This massive heat recovery steam generator uses hot gas exhaust to convert water in the pipes into steam for the turbines. Predicting corrosion to avoid downtime is challenging. Reduced order models aren't extremely accurate, and full simulation takes expertise and time. Siemens Energy is developing a digital twin with NVIDIA Modulus for the multi-phase turbulent flow. With point cloud data to train a physics-based AI model, they can infer high-fidelity flow shown by the streamlines in seconds. This could reduce downtime by 70%, saving the industry $1.7 billion a year.
Nvidia
53 second
landscape
low
Lavender,Light_Blue,Gray,Dark_Blue,Black,Dark_Gray,Off_White
shows a close up view of a metal tank
pollution, protective, hazard
1
architectural
lighthouse, building, chimney, factory, plant, power station, sky, tank
cool
Black,Dark_Blue,Gray,Dark_Gray,Dark_Blue,Black
shows the ceiling looking down inside of a building
, vibrant
2
architectural
building, ceiling, elevator, escalator, floor, person, man, office building, stairwell, terminal, walk
neutral
High
Black,Dark_Blue,Dark_Gray,Cyan,Royal_Blue,Dark_Blue,Light_Blue,Cyan,Gray,Royal_Blue
shows multiple large pipes and blue water
bizarre, energetic
3
architectural
building, ceiling, pillar, transporter, elevator, escalator, machine, neon light, pipe, slide, tube, water pipe
cool
High
Siemens Energy HRSG Digital Twin Simulation Using NVIDIA Modulus and Omniverse