Flexural Capacity Enhancement of Timber Beams Partially Confining the Principal Compression Arch using Carbon Fiber Reinforced Polymer Composites
Bibliographic record
Abstract
Timber is widely used as a structural element because of its engineering and mechanical properties. This study focuses on the flexural behavior of timber beams externally reinforced with carbon fiber reinforced polymer (CFRP) composites at the tension face and the responses of the fundamental principal compression arch because of confinement from end anchorage. Beams of three different types of timber are studied. All the beams had the same length, width, and span length and were tested under four-point loading. Different CFRP lamination techniques were adopted, with and without U-clamp confinement as end anchorage, to investigate the flexural capacity enhancement of CFRP strips as reinforcement for timber beams. The profile of the principal compression arch is estimated experimentally from fundamental flexural strain-along-depth phenomena by post-processing high definition images extracted from test videos employing digital image correlation technique (DICT) in the MATLAB R2011a framework. Similar responses were found from finite element analysis using ANSYS 11.0. Effective confinement of the principal compression arch produced significant enhancements of flexural capacities and stiffness in the strengthened timber beams.
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 | 0.000 |
| 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 | 0.000 | 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".