Pultruded fibre reinforced polymer reinforcements with embedded fibre optic sensors
Bibliographic record
Abstract
The use of the pultrusion process for the manufacture of fibre reinforced polymer (FRP) composites with embedded fibre optic sensors is discussed. The specific application is the use of smart composite reinforcements for strain monitoring in innovative concrete bridges and structures. The Bragg grating and Fabry-Perot fibre optic sensors are embedded during the pultrusion of FRP rods and the process-induced residual strains are evaluated using these sensors. The behaviour of optic sensors during pultrusion is assessed, and the effect of the embeddment of optical fibres and their surface coatings on the mechanical properties of the composite material is investigated. To verify the operation of the optic sensors embedded in the smart pultruded rods, mechanical tests were conducted and the output of the fibre optic sensors was compared to that of an extensometer. These mechanical tests were performed at room temperature as well as under conditions of low and high temperature extremes. The reliability assessment of the fibre optic sensors further entailed the study of their fatigue and creep behaviour as well as their performance when the rods in which they are embedded are placed in a severe environment (e.g., alkaline solutions) that may simulate conditions encountered in concrete structures wherein the composite rods will be used as prestressing tendons or rebars.Key words: smart composite reinforcements, fibre optic sensors, pultrusion, residual strain, fatigue and creep behaviour, reliability assessment.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".