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HGTO

model1 events
papersTODAY 04:00 UTC

HGTO: Graph-Based Physics-Informed Formulation for Structural Topology Optimization

A new arXiv preprint introduces HGTO, a unified graph-based, physics-informed framework for density-based structural topology optimization. The approach reframes the usual nested loop of material updates, structural analysis, and sensitivity computation, drawing on neural density parameterization and dual-field physics-informed methods that require no labeled data. The abstract positions the work as a data-free alternative to conventional optimization pipelines.

research/physics-informed/optimization/graph-neural-networks