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ABLATE is a UB CHREST project focused on leveraging advances in both exascale computing and machine learning to better understand the turbulent mixing and fuel entrainment in the combustion environment that is critical to the operation of hybrid rocket motors.

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Ablative Boundary Layers At The Exascale = ABLATE

ABLATE is a UB CHREST project focused on leveraging advances in both exascale computing and machine learning to better understand the turbulent mixing and fuel entrainment in the combustion environment that is critical to the operation of hybrid rocket motors. Documentation can be found at ABLATE Documentation along with a Getting Started Guide

Acknowledgements

This research is funded by the United States Department of Energy’s (DoE) National Nuclear Security Administration (NNSA) under the Predictive Science Academic Alliance Program III (PSAAP III) at the University at Buffalo, under contract number DE-NA000396

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ABLATE is a UB CHREST project focused on leveraging advances in both exascale computing and machine learning to better understand the turbulent mixing and fuel entrainment in the combustion environment that is critical to the operation of hybrid rocket motors.

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