Abstract: A method for simulating the combustion of a fluid in a combustion chamber, for the design of said combustion chamber, which includes: discretizing the space of the chamber into a given mesh; training a neural network by means of a learning set associating a graph corresponding to the mesh, the vertices of which have, as a value, progress variables predicted by a computational fluid dynamics simulation with local combustion quantities at these vertices; and an iterative simulation phase, where: the values predicted by the neural network of a local combustion quantity at the vertices of the mesh are provided as input to a solver, in order to obtain a value of a progress variable at each vertex of said mesh, and a graph corresponding to the vertices of the mesh is provided to said neural network, each vertex having a corresponding value of said progress variable, obtained by said solver, in order to obtain predicted values of the local combustion quantity at said vertices.

Abstract: A method for simulating the behavior of a system (20) composed of a subsystem (10), such as an aerial vehicle, in a physical environment (21) made of an incompressible fluid, comprising training a multilayer neural network (HNN) by means of a training set associating coordinates (x, y) in said physical environment (21) and respective values of a gradient of the current function (?) at said coordinates (x,y), and a loss function configured to minimize an error between a gradient (S?) of the output of said neural network and said gradient of the current function; using said neural network to predict a value of a current function (?) and a velocity field (u) by providing it with input coordinates.