A discrete element model has been developed for geogrid-reinforced ballast. A model for unreinforced ballast has first been developed and evaluated using simulations of large-scale triaxial experiments and comparing with available data. A model for the geogrid has also been developed by bonding many small balls together to form the desired geometry and evaluated by simulating standard tests. The discrete element method (DEM) has then been used to model the interaction between ballast and geogrid by simulating pull-out tests and comparing with experimental data. The DEM simulations have been shown to predict well the peak mobilised resistance and the displacement necessary to mobilise peak pull-out force. The effect of the ratio of the geogrid aperture size to ballast particle diameter on pull-out resistance has also been investigated. The zone of influence of the geogrid has also been examined by simulating larger-scale pull-out tests in addition to cyclic triaxial tests. The method holds much promise as a tool for investigating aggregate–geogrid composite systems with a view to choosing appropriate geometries to optimise performance.

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Improving the long-term performance of deep geothermal reservoirs, as an energy source, can lead to a significant increase in efficiency of heat extractions from these assets. This will assist designers, energy firms, managers, and government decision makers to plan and maintain the use of limited available energy resources and hence enhance key sustainable development goals. Enhanced geothermal reservoirs possess a multi-phase behaviour with complex interrelationship between several parameters that makes the analysis and design of these systems challenging. Often, this challenge is increased when taking into consideration the optimum use of the available resources and induced costs during both creation and exploitation phases. This research presents a novel design approach developed to achieve efficiency and improved long-term performance in doublet enhanced geothermal systems (EGS). The proposed approach is based on an optimisation procedure using a numerical hybrid methodology integrating a multi-objective genetic algorithm with finite element analysis of fully coupled thermal hydraulic processes of reservoirs. The results of the optimisation process are discussed in comparison with data available from a benchmark case study. The results demonstrate a significant improvement in the long-term performance of EGS reservoir, both in terms of thermal power and costs when optimised using the proposed methodology.

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