Dynamic analysis of cable roofs under transient wind: A comparison between time domain and frequency domain approaches
Why this work is in the frame
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Bibliographic record
Abstract
At present, high-speed computing capabilities and advanced nonlinear dynamic finite element procedures enable detailed dynamic analysis of cable structures. Although deterministic approaches require considerable analysis time and effort in relation to modeling, running, and data processing, they seem to be the only alternative to obtain high accuracy. Detailed dynamic analysis of cable roof networks is sophisticated and requires advanced modeling expertise. This paper presents a comparison between detailed nonlinear dynamic analysis and a simplified frequency domain approach to estimate the maximum probable response of weakly nonlinear cable roofs. The approach can be considered as alternative to detailed time-domain analysis in the preliminary design phase, or can be used to validate results obtained from more elaborated numerical models. The proposed method is illustrated with two examples of cable net roofs that were also analysed in the time domain.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it