Interface shear behaviour of ultra-high performance concrete under combined shear and lateral loads
Bibliographic record
Abstract
The use of ultra-high performance concrete (UHPC) in construction has expanded in recent years due to its superior mechanical properties, including enhanced compressive strength and improved post-cracking tensile resistance and deformation capacity. Structural components constructed with UHPC have exhibited improved response attributes in applications where conventional concretes have demonstrated deficiencies, such as precast concrete component connections where interface shear plays a key role in transferring loads and maintaining structure integrity. This study investigates the interface shear resisting behaviour of monolithically-cast UHPC push-off specimens subjected to combined shear and lateral loading. A comparative evaluation of existing shear strength estimation models is presented and the applicability of classical concrete failure criteria for unreinforced UHPC interfaces is assessed. The findings presented offer insight into the shear transfer mechanisms of unreinforced UHPC interfaces under varied stress conditions, demonstrate the relationship between interface confining pressure and interface shear strength, and provide a foundation for advancing design models for UHPC structural connections. • Push-off tests on UHPC specimens subjected to combined shear and lateral loading. • Investigation of UHPC shear strength, failure mechanism, and load-shear displacement responses. • Influence of lateral stress conditions on interface shear resisting performance of UHPC. • Evaluation of shear strength prediction models using experimental results. • Application of classical concrete failure criteria to unreinforced UHPC interfaces.
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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 | 0.000 | 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) | 0.001 | 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".