Predicting Behavior of Grouted Dowel Connections Using Interfacial Cohesive Elements
Bibliographic record
Abstract
Grouted dowel connections are used extensively in precast load bearing walls owing to their simple construction and forgiving tolerances. Current design guidelines do not adequately consider the composite nature of such connections. Moreover, robust numerical models for these connections are yet to be developed. Therefore, a finite element model of grouted dowel connections was developed in this paper. The model adopts a phenomenological bond–slip constitutive law to predict the load versus slip response of grouted bars and considers tensile yielding of the reinforcement. The local bond–slip law used was generated from carefully designed experiments to eliminate spurious effects associated with bond testing. The model was validated using experimental results on grouted connections, as well as data retrieved from the open literature. Excellent agreement between experimental and numerical results was observed, highlighting the accuracy of the model in depicting interfacial stresses of the assembly. The model requires simple calibration, is computationally efficient, and can accurately simulate the failure behavior of bars embedded in grouted connections.
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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".