Preflex Prestressing Technology on Steel Truss Concrete-Composite Bridge with Medium Span
Bibliographic record
Abstract
Guangdong Qingqiyong bridge is a prefabricated steel truss-concrete composite continuous rigid frame bridge with a span arrangement of 41 m + 70 m + 41 m, to prevent cracks of concrete deck on the bridge pier top section, prestress tendons are usually arranged inside of the concrete deck, after the connection between deck panels and steel truss, prestress tendons are tensioned to make deck compressed, it has been proved that this conventional prestress method is tedious for construction and it also results in a significant loss of prestress. In addition, stress of the top chords in the pier top section is very small in all construction stages, mainly ranges from -60 MPa to 50 MPa, thus failed to make full use of its material properties; therefore, preflex prestressing technology of steel truss concrete composite bridge (PPSC in short) was put forward based on preflex prestressing technology, then the detailed analysis was conducted. To validate the feasibility of PPSC, another case study-Wanzhou Bridge was carried out. Results show that the PPSC technology is feasible and it can avoid the use of prestress tendon, simplify the construction, make deck panels get the expected compressive stress easily and make full use of steel properties.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".