Natural fissures/faults or pressure‐induced fractures in the caprock confining injected CO2 have been identified as a potential leakage pathways of far‐field native brine contaminating underground sources of drinking water. Developing models to simulate brine propagation through the overlaying formations and aquifers is essential to conduct reliable pre‐ and post‐risk assessments for site selection and operation, respectively. One of the primary challenges of performing such simulations is lack of adequate information about source conditions, such as hydro‐structural properties of caprock fracture/fault zone and the permeability field of the storage formation. This research investigates the impact of source condition uncertainties on the accuracy of leaking brine plume predictions. Prediction models should be able to simulate brine leakage and transport in complex multilayered geologic systems with interacting regional natural and leakage flows. As field datasets are not readily available for model testing and validation, three comprehensive intermediate‐scale laboratory experiments were used to generate high‐resolution spatiotemporal data on brine plume development under different leakage scenarios. Experimental data were used to validate a flow and transport model developed using existing code FEFLOW to simulate brine plume under varying source conditions. Spatial moment analysis was conducted to evaluate how uncertainty in source conditions impacts brine migration predictions. Results showed that inaccurately prescribing the permeability field of storage formation and caprock fractures in models can cause errors in leakage pathway and spread predictions up to ∼19% and ∼100%, respectively. These findings will help in selecting and characterizing storage sites by factoring in potential risks to shallow groundwater resources.
We propose a novel and efficient numerical approach for solving the pseudo two-dimensional multiscale model of the Li-ion cell dynamics based on first principles, describing the ion diffusion through the electrolyte and the porous electrodes, electric potential distribution, and Butler-Volmer kinetics. The numerical solution is obtained by the finite difference discretization of the diffusion equations combined with an original iterative scheme for solving the integral formulation of the laws of electrochemical interactions. We demonstrate that our implementation is fast and stable over the expected lifetime of the cell. In contrast to some simplified models, it provides physically consistent results for a wide range of applied currents including high loads. The algorithm forms a solid basis for simulations of cells and battery packs in hybrid electric vehicles, with possible straightforward extensions by aging and heat effects.
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