Simulation of a large-scale airlift pump taking into account uncertainties. Application to the optimization of a new urban geothermal system

This PhD thesis is part of the ANR project 'Uncertain Flow Optimization' (UFO). The project is devoted to the development and application of efficient uncertainty quantification methods for flow analysis and optimization. In this framework, these methods are applied to the study of a large-scale airlift pump. The airlift pump is selected to be part of an innovative geothermal system, which can be exploited within an urban environment. We wish to quantify and optimize the energy potential of this new system with numerical tools. They provide both good accuracy and efficiency properties. The airlift two-phase flow simulation is based on a quasi one-dimensional drift flux model, which is implicitly solved. The solver is validated by comparison with relevant experimental airlift studies from the literature. However, these studies remain below the kilometric-targeted pipe length. Thanks to the analysis of two uncertainty quantification methods, a non-intrusive approach relying on polynomial chaos expansion and a new semi-intrusive method developed ahead of the UFO project, we perform airlift pump simulations taking into account physical and modelling uncertainties. This numerical tool is inserted into a simplified model of the complete urban geothermal system that involves surface devices, such as an air compressor. Finally, a robust preliminary optimization process is performed for two versions of the proposed geothermal urban system. They are designed respectively for heat recovery and electricity production. (author)