Fluid flow simulation

A method of using a computer implemented neural network for a simulation of aerodynamic performance of a technical object having a geometry, the method comprising:

• training the neural network using a plurality of sets of encodings of pre-computed computational fluid dynamics, CFD, outputs, wherein the training is generated using inputs comprising:
• a geometry of at least one training technical object;
• spatial locations of input nodes of the neural network as node attributes;
• a relationship between the geometry of the at least one training technical object and the neural network input node locations;
• associated boundary conditions;
• operating conditions;
• and
• pre-computed CFD outputs comprising flow fields and aerodynamic performance parameters;
• the training using a loss function that evaluates an error between a neural network output and the pre-computed CFD outputs to produce a trained neural network;
• using the trained neural network with new simulation inputs to generate as output a predicted aerodynamic performance of the technical object, wherein the relationship between the geometry of the at least one training technical object and the neural network input node locations comprises a vector with at least two parameters.