Optimization and Parametrization of Industrial NURBS Geometries
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Constraint-driven Optimization and Parametrization of Industrial NURBS Geometries via Neural Deformation Field
new Abstract: This work presents a differentiable framework for the parametrization and shape optimization of industrial CAD geometries represented by multi-patch NURBS surfaces. The method enables the deformation of complex CAD models through a physics-informed geometric parametrization, allowing direct morphing driven by physical constraints without the need to prescribe a predefined deformation strategy. A neural displacement field, implemented as a multi-layer perceptron acting on the...