Comparison of prediction provisions for drying shrinkage and creep of normal-strength concretes
Bibliographic record
Abstract
Calculating the response of concrete structures to loads that change with time, strain recovery under removal of load, relaxation of stress under constant strain, and redistribution of internal moments in indeterminate structures requires equations to predict the shrinkage and creep of concrete. Current North American practice would be to use the recommendations of American Concrete Institute ACI 209-82. The 2002 version of Eurocode 2 endorsed the use of the 1999 version of the 1990 Comité Euro-international du Béton (CEB) model code MC1990-99 shrinkage and creep equations. Baant and Baweja and Gardner and Lockman have proposed prediction methods, known as B3 and GL 2000, respectively, to replace the current ACI 209-82 provisions. The practitioner needs to know what method would be appropriate in what circumstances, what input information is required, and what is the probable uncertainty. This paper compares the shrinkage and creep predictions of ACI 209-82, CEB MC1990-99, B3, and GL 2000 with the experimentally measured results given in the Réunion Internationale des Laboratoires et Experts des Matériaux, Systèmes de Constructions et Ouvrages (RILEM) data bank for normal-strength concretes.Key words: concrete, creep, modulus of elasticity, shrinkage, strength development.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".