NotePrediction of early age curling in thin concrete topping over wood floor systems
Bibliographic record
Abstract
This paper presents finite element simulations of curling of unreinforced concrete topping laid over wood floor systems. The finite analysis consists of two parts. The first part calculates the relative moisture distribution with respect to the age of the concrete, while the second determines the topping curling deformation based on modulus of elasticity, density, and shrinkage of the concrete. With the finite element model the curling profile at any point in time can be predicted. Predictions agree reasonably well with measurements from a full-sized wood floor with a thin concrete topping. A model-based parametric study was performed. For the floor size investigated the results of the parametric study indicate that curling is greatly influenced by topping thickness and relative humidity of the surrounding air. Although the modelling as discussed is a preliminary approach, it provides a basis for further enhancements that will address factors such as creep and relaxation of concrete and deformation of the underlying floor system. Key words: finite element analysis, concrete topping, wood floor, curling, shrinkage.
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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) | 0.000 | 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".