Interfacial Parameters for Bridge Connections at High-Strength Concrete–Ultrahigh-Performance Concrete Interface
Bibliographic record
Abstract
There has been a rapid increase in the use of ultrahigh-performance concrete (UHPC) in bridge connections and in bridge rehabilitation. When using UHPC in bridge construction, one common recommendation is that UHPC reach a compressive strength of at least 97 MPa before allowing traffic loads. However, bridges are subject to other loads prior to being open to traffic, such as load due to construction equipment, shrinkage, and temperature. The interface bond strength and interfacial parameters, such as adhesion/cohesion and the shear friction coefficients at early ages, are important in determining the ability of connections to resist these types of loads early on after casting. In this study, the interfacial bond strength between high-strength concrete (HSC) and UHPC was determined using pull-off, bi-shear, and slant-shear test methods at different ages. These test methods provide values of bond strength for different stress scenarios at interfaces, and the resulting values of bond strength vary by the test used. The adhesion/cohesion coefficients were calculated using experimental data, and the mean values were found to be in the range of 1.9–3.6 MPa and 3.2–6.5 MPa under tension and shear, respectively. The friction coefficients were found to be in the range of 1.37–1.52 due to tension and 1.07–1.37 due to shear. This research found that the adhesion/cohesion and friction coefficients are much higher than the values reported in AASHTO for initially roughened surfaces.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".