Load distribution characteristics of curved composite steel single-cell bridges at construction phase.
Bibliographic record
Abstract
In this thesis, a theoretical investigation on the elastic behavior of straight and curved non-composite single-cell box girder bridges is presented. A finite-element analytical model, based on the commercially available "ABAQUS" software, was used for the analyses. A shell element was used to model the steel web, bottom flange, and end-diaphragms. A three-dimensional beam element was adopted to model the top flanges, cross-bracings, and top chords. An extensive parametric study, using the finite-element modelling, was conducted, in which 15 non-composite single-cell bridge prototypes were analyzed to evaluate their load distribution factors for moment, reaction, axial force and deflection under dead load conditions. The span length of prototype bridges ranged from 20 to 100 meters. The width of the cell was taken as 3.0, 3.8, and 4.65 meters. The span-to-radius of curvature ratio was taken as 0, 0.4, 1.0, 1.4, and 2.0 for selected prototype bridges. The key parameters considered in this study were: the stiffness of horizontal bracing at the level of top flanges, number and stiffness of vertical cross-bracing and top-chord systems, width of the cell, degree of curvature, and span length. (Abstract shortened by UMI.)Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .L435. Source: Masters Abstracts International, Volume: 41-04, page: 1141. Advisers: John Kennedy; Khaled Sennah. Thesis (M.A.Sc.)--University of Windsor (Canada), 2002.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".