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This collaboration demonstrates how AI surrogate models can bypass the computational bottlenecks of traditional multiphysics simulations in industrial manufacturing. By predicting 3D melt-pool dynamics up to 100,000 times faster than standard tools, this Fourier Neural Operator enables real-time process control and digital twin deployment for laser welding applications.
Terra Quantum and Empa Develop AI Model for Laser Welding Prediction
Insider Brief PRESS RELEASE — Terra Quantum, a global leader in quantum technologies, and Empa, the Swiss Federal Laboratories for Materials Science and Technology, announced LP-FNO (Laser Processing Fourier Neural Operator), an artificial intelligence surrogate model that predicts full three-dimensional melt-pool dynamics in laser welding up to 100,000 faster than traditional multiphysics simulation. Removing the […]
Terra Quantum and Empa developed LP-FNO, a Fourier Neural Operator model that predicts three-dimensional temperature fields and melt-pool boundaries from laser welding parameters. The model was trained on high-fidelity simulations of Ti-6Al-4V across laser powers of 40–190 watts and scan speeds of 0.1–1 meter per second. Once trained, LP-FNO generates full 3D predictions in about 8 milliseconds at standard resolution and 88 milliseconds at twice the resolution. PRESS RELEASE — Terra Quantum, a…
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