Design of precast UHPFRC retaining walls – Experimental and numerical validations
Bibliographic record
Abstract
This paper focuses on the design as well as on the experimental and numerical validations of the mechanical behavior of a precast ultra-high performance fibre reinforced concrete (UHPFRC) retaining walls. The design, made in accordance with the Canadian Highway Bridge Design Code ( CSA S6, 2019 ), led to the fabrication of a full-scale UHPFRC retaining wall with 3% fibre content which had dimensions of 3 m in height, 2 m in length, 2 m in width, with two vertical and horizontal stiffeners, and very thin vertical and horizontal panels of 40 and 65 mm, respectively. The experimental tests showed that the UHPFRC retaining wall exceeded by 42% the ultimate limit state (ULS) design factored bending moment and showed a very ductile behavior under flexural loading. At service limit state (SLS), the retaining wall had maximum crack opening between 0.15 and 0.28 mm, and a maximum lateral displacement of 4 mm. The finite-element model developed for the application captured accurately the flexural behavior of the UHPFRC retaining wall and was used later in parametric studies to optimize the design. The retaining wall optimal design includes UHPFRC with 3% fibre content and stiffeners with variable cross-section which allows volume reductions of 73% for concrete and 86% for rebars in comparison to the conventional reinforced concrete design.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".