A Hybrid Experimental and Computational Framework for Evaluating Wind Load Distribution and Wind-Induced Response of Multi-Span UHV Substation Gantries
Bibliographic record
Abstract
The structural safety of multi-span ultra-high-voltage (UHV) substation gantries is a cornerstone for the reliability and resilience of sustainable energy grids. The wind-resistant design of the structures is complicated by their complex modal behaviors and highly non-uniform wind load distributions. This study proposes a novel hybrid framework that integrates segmented high frequency force balance (HFFB) testing with a multi-modal stochastic vibration analysis, enabling the precise assessment of wind load distribution and dynamic response. Five representative segment models are tested to quantify both mean and dynamic wind loads, a strategy rigorously validated against whole-model HFFB tests. Key findings reveal significant aerodynamic disparities among structural segments. The long-span beam, Segment 5, exhibits markedly higher and direction-dependent responses. Its mean base shear coefficient reaches 4.34 at β = 75°, which is more than twice the values of 1.74 to 2.27 for typical tower segments. Furthermore, its RMS wind force coefficient peaks at 0.65 at β = 60°, a value 2.5 to 4 times higher than those of the tower segments, all of which remained below 0.26. Furthermore, a computational model incorporating structural modes, spatial coherence, and cross-modal contributions is developed to predict wind-induced responses, validated through aeroelastic model tests. The proposed framework accurately resolves spatial wind load distribution and dynamic wind-induced response, providing a reliable and efficient tool for the wind-resistant design of multi-span UHV lattice gantries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".