Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite several full-scale applications in Canada, the vibrational characteristics and performance of aluminium pedestrian bridges have not been studied comprehensively in the literature. There is a large degree of variability between design codes and standards, particularly in North America and Europe. This is in part due to a lack of comprehensive experimental test data on full-scale pedestrian bridges. This is compounded by a lack of agreement between researchers on the characterization of pedestrian induced loads and the interaction between loads and the structure. This thesis aims to bridge this gap by building and testing full-scale aluminum pedestrian bridges in a controlled laboratory test program. Results from the experimental program are presented, discussed in detail, and used to estimate the vibration characteristics of an aluminium pedestrian bridge of various lengths. These characteristics include the modal properties -- natural frequency, damping ratio, and mode shapes -- and human-structure interactions measured using accelerometers, load cells, and strain gauges. Using multiple signal processing techniques, these characteristics were extracted from the data. The results from the pedestrian loading tests were then used to assess the bridge specimens through the above-mentioned design codes. Finite element models of each specimen were built and used for parameter studies and model verification. \n \nThese data from full-scale pedestrian bridges are likely to shed new light on their vibrational behaviour and performance, and allow aluminium bridge designers to create competitive alternatives to bridges constructed with conventional materials. It is also anticipated that these tests will form a foundation for future research in the area of pedestrian bridge load modelling.
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.
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) | 0.000 | 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 it