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Model reduction techniques allows companies to reduce the time needed to undertake complex computations as these computations are replaced with real time automatic AI models.

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Context

• We are proposing a unique dynamic modeling tool.

• The goal is to go further and to take into account the contact and friction in the reactor. Examples: Pellet clad interaction in a nuclear core, seismic motion.

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Challenge

• The time needed to model build the model is reduced as the data needed for parsimonious NN models is significantly reduced without compromising the accuracy.

• Nonlinear dynamic modeling is challenging because it is not addressable with traditional methods.

• Dynamic modeling is more challenging due to this being an almost chaotic scenario.

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Results

This model reduction for nuclear power production was thought to be an impassable limit, however, NeurEco easily overcame this limit and provided Framatome with an accurate, reliable and efficient solution.

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