Utilization of finite element analysis for rapid curing of fiber-reinforced polymers in a novel two-phase curing technique for braided rebars
Bibliographic record
Abstract
This study focused on determining the capability of a proposed two-step curing process for composite rebars production. A finite element analysis is carried out on rapid curing of fiber-reinforced polymer rebars during a continuous braid trusion manufacturing process. This process combines pultrusion and braiding techniques to produce fiber-reinforced polymer rebars. The system uses a novel two-step curing technique to obtain a uniform cure profile. This is achieved by embedding small diameter steel wires within the core of the rebar. In the first step, as the rebar passes through an induction coil, a curing radially in the outward direction is initiated due to the induction coil. In the second step, the induction-initiated curing rebar enters a series of ovens, initiating radially inward curing. The resulting fiber-reinforced polymer rebars can be used as alternative to steel reinforcement in applications where steel cannot be utilized due to its corrosive or metallic nature. The result of this study showcased the importance of induction unit in obtaining a uniform cure profile.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".