An Evaluation of the Placement and Fiber Orientation Factors based on Existing UHPC Codes and Standards
Bibliographic record
Abstract
In various infrastructure applications, ultra-high-performance concrete (UHPC) has been investigated widely for its exceptional structural and durability qualities. Although UHPC structures have proved structural stability at the structural level, fiber dispersion and fiber orientation due to casting procedure and construction processes remain concerns. Fiber orientation and structural performance of UHPC members are strongly influenced by the casting flow direction of freshly mixed UHPC, formwork geometry, rebar arrangement, casting device, and rheology of the mixtures. Different professional organizations across various countries have released UHPC design codes and guidelines, and each addressed fiber orientation in a distinctive way. An extensive review of the influence of various factors on fiber orientation in structural elements is presented in this article. A review of existing structural design guidelines for UHPC and steel fiber-reinforced concrete materials from France, Germany, Japan, South Korea, Canada, Switzerland, Australia, and the United States was conducted. The method used to account for fiber orientation and dispersion was discussed. The effect of undesirable fiber orientation was compensated by different design reduction factors introduced by several design codes. Additionally, this paper discusses the underlying rationale for these design factors. The paper concludes by making recommendations to design professionals and suggesting future research directions.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".