Haul truck driving remains to be the most dangerous occupation in the mining industry (Kecojevic et al., 2007), leading in fatalities over other occupations in the mining industry. As the transition to autonomous haul trucks over the coming decades will not address thisproblem today, an immediate solution is needed that can be adopted at short notice to help aid in minimizing haul truck accidents. A gamified training simulator was developed that teaches haul truck drivers how to handle the hazardous situations that lead to the most injuries in the mine environment. The simulated nature of the training method allows truck drivers to gain knowledge on hazardous situations and immediately put them into practice by applying the gained knowledge during the different levels. Gamification aspects like a score system and progression through levels were added to increase engagement during the training simulation.
A statistical analysis was made on haul truck accidents from 1983 until 2022. The accidents that proved to be most relevant were included in the content of the training software. A training software was developed using Unreal Engine 5, where trucks could be driven using a Thrustmaster T150 Pro steering wheel and driving pedals. 18 participants from ages 19-65 underwent the training program and two tests of identical difficulty were taken before and after undergoing the training, in order to make a judgement on the progress of the participants by undergoing the training simulation. Participants were judged based on the number of crashes and traffic violations committed, attempts required to complete the test, as well as the time taken to finish the test. A score was calculated based on these factors providing an overall judgement of the participants’ level of skill.
Average skill of participants increased by undergoing the gamified training, and training showed particularly good progress for underperformers in the initial test. After completing the gamified training the average score of participants was notably higher and the standard deviation was notably lower. It was concluded that all participants were brought to a comparably high level after completing the training.

This thesis investigates the impact of truck electrification systems on CO2 emissions and financial aspects in mining. Through comprehensive simulations, the study analyses diesel-electric trucks with trolley assist as well as battery-electric variants with trolley assist and stationary charging. The research findings reveal a noteworthy decline in CO2 emissions and an improvement in cost-effectiveness for the diesel-electric variant with trolley assist. Comparable CO2 savings are observed in battery-electric scenarios, but with varying financial profiles. The transition to battery-electric trucks with trolley assist leads to improved efficiency and associated cost savings. On the other hand, stationary charging entails financial challenges owing to high equipment costs. The analysis of emissions was conducted by different scopes, allowing a differentiated analysis of direct emissions (Scope 1) and indirect emissions (Scopes 2 and 3). This research highlights the significance of adopting a comprehensive approach towards achieving a sustainable future in mining. It provides clear insights into the potential of electrification technologies, particularly highlighted by a 49% CO2 reduction in battery-electric scenarios.

The case study consist of a small underground mine with a small mining crew. The vehicle park is relatively large, and therefore it is necessary to establish the added value of additional miners or equipment for short-term production planning purposes, assuming that staff size currently limits production capacity to find out if staff size is indeed the bottleneck in the production capacity of the mine operation. When the bottlenecks of the mining system are known, it will be easier to focus on necessary areas and further implementations to improve the system.

The truck numbers used in the simulation study were ranging from 4 to 7, and the operator pool size was ranging from 10 to 15 people. Significant findings of this study are that with the current mine setup of 4 trucks, there would be no increase in production when adding operators. For the 24 scenarios the production increase was determined, the revenue change and the mining cost. By adding trucks and operators, a production increase of 19.38 % could be reached with 15 operator and 7 trucks.

The current plan of bottom to top bottom sublevel stoping for the Kearney gold vein at the Cavanacaw mine, Omagh, Northern Ireland may not be the most effective in terms of stability. The Kearney ore body is a narrow vein gold deposit, which has been previously exploited through an open pit and is currently being developed as an underground operation using sublevel stoping (modified Avoca mining method). Stability within the mine is one of the key factors to be considered when it comes to hard rock mining. It should be considered equally as important from a safety and economic point of view. The extraction sequence plays an important role when considering the stability of a designed mine. This thesis aims to establish if the current planned sequence of extraction of bottom to top sublevel stoping is the most effective in terms of overall rock stability, or whether an alternative plan would be better? In the context of this thesis, the modified Avoca mining method is a form of sublevel stoping where material is extracted (stoped) between two drives (blind tunnels) and then backfilled.
The project addressed, a conceptual study, field testing and laboratory testing in order to yield the information required to build several numerical models. The numerical modelling was carried out on several different stoping orders which met the constraints set out by Galantas, using the Hoek-Brown model within Plaxis2D. The analysis was conducted on the total displacements, phase displacements, predicted failure points and safety factors. The analysis of the different models showed that an alter- native stoping method of middle to top bottom to middle sublevel stoping peformed better in terms of stability. This improvement in stability was shown by an increase in the minimum safety factor from 3.20 to 3.50, over the current plan. There is further evidence in the reduction of the total number of predicted failure point by 25%.

Since 1918 AkzoNobel produces salt by means of solution mining from the bedded Triassic Röt Evaporite deposit in the eastern part of the Netherlands. In this technique water is pumped into the rock salt layer through a well and dissolves the halite in situ. Subsequently the brine is pumped to the purification plant at surface level where the NaCl is extracted from the brine after several impurities have been removed.
Near the city of Hengelo, the Hengelo Brine field has been exploited by AkzoNobel since 1933 and based on the technological progress during the years it can be divided into five phases:
1. 1933-1958, 53 wells, 42 caverns;
2.1959-1975, 226 wells, 94 caverns;
3.1976-2005, 213 wells, 72 caverns;
4.2006-2013, 37 wells, 36 caverns;
5.2014-present day, 31 wells, 31 caverns.

The area corresponding to the first phase comprises 42 caverns which have been developed from 50 production wells. The production wells have been drilled between 1933 and 1958 and during later stages 3 appraisal wells have been drilled.
Present-day AkzoNobel pursues stable caverns at the end of their production life. This is achieved by leaving a sufficient thickness of salt in the roof above the cavity. The result is a ductile boundary between the void and the overburden material. The directly overlain anhydrite layer is much stiffer and shows brittle behavior. When this anhydrite layer is not supported by a sufficient amount of rock salt underneath it can potentially collapse. This roof failure occurs when the span of the exposed anhydrite is large enough. The fragments of the collapsed roof layer will deposit on the bottom of the cavern leaving the next roof layer exposed. With each roof layer collapsing the cavern top and bottom attain a new depth. This process is called cavern migration, which continues until the cavern reaches a status where the roof layer is stable either by sufficient support or strength.
Most of the 42 caverns of the phase 1 area have migrated and in five cases this led to significant surface subsidence. Currently AkzoNobel prepares abandonment of the last open wells in the phase 1 area. In order to proof long term safety after closure, the caverns have been examined, simulated, reconstructed, and modelled. By analyzing the available data and scrutinizing a few caverns where extensive migration did occur, the cavern migration behavior and its influential parameters were identified. This report clarifies how the caverns have been reconstructed and how the maximum migration potential is determined with the model.
The phase 1 area comprises the oldest part of the Hengelo Brine field. The wells were drilled between 1933 and 1958. During this phase some of the wells were positioned close to each other, intentionally allowing interconnections. The motive was to complete these wells as doublets, while the rest were setup as single completion caverns. Despite these intentions, the leaching during this phase was performed in a less restrained manner than what is acceptable today. The majority of the caverns in the phase 1 area have established unintentional connections and were completed as series of caverns. Due to this lack of control overmining occurred at some of the caverns and as a result most of the caverns have migrated upwards through the overburden and some induced significant subsidence at the surface.
As the amount of data and especially measurements of these phase 1 caverns is scarce, the caverns needed to be reconstructed to enable a comprehensive analysis. In order to reconstruct the cavern development and final dimensions, the caverns have been simulated based on their historical production and on interpretations of the geology and logbooks. After cross-correlating the dimensions with the available data, the dimensions are used in an analytical model. Considering multiple influential parameters the post-production ‘residual’ volume and dimensions of the caverns are deduced. Thereafter the maximum potential migration is determined using a migration model.