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Using Hybrid Physics-Informed Neural Networks for Digital Twins in Prognosis and Health Management

Read about a success story of SimNet’s application in the use of hybrid PINNs for digital twins in prognosis and health management. 11 MIN READ
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Meet the Researcher: Dr Emanuel Gull, Theoretical and Computational Condensed Matter Physics

‘Meet the Researcher’ is a series in which we spotlight different researchers in academia who use NVIDIA technologies to accelerate their work. 4 MIN READ
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Using Physics-Informed Deep Learning for Transport in Porous Media

Simulations are pervasive in every domain of science and engineering, but they are often constrained by large computational times, limited compute resources… 8 MIN READ
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NVIDIA SimNet v21.06 Released for General Availability

NVIDIA SimNet is a physics-informed neural network (PINNs) toolkit, which addresses these challenges using AI and physics. 7 MIN READ
Technical Walkthrough 0

Scaling Inference in High Energy Particle Physics at Fermilab Using NVIDIA Triton Inference Server

In a series of studies, physicists from Fermilab, CERN, and university groups explored how to accelerate their data processing using NVIDIA Triton Inference… 9 MIN READ
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NVIDIA SimNet v20.12 Released

With this release, use cases such as heat sinks, data center cooling, aerodynamics and deformation of solids in linear elastic regime can be solved. 4 MIN READ