. A baseline PoF for each dam construction method and failure category is established using a database of 450 tailings dam incidents and accidents developed in this study. This baseline PoF is subsequently modified based on site-specific factors influencing failure prevalence. A total of 255 key contributing factors are identified based on a fault tree analysis, the Global Industry Standard on Tailings Management (GISTM), and experts in the field. The factors encompass site conditions, design elements, and the level of practise, which address all major credible failure modes and mechanisms. The factors are linked to the failure categories they influence and assigned relative weights through the analytical hierarchy processing method for each dam construction method and failure category. Subsequently, the weights are multiplied by modifiers to account for the effects of site-specific conditions (favourable: 0.2, neutral: 1, adverse: 5, and unknown: 2). Within the tool, users can choose fulfilment conditions for each factor from drop-down menus and the selected inputs are connected to the modifiers. The adjusted weights are multiplied by the baseline PoF of each failure category, given the dam construction method. The summation of these products yields the total PoF of the investigated dam.

The results provide preliminary insight into factors significantly affecting the total PoF for the dam under investigation, aiding in evaluating whether the PoF reduction justifies costs. It facilitates preliminary, rational prioritisation of mitigation measures in accordance with the ALARP principle, contributing to ongoing efforts to improve tailings dam safety.

To validate the tool’s capabilities, two case studies with available data are analysed: the Aznalcóllar failure to examine the ability to identify high-risk factors and a recently improved dam to evaluate if the mitigation efforts are adequately reflected. The studies demonstrate the tool’s potential but also reveal uncertainties, inaccuracies, and limitations. These stem from discrepancies in the baseline PoF, weightings, modifiers, and unaccounted factors. Therefore, caution is warranted in the tool’s utilisation. Recommendations include various improvements and further verification and validation across a broader range of case studies. Value can be added by incorporating additional components and adapting the tool for new dams.

New mining and exploration projects have revived across Europe with an increasing demand for critical raw materials driven by the energy transition and unstable political conditions. Hyperspectral imaging proves to be an excellent tool for quick and efficient non-invasive mineral exploration. By mounting hyperspectral- and LiDAR sensors on drones and other robots, inaccessible and dangerous areas can safely be mapped for geological information. With increasingly deeper and more hazardous underground mines, a robot-aided
hyperspectral mineral exploration method in underground environments is needed. This study configures a Cubert X20P hyperspectral camera (VNIR) and VLP16 LiDAR on the versatile Boston Dynamics Spot robot, creating a multi-sensor robotic platform for data acquisition in underground mining environments. A data workflow is proposed and applied to the granite greisen rocks of the Zinnwald/Cinnovec mine (Germany). Combining hyperspectral and geometric data provides unique 3D hypercloud results interpreted for mineral
and structural features. Hyperspectral analysis successfully identifies iron and clay minerals along with multiple vein and fault structures. A remote mineral exploration method in underground mines significantly improves safety by keeping the operator away from hazardous areas. The proposed platform and workflow show potential to contribute to underground mineral exploration, especially if future improvements in data quality and autonomous capabilities are made.

Measuring and analyzing the tunnel deformation through convergence measurements and cross-correlation with geological mapping is essential for understanding and controlling tunnel stability, worker safety and predicting failure zones. In order to achieve this, a new device, the so-called GroundProbe GML is tested and analyzed in this study. Currently, the deformation in the Kristineberg mine is measured through conventional techniques, such as the tape extensometer, that are labor intensive and time-consuming. On top of that, the geological mapping is done by visual inspection by experienced geologists. There is no system in place that correlates the geological setting to the deformation of the tunnels. This research aims to explore the possibility to quantify tunnel wall convergence and correlate the movement to geological circumstances. An accuracy analysis is performed, to identify the accuracy of the Light Detection and Ranging (LiDAR) technology in comparison to conventional techniques. This analysis is conducted in both a controlled (above-ground) and an uncontrolled (underground) environment and focuses on the use of different targets, i.e. prisms or reflectors, and the difference between continuous and periodic measurements. The fresh rock surfaces are also mapped by means of geological LiDAR data as well as Red-Green-Blue (RGB) image analysis and this is correlated with tunnel wall convergence. This is done to increase the understanding of the impact of the geological setting on the tunnel wall convergence.
The accuracy presented by GroundProbe of _3 mm for periodic measurements is difficult to achieve in an underground environment with mining activity. Especially the deformation of measurement points that are at a more oblique angle to the scanner prove to be difficult to assess. The geological LiDAR data can be used to distinguish different rock types and geological features with limited subjectivity. The transition zones from one rock type to the other become clearly visible from the geological LiDAR data. Additionally, geological features such as joints can be identified when combining LiDAR data with RGB image analysis. The primary promotor of tunnel wall convergence is the hanging wall that pushes down on the foot wall in combination with non-uniform waste rock areas, that are for example split into two sections by a joint. In a tunneling environment where mining activities are conducted, such as the application of shotcrete, scaling, blasting and leveling of the floor, periodic measurements with a LiDAR set-up on a tripod are difficult. One of the main limitations is the absence of stable reference points that the LiDAR scanner uses to determine its XYZ-position. The oblique angle can also be a limiting factor, measurement points closer to the LiDAR scanner provide more reliable results. For continuous measurements however, this proves to be less relevant because the repositioning error can be omitted. The LiDAR scanning technology has the potential to be used as geological mapping tool based on the varying reflectivities of different rock types. By combining LiDAR technology with RGB image analysis, a more thorough understanding of the geological setting can be obtained. By relating this understanding to the quantification of the tunnel wall convergence, this technique can be used to correlate the geology to the movement of the rock mass.

Surface mining operations can have a significant visual impact on the surrounding landscape and communities. There have been numerous cases of local populations pushing back against the development of mining operations near their communities. This study aims to determine whether it is possible to assess the visual impact of surface mining operations before the development has started. With this assessment it would become possible to make informed decisions as to pitshell development and selection in terms of visual impact. A tool was developed to determine whether it is possible to make this assessment. This tool must be able to be used to determine the visual impact of two or more scenarios in the pre-feasibility phase of development to assist in the decision of
which scenario will be developed further in the feasibility phase. In this context, the visual impact is defined as the perceived change in the landscape as a result of mine development on local communities around the surface mine development. The scenarios are defined as the option of pitshells designed during the pre-feasibility phase of mine development.

The tool makes a distinction between the physical changes in the landscape caused by the surface mining operation and how this physical change is perceived by anyone viewing the operation.

The tool is GIS based and utilizes the free open-source software QGIS to calculate the physical change in the landscape. The tool calculates the vertical and horizontal visibility angle. The visibility angle describes the extent that the change in the landscape takes up in the view of an observer. In addition
to that, the tool calculates the contrast between the changed colour in the landscape and its surroundings, which describes how much the change stands out. It requires two sets of data to work: a digital elevation model of the prospected surface mine pitshell and the surrounding landscape and a
RGB satellite image of the surrounding area. The DEM provides elevation data for every square metre of the landscape to the GIS, while the satellite image provides RGB colour data. All other data can be generated from the previously mentioned data features.

The tool is tested using a case study, in which several distinct pitshell scenarios are compared against one another on their visual impact. The case study is based on the extension of a limestone quarry in
Belgium, which aims to secure reserve for future operations. The area of interest is surrounded by several small to medium size villages, which would be affected visually by the extension. Therefore, a comparison should be made regarding the visual impact of the several pitshell scenarios. The results showed it is possible to determine the visual impact of surface mining operations before the
development has started. On this basis, it is possible to compare different pitshell scenarios and determine which scenario would be least impactful in terms of visual impact on the local community and surrounding landscape. The reliability of the tool can only be assessed theoretically, however a high level of accuracy is achieved by adhering to guiding principles which are set out in this thesis.

The aim of this master thesis is to improve a raw materials certification scheme by checking and validating the application matrix and the coherent hazards developed for the Certification of Raw materials (CERA) project. The scope of the original application matrix included exploration, mining, physical processing, chemical processing, smelting and refining. The validation in this thesis was focussed on the iron ore value chain. This validation showed that important methods associated with these processes were missing in the application matrix. Two main sections that are absent are recycling and storage and transportation, which have been added to the application matrix including the main methods used within those two sections. The risks and hazards developed by CERA, associated with the application matrix’s processes and methods, are transformed to only hazards. Next to this, new hazards are suggested to make the hazards list more holistically applicable. After the addition of recycling to the application matrix, an analysis on the addition of recycling to the CERA Performance Standard (CPS) and to the CERA Chain of Custody Standard (CCS) was done. This analysis showed that adding recycling to the Performance Standard deals with few challenges due to it being an industrial activity with many similarities to methods used in processing and smelting. Therefore, with the additions that are proposed in the validation of the matrix and the hazards analysis, recycling can be easily added to the CPS. This is done by including collection centres, recycling facilities and scrap transport in the standard under the general term ‘recycling facilities’. Adding recycled material to the CCS can be done in different ways, this thesis proposes multiple options of which three are viable. First, three types of recyclable materials have been distinguished: Recyclables of which the origin is known (1); Recyclables of which the origin is unknown and no further information is available (2); Recyclables of which the origin is unknown but a due diligence can show that it has sufficient added value to the raw materials value chain with regard to responsibility and sustainability (3). In all cases, CERA should include the certification of recycled material of which the origin is known. The first viable option is to only certify type one with the original CCS certificate and exclude the other two types from the scope. This requires no extra certification or requirements by CERA. The second viable option for CERA would be to also certify type three within the original CCS certification standard, and add a ‘recycled label’ to materials of type two. The third viable option would be for CERA to develop a ‘CCS recycled’ certificate for materials of the third type mentioned, and add a ‘recycled label’ to materials of type two. CERA should decide which option is best according to their basic criteria and values. If CERA decides to select option one, CERA safeguards their integrity but the option is lacking holistic applicability. If option two is preferred, CERA increases their holistic applicability level, however, the integrity of CERA might be at stake. If CERA decides to select option three, holistic applicability is maximized and their integrity is safeguarded, however, the system of CERA is complicated due to different levels of certifying.

Site-specific calibration of laser induced breakdown spectroscopy (LIBS) analysis can be achieved by presenting known geological sample data to update algorithms, therefore improving analysis of unknown samples post-calibration. The goal of this project is to optimise drill core analysis by LIBS for samples from Kittilä gold mine. In total 227 samples have been produced and analysed with a range of analytical techniques to build a comprehensive, site-specific reference library. The data from these analyses has been input into the reference library and utilised by algorithms for spectral peak identification during LIBS analysis of bulk drill core material. The semi-quantitative and quantitative data of 40 Kittilä samples has been used as a comparison to ICP-AES data used by the mine. The Kittilä powders were used to produce 39 pellets, each representative of a section of drill core of which the ICP-AES and TXRF data was known. The pellets were scanned by LIBS and the data then compared to the known data. LIBS showed strong correlations (>0.75) with ICP-AES data for As, Cr, Cu, Fe, Mn and S, poor correlations were seen for Pb and Co, however these can be explained by issues related to ICP-AES. LIBS pellet data proved strongly competitive as 5/9 elements displayed stronger correlations between LIBS and ICP-AES than TXRF. Subsequently, the successful scanning of drill core boxes directly has proven that calibration can increase the speed with which the bulk material can be effectively analysed.

Over the last decade, interest in deep-sea mining of Polymetallic Nodules (PN) has reignited. It is driven by an increasing demand of metals that are critical for the digital economy and modern technologies such as batteries. Methods for resource estimation of PN are known and commercially available. There is however no standard method of a planning a deep-sea mining operation. This is an essential step to define mineable reserves. To address this problem, an existing concept has been applied in this thesis. This planning concept was inspired by agriculture and subdivides a mining license area into large scale mining sites, which are in turn subdivided into smaller, continuouslymineable areas calledmining fields. The subdivision is illustrated in figure 1. The contribution of this thesis is the development of a methodology for this concept. The concept was applied to a framework based upon a license area in the Clarion-Clipperton Zone (CCZ) in the Pacific Ocean. The mining will be done using a Nodule Collector (NC), which is a self-propelled machine that continuously gathers PN on the ocean floor and transports them upwards to a vessel at the ocean surface. Certain areas are deemed constrained by slopes or nodule types. Mining sites wherein the NC will operate were outlined within the license area using those constraints and Nodule Abundance (NA).Within the mining sites, a new metric was introduced for assessing the mineability for the NC: the Straight-Line Distance (SLD). The next step down from mining sites are the mining fields. The operation of the NC within them is approximated by two different driving patterns. Different field shapes are also analyzed, along with the impact of obstacles inside the field. Different methods of creating fields inside the mining sites were considered. The procedure relied upon the SLD to define the boundaries between fields. Two sets of field are created: with elongated shape and compact shape. The best set of fields was selected using the approximation of NC operation. Lastly, a method for determining the sequence of fields is developed that uses a Genetic Algorithm (GA) as optimization method. It takes into account constraints for mining rate, operational hours, nodule targets and travelling time. The methods outlined in this thesis are flexible and can be applied in a variety of circumstances. The selection of mineable areas turns out to be the must crucial step. The subsequent delineation of mining fields and sequencing does not make or break the profitability of the operation, although they are essential steps for the definition of mineable reserves.