Numerical modeling of compression behavior of foam concrete using representative volume element
Bibliographic record
Abstract
Foam concrete is an economical structural material in cast-in place and precast construction techniques. The microstructural of foam concrete is very complex due to random distribution of air voids. Previous experiments have shown significant effect of air void content and distribution on the compression behavior of foam concrete. While sufficient experimental characterization have conducted on foam concrete, limited theoretical investigations have been carried out to model the complex microstructure of foam concrete. In this paper, numerical modeling approach is proposed to simulate the behavior of foam concrete using Representative Volume Element (RVE) technique. A Finite element (FE) model was first developed and validated using available data in literature. The FE model was then extended to study the effect of several parameters on the behavior of foam concrete. Simulations results show significant effect of air void distribution and compressive strength of mortar on the compression behavior of foam concrete. In general, the simulations show that RVE technique can be used as a powerful tool for modeling the compression behavior of foam concrete.
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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 | 0.001 | 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".