Analysis of cracking in steel fibre‐reinforced concrete (SFRC) structures in bending using probabilistic modelling
Bibliographic record
Abstract
Abstract An improvement to the probabilistic discrete cracking model for fibre‐reinforced concretes, originally developed by Rossi, is proposed in this paper. This new model features the following: – Crack formation and propagation in the concrete is taken into account by using special interface elements. These elements open once the normal tensile stress at their centre of gravity reaches the tensile strength of the element. The probabilistic aspect of the cracking process is taken into account by the fact that the tensile strength is randomly distributed throughout the mesh elements. – Immediately after the formation of cracks, the fibre bridging effect is considered by a damage model approach. The probabilistic aspect consists of randomly distributing the post‐cracking energy. The improved numerical model is used to analyse the bending behaviour of three SFRC beams made from the same material. The numerical simulations are compared with experimental results in terms of the global behaviour of and cracking processes in the beams.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".