A method for numerical simulation of a flow of a fluid in a space around a geometry, implemented by computer, including: a so-called deterministic sampling step, configured to process the initial mesh M0 as an input so as to obtain a set of so-called simulation multiscale meshes, the set of simulation messages including a number Z≥1 of subsampled meshes Mi; a step of generating a simulation result from at least one machine learning algorithm of the neural network type, previously trained from a database including a plurality of sets of so-called training multiscale meshes each associated with a numerical simulation, to provide a set of simulation data for all or some of the nodes of a mesh Mi; in the set of multiscale meshes obtained during the deterministic sampling step.