Full-scale bending test and parametric study on a 30-m span prestressed ultra-high performance concrete box girder
Bibliographic record
Abstract
Due to its structural efficiency, durability, and cost-effectiveness, ultra-high performance concrete was utilized to build the first highway overpass bridge in China. The bridge was made of prestressed ultra-high performance concrete box girders of four continuous spans of 30 m each. As the original design of such bridge was observed to be somewhat conservative, its cross-sectional dimensions, in the form of the box girder wall thicknesses were optimized in this research to lower the material cost in future bridge construction. Then, a full-scale simply supported ultra-high performance concrete box girder of 30 m span, incorporating the new box girder wall thicknesses, was fabricated and then tested under static loading to obtain research data to justify the revised design. The loading system was designed to examine the flexural behavior of the girder using two concentrated loads symmetrically located at the mid-span. Experimental results show that the optimized girder has a favorable ductile behavior and excellent flexural strength, which can meet the design requirements for serviceability and ultimate limit states. A finite element model of the tested girder was developed, using ABAQUS software, and then was verified using the experimental findings. A parametric study was then conducted to investigate the influence of key parameters on the structural response, namely, the reinforcement ratio, the number of the prestressing wires, and the web thickness. Recommendations on minimum and maximum compressive strength and tensile property of ultra-high performance concrete were proposed. Also, a simplified calculation method of prestressed ultra-high performance concrete box girder was developed based on a verified strain and stress diagrams for cross-sectional analysis. The proposed methodology can be used in future practice with confidence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".