A case study on the impact of fiber distribution on X-connections of complex-shaped UHPFRC footbridges cast with recyclable formwork
Bibliographic record
Abstract
Ultra-High Performance Fiber Reinforced Concrete (UHPFRC) is increasingly recognized worldwide for its potential in constructing innovative architectural footbridges. This study examines the influence of fiber distribution on the mechanical behavior of the X-connection, a critical structural detail in a novel latticework concept for UHPFRC footbridges, while also introducing an innovative approach using recycled wax formwork for shaping complex geometries. Following the architectural design process for the latticework UHPFRC footbridge, the methodology involves: (i) fabrication of fully recyclable wax formwork using CNC milling for two X-connection configurations with distinct crossing angles (i.e., the angle formed at the intersection of the X shape); (ii) gravity casting of UHPFRC, incorporating 1% steel microfibers; (iii) application of the magnetic inductance method (MIM) for non-destructive testing to evaluate fiber distribution, supplemented by fiber counting and image analysis of cracked sections post-testing; (iv) mechanical testing of the X-connection under bending to assess structural performance; and (v) a nonlinear Finite Element Analysis (NLFEA) to comprehensively examine the impact of fiber distribution. The findings underscore the pivotal role of fiber distribution in determining the ductility and strength of X-connections within the latticework UHPFRC footbridge, elucidating both the strengths and constraints of contemporary magnetic methods integrated with the Finite Element Method for accurately predicting the effects of fiber distribution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".