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Open Data

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Wetting hydrodynamics on inclined surfaces

AI models predicting droplet motion on inclined heterogeneous surfaces.

The RAISE-LPBF-Laser benchmark

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A large dataset on the effect of laser power and laser dot speed in powder bed fusion (LPBF) of 316L stainless steel bulk material.

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Training convolutional neural networks to estimate turbulent sub-grid scale reaction rates

Results of three Direct Numerical Simulations (DNS) of a methane-air slot burner.

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Actuated turbulent boundary layer flows

Results of highly resolved simulations of actuated turbulent boundary layer flows with varying parameters.

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Wetting hydrodynamics on horizontal surfaces

Training Fourier neural operator (FNO) models to predict droplet dynamics

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Particle Flow Reconstruction

This High-Energy Physics dataset contains terascale data on physics events with full GEANT4 simulation, suitable for Particle Flow (PF) reconstruction.

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m-AIA Testcases

Contains the reference solutions and test cases for the multi-physics simulation framework m-AIA.

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The CoE RAISE project have received funding from the European Union’s Horizon 2020 – Research and Innovation Framework Programme H2020-INFRAEDI-2019-1 under grant agreement no. 951733

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