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Mean-field Games and Nonlinear PDE
MFG
Mean-field Games and Nonlinear PDE

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SBP

Unveiling the potential of energy/entropy stable numerical methods for hyperbolic/mixed hyperbolic-parabolic PDEs

Matteo Parsani, Associate Professor, Applied Mathematics and Computational Science
Feb 13, 12:00 - 13:00

B9 L2 H1

algorithm Hyperbolic PDEs PDE parabolic-hyperbolic PDE SBP numerical methods for PDE's

Abstract The demand for increasingly multidisciplinary reliable simulations, for both analysis and design optimization purposes, requires transformational advances in individual components of future PDEs solvers. At the algorithmic level, hardware compatibility and efficiency are of paramount importance in determining viability on future hardware. However, equally important (if not more so) is provable algorithmic robustness which becomes progressively more challenging to achieve as problem size and physics complexity increase. We show that rigorously designed adaptive semi- and fully-discrete

Mean-field Games and Nonlinear PDE (MFG)

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