Physics-based-loss-and-machine-learning-approach-in-application-to-viscous-fluids-flow-modeling
The premium Open Source alternative to Ansys Fluent
🎯 Best for:Engineers modeling complex, non-linear fluid dynamics using machine learning.
What is Physics-based-loss-and-machine-learning-approach-in-application-to-viscous-fluids-flow-modeling?
An alternative to traditional finite element methods for modeling viscous fluid flows. It uses physics-informed neural networks and energy-based variational principles to simulate non-Newtonian fluids like blood and rheomagnetic materials.
Tech Stack
Jupyter NotebookPhysics & Astronomy
Why Physics-based-loss-and-machine-learning-approach-in-application-to-viscous-fluids-flow-modeling?
- • Handles non-Newtonian fluids
- • Energy-based accuracy
- • Flexible physics-informed loss
Limitations
- • High compute requirement
- • Complex mathematical setup
- • Research-oriented codebase
9/28/2025
Last Update
0
Forks
0
Issues
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License
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Competitor Cost
-$1,440
/ year (est. based on Ansys Fluent)
Self-Hosted
$0
/ year
Team Size10 Users
150+
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