Offer Description
This project is part of the European ERC Synergy project Karst https://erc-karst.eu/, which aims to develop a predictive flow model for an entire karst network. We will simulate water flows, possibly marked with tracers, in networks comprising millions of nodes. The flows will not necessarily be saturated, and nonlinear flow-rate//Dp relationships between the inlet and outlet of the conduits will lead to the resolution of a large system of nonlinear equations.
A first thesis project currently underway focuses on simplifying these large systems of discretized Laplacian-type equations, assuming the network is static at a given time t, by grouping the unknowns and managing the uncertainty due to the conductivity of the conduits. Solutions have been developed and are available in Python packages.
This second doctoral student will focus on dynamic aspects when, due to external forces, the network of conduits changes topology as a result of competition between the system’s recharge and drainage mechanisms. Reference simulations will be available following developments carried out by the Barcelona partner (openkarst code https://openkarst.org/) using data acquired in the field (Swiss partner).
In a final phase, the karst network will be dynamically evolved by modeling changes in the network’s geometry related to its drainage or filling due to external weather hazards, which can lead to major reorganizations of flows. Setting up monitoring techniques capable to anticipate such majors changes on the flow structure will be studied.
Real-world case studies from the ERC project or similar projects (K3, GEEAUDE) will be conducted. In a final phase, we will focus on speleogenesis, i.e., the emergence of karst structures due to fluid-rock interactions, a typical case of self-organization.
