PhysicsNeMo 2.1: one external-aerodynamics recipe for several datasets and models, GLOBE and out-of-distribution guardrails

NVIDIA publishes PhysicsNeMo v2.1.0 on GitHub. A new unified external-aerodynamics recipe trains DoMINO, Transolver, GeoTransolver or FLARE on DrivAerML, SHIFT-SUV, HiLiftAeroML or a user's own data, mixing datasets at run time through mesh datasets and non-dimensionalisation, with surface or volume data. The release adds the GLOBE model with AirfRANS and DrivAerML examples, concrete-dropout uncertainty estimates and an out-of-distribution guard (OODGuard) for GeoTransolver, a `physicsnemo.sym` module that replaces the separate PhysicsNeMo-Sym package for PDE residuals, and a multi-diffusion subpackage for patch-based training and sampling. PyTorch 2.5 becomes the minimum version.

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