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electrolysis and fuel cells (SOEC and SOFC). By combining numerical modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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sensing, high-resolution plume modelling (MicroHH), and atmospheric chemistry transport models (LOTOS-EUROS, ECHAM-HAM). The focus will be on better characterizing fire emissions, smoke plume injection
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for pavement lifetime prediction, primarily in Dutch conditions. Foreseen challenges include data harmonization, key relationship extraction, scalability, metadata structuring, predictive modeling, and data
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modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic performance in fuel cell (biogas) and co-electrolysis