Planning and Optimisation Methods for Lunar In-Situ Resource Utilisation

Lunar water resources are expected to be used for space exploration and development in the future. These resources can be used for life support and rocket fuel to reduce the risks and costs associated with lunar settlement. There is a notable gap in literature relating to the planning and optimisation of lunar resource extraction. This thesis aims to address the problem by developing tools for planning and optimisation of In-Situ Resource Utilisation (ISRU) on the Moon, with a focus on H2O resources. The multidisciplinary tools currently used in the terrestrial mining industry are examined as possible solutions to fill the gap. However, several issues are identified with the direct transfer of these methods to ISRU. Four foundational areas of mining engineering are then expanded for off-Earth applications. These are geomechanics and modelling, mining system selection, extraction sequence optimisation and project valuation. For geomechanics, the Discrete Element Method (DEM) is used to determine the stability of regolith excavations on the Moon. This method is also extended to the development of ground engaging tools under lunar gravity. Conceptual proofs are shown for two novel mining systems using DEM, the Impact Excavator and Drill and Pull method. With further development, these new rock breakage systems can improve ISRU planning and optimisation by enabling the access of harder, higher grade icy regolith. Within literature, there are also numerous off-Earth mining systems described. A procedure is developed to objectively select a mining system for a range of possible space resource deposit types. The procedure utilises principles of Axiomatic Design to estimate the reliability of systems in the absence of experimental data. These system reliabilities assist in making selections that can be used as inputs for subsequent planning and optimisation activities. Traditional optimisation algorithms, such the Lerchs-Grossman pit optimisation method and other graph-based methods are next examined for their applicability to off-Earth mining. They are found to be incompatible when directly applied to ISRU and a new paradigm is developed based on Reinforcement Learning. This method has advantages over the traditional mine optimisation algorithms and solves many of the issues identified for ISRU. For example, it does not require uncertain financial inputs such as cost estimations or price forecasting. This particular weakness in financial inputs for off-Earth mine planning is also addressed for project valuations. An opportunity cost measure, the Propellant Payback Ratio, is shown to overcome many of the difficult input requirements of the traditional method for the purpose of ISRU project appraisal. It enables ISRU project appraisals to be conducted completely independent of the uncertain financial inputs mentioned. Overall, the thesis contributes to the expansion of the mining engineering discipline into the ISRU domain. Four interconnected areas of mining engineering are developed including: geomechanics, mining system selection, sequence optimisation and project appraisal. These are all part of a multidisciplinary approach to ISRU planning and optimisation. Although ISRU has so far not begun, the methods and tools developed here can be used to improve the future prospect of resource utilisation on the Moon