Development of a Procedure for Fatigue Design of Slender Support Structures Subjected to Wind-Induced Vibration
Bibliographic record
Abstract
Cantilevered signal, sign, and light support structures are used nationwide on major Interstate highways, national highways, local highways, and at local intersections for traffic control. Recently, a number of failures of these structures have been characterized as wind-induced fatigue failures. It is widely accepted that there is considerable lack of accuracy in the calculation of wind-induced loads on high mast light poles (HMLPs) in both the AASHTO and the Canadian Highway Bridge Design Code provisions. A coupled model for predicting buffeting- and vortex shedding–induced response for slender support structures was developed. To accomplish this, monitoring of long-term response behavior of an HMLP subjected to wind-induced vibration and wind tunnel experiments was used to study global behavior and to extract important parameters. From the long-term field monitoring and wind tunnel experiments, the two critical types of wind vibration (natural wind gusts or buffeting and vortex shedding) were individually identified for in-depth analysis. Finally, a coupled dynamic model in time domain was developed for predicting the wind-excited response and was validated by comparing the simulation results with the field-collected data. The fatigue life of a specific HMLP was also estimated with the stress amplitudes predicted by the time-domain model and was validated with statistical extrapolation of the field data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".