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Compressed solutions with tensor methods

The predictive models created by École Centrale de Nantes in the context of STREAM-0D project need to be used with ease by users despite their complexity. To do so, ECN uses special encodings able to reduce complexity and allow the models to run in real-time.

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Sparsity and machine learning for design and optimisation

To operate in real-time, complex simulation models such the ones implemented in STREAM-0D need to cut down computational times while saving the reliability of information. This is where the notion of ‘sparsity’ comes into play.

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Reduced Order Models, augmented knowledge

For this new Bits Of STREAM-0D episode, the Institut de Calcul Intensif (ICI) of the École Centrale de Nantes explains why, in the last decade, Reduced Order Modeling (ROM) has emerged as a key tool in simulation-based engineering sciences.

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