- Authors
- Yu Wang; Ribiao Liu; Huanhuan Lai; Hao Zhu; Yulong Chen; Daguang Han
- Journal
- Applied Sciences, 16(17), 8582, 2026
- DOI
- 10.3390/app16178582
- Licence
- CC-BY
- Role
- Corresponding author
Key findings
- The PINN wind solver reconstructs a three-dimensional steady-state wind field over irregular topography in about 0.12 s, with RMS velocity divergence below 2.1 × 10⁻³ — more than two orders of magnitude lower than linear interpolation.
- KD-Tree indexing with BFS connected-component analysis achieved 100% node-merging accuracy across fifteen production tower drawings, resolving pseudo-disconnections and nested block references.
- On a 220 kV line struck by Super Typhoon Meranti, the pipeline found seven at-risk members that code-based checking had missed, consistent with recorded field damage, and finished the full assessment in 34.4 s.
Abstract
Assessing whether existing lattice towers can survive extreme wind when they are located on ridgelines or at saddle points requires three questions to be answered simultaneously: how the local wind field is modified by the surrounding topography, how the structural geometry recorded in legacy computer-aided design (CAD) drawings can be recovered accurately, and which member fails first and by what mechanism. This paper couples a Physics-Informed Neural Network (PINN) wind solver, jointly constrained by mass and momentum conservation, with a graph-theory-based Drawing Exchange Format (DXF) parser and a closed-loop vulnerability screening module, so that all three questions are answered in a single automated pass. The PINN reconstructs the three-dimensional steady-state wind field over irregular topography in approximately 0.12 s, holding the root-mean-square (RMS) velocity divergence below 2.1 × 10−3 (more than two orders of magnitude lower than that of linear interpolation) while recovering the pressure-gradient-driven acceleration that mass-consistent variational solvers cannot represent. On the CAD side, k-dimensional tree (KD-Tree) spatial indexing combined with breadth-first search (BFS) connected-component analysis resolves the pseudo-disconnections, spurious intersections, and multi-level nested block references that are common in production DXF files, achieving 100% node-merging accuracy across fifteen tower drawings. A unified Vulnerability Index (VI) that combines strength, member stability, and plate buckling into a single scalar, updated through Sherman–Morrison rank-one perturbation at a millisecond cost, closes the diagnose–strengthen–verify loop without re-solving the full stiffness system. Applied to a 220 kV line struck by Super Typhoon Meranti, the pipeline identified seven at-risk members that code-based checking had missed, a result consistent with the recorded field damage, and completed the full assessment in 34.4 s, over three orders of magnitude faster than conventional practice.
Cite this work
@article{wang2026endtoendautomated,
title = {End-to-End Automated Wind-Induced Stress Simulation of Lattice Transmission Towers in Complex Terrain via Physics-Conserving PINN Wind-Field Reconstruction and Graph-Theory-Based DXF Parsing},
author = {Yu Wang and Ribiao Liu and Huanhuan Lai and Hao Zhu and Yulong Chen and Daguang Han},
journal = {Applied Sciences},
volume = {16},
number = {17},
pages = {8582},
year = {2026},
doi = {10.3390/app16178582},
}
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Author identity: ORCID 0000-0003-3787-963X · Google Scholar