Room-level conditional graph neural networks for shear wall layout generation in high-rise buildings

Hao Leng

doi:10.1016/j.autcon.2026.107189

Room-level conditional graph neural networks for shear wall layout generation in high-rise buildings

2026-08-11

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AI

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Hao Leng

Y

Ying Zhou

Y

Yuqing Gao *

DOI：10.1016/j.autcon.2026.107189

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Abstract

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• Room-level graphs encode spatial semantics and boundary feasibility. • FiLM conditioning enables discrete density-controlled wall generation. • Dual-stream training improves compliance with sparse paired labels.

Keywords:

Structural design automation

Shear wall layout

Graph neural networks

Conditional generation

Room-level representation

Room-level conditional graph neural networks for shear wall layout generation in high-rise buildings

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