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The CNES solicited the expertise of Clemessy teams to contribute to the development of a fluidic system simulator using artificial neural networks

The need expressed by the CNES and Clemessy teams consisted in initiating a digital simulator enabling the reproduction of the real behaviour of the physical phenomena that occur on a fluidic system.

In order to better control this critical phase of the filling of its tanks with liquid hydrogen (LH2), a fuel with two-phase behaviour, the CNES, which excels in complex mathematical modelling, chose to consider AI, so as to obtain better results.

  • Production of an AI model (a model which is mainly based on LSTM recurrent and Conv1D convolutional neural network layers)
  • Import of DATASETs (data acquired via the Ariane 5 project and open data)
  • Implementation of a tailor-made web HMI (Human Machine Interface)
  • Modelling of the fluidic system
  • Launch of simulations
  • Visualisation of data predicted by Artificial Intelligences (via graphs and supervision-type view animations)