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the Eulerian approach and the Lattice-Boltzmann Method (LBM) with Lagrangian bubble tracking, in collaboration with TUHH Improvement of closure laws for the two-fluid model based on novel experiments and LBM
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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ProLB and LBM including permanent researchers, three post-doctoral fellows and two additional PhD students. The Laboratoire de Mécanique des Fluides et d’Acoustique (LMFA) is a major research actor on
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, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent research and publish in peer-reviewed journals Strong written and verbal
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innovative tools combining high-fidelity simulations based on a Lattice Boltzmann Method (LBM) CFD code with advanced data assimilation techniques, notably the Ensemble Kalman Filter (EnKF). By integrating
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projects (in Polish and English) Close collaboration with other research groups within the LBM Laboratory and NCBJ, as well as with external partners participation in the implementation of scientific
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modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent research and publish in peer-reviewed journals Strong written and
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decision is made Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux
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multiphase flows Your tasks Develop and extend the in-house GPU-accelerated multiphase Lattice Boltzmann (LBM) code for DNS-grade boiling multiphase flow related to nuclear reactor operation, including bubble