Finite element modeling of fiber reinforced polymer bars embedded in prismatic concrete beams under high temperatures
Bibliographic record
Abstract
Numerous experimental tests and analytical investigation were carried out on thermal effects on fiber reinforced polymer bars reinforced concrete structures. Nevertheless, the finite element modeling of thermal behavior of fiber reinforced polymer bars embedded in concrete was insufficiently analyzed, particularly, for asymmetric problems. This paper presents a nonlinear numerical study using ADINA finite element software to investigate the effect of the ratio of concrete cover thickness to fiber reinforced polymer bar diameter ( c/d b ) on the distribution of transverse thermal stresses and deformations in fiber reinforced polymer bars and concrete cover for an asymmetric problem using prismatic concrete beams reinforced with fiber reinforced polymer bars submitted to high temperatures up to + 60℃. Also, to predict the thermal loads ( ΔT cr ) that produce the first radial cracks within concrete and the thermal loads ( ΔT sp ) which cause the splitting failure of the concrete cover as a function of the ratio of concrete cover thickness to fiber reinforced polymer bar diameter for an asymmetric problem. Nonlinear numerical results in terms of cracking thermal loads, thermal deformations, and thermal stresses are compared to those evaluated from analytical models and experimental tests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".