Energy-Based Physics-Informed Form Finding for Clustered Tensegrity Structures
Tensegrity form-finding and physical property prediction are fundamental inverse problems in structural mechanics, which aim to determine equilibrium configurations and internal force distributions. These problems are challenging due to strong nonlinearity arising from the coupling between geometry and forces, the need to ensure structural stability, and the enforcement of constraints such as boundary conditions and symmetry. Moreover, traditional methods often lack robustness to noise and outliers. This paper proposes an energy-based learning framework for clustered tensegrity form finding an
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via arxiv author · 85%Jing Qin →
“Energy-Based Physics-Informed Form Finding for Clustered Tensegrity Structures”
- LinkedLinked via arxiv author · 85%Muhao Chen →
“Energy-Based Physics-Informed Form Finding for Clustered Tensegrity Structures”