FE stress analysis and prediction of the pull-out of FRP rods glued into glulam timber
Bibliographic record
Abstract
This paper focuses on the FE analysis of the mechanical behavior of glued composite fiber-reinforced polymer (FRP) rods into glulam timber, using a 3D-continuum damage mechanics. The application of FRP to the glulam timber beams, despite the fact of limited investigations to date, offers an interesting and economic solution for strengthening in timber construction. In particular, the use of glued-in FRP rods for timber connections instead of steel is of great interest, due to the improved durability of the joint systems compared to their equivalent counterparts made of steel rods. For pull-out tests, the estimation of the mechanical response of glued FRP rods into glulam timber is very complex because of the combination of the three different materials: FRP rods, epoxy resin and glulam timber as well as the complexity of the expected brittle modes of failure of the timber. On the other hand, the existing prescriptive approaches (standard design codes) did not cover all the modes of failure expected within timber material and their predictivity is highly depending on the loading direction and on the rod material. There is, therefore, still a need to establish a general and predictive FE model to simulate accurately and cost-effectively the glued-in rod timber connections. In this study, a FE model combining 3D continuum damage mechanics (CDM) and cohesive zone modeling approaches is presented and its effectiveness was verified by comparison to experimental results available in the literature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".