Master
English

Machine Learning Based Fluid Solver for Shock Modeling

ContributorsZebad, Soheib
Number of pages44
Master program titleMaster en mathématiques, informatique et sciences numériques
Handover date2026-02-11
Defense date2026-02-13
Abstract

An existing 2D solver (CPU and GPU) for the Navier-Stokes equations in a supersonic regime is taken, and the most computationally expensive part is replaced by a neural network.

Citation (ISO format)
ZEBAD, Soheib. Machine Learning Based Fluid Solver for Shock Modeling. Master, 2026.
Main files (1)
Master thesis
accessLevelRestricted
Identifiers
  • PID : unige:191970
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Technical informations

Creation01/03/2026 15:02:52
First validation04/03/2026 14:08:49
Update04/03/2026 14:08:49
Status update04/03/2026 14:08:49
Last indexation04/03/2026 14:08:51
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