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Arxiv
2d
43
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LT-PINN: Lagrangian Topology-conscious Physics-informed Neural Network for Boundary-focused Engineering Optimization
- Physics-informed neural networks (PINNs) are powerful tools for topology optimization and determining physical solutions.
- A new approach called Lagrangian topology-conscious PINNs (LT-PINNs) eliminates the need for manual interpolation in determining optimal topologies and physical solutions.
- LT-PINNs introduce specialized loss functions ensuring sharp and accurate boundary representations for complex geometries.
- LT-PINNs demonstrate superior performance in reducing errors, handling arbitrary boundary conditions, and inferring clear topology boundaries without manual interpolation.
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