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20112026
most citedArtificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control

572 citations

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cs.CE2022★ 19 cited

Simulation of continuous dynamic recrystallization using a level-set method

Victor Grand, Baptiste Flipon, Alexis Gaillac +1

Dynamic recrystallization is one of the main phenomena responsible for microstructure evolutions during hot forming. Consequently, getting a better understanding of DRX mechanisms…

cs.CE2020★ 10 cited

A new front-tracking Lagrangian model for the modeling of dynamic and post-dynamic recrystallization

Sebastian Florez, Karen Alvarado, Marc Bernacki

A new method for the simulation of evolving multi-domains problems has been introduced in previous works (RealIMotion), Florez et al. (2020) and further developed in parallel in th…

cs.CE2020★ 32 cited

A novel highly efficient Lagrangian model for massively multidomain simulations: parallel context

Sebastian Florez, Julien Fausty, Karen Alvarado +2

A new method for the simulation of evolving multi-domains problems has been introduced in a previous work (RealIMotion), Florez et al. (2020). In this article further developments…