A concrete sandwich wallboard damage identification method based on strain energy density increment
Bibliographic record
Abstract
During the loading process of concrete members, the identification of characteristic damage states is not sensitive enough. This paper investigates the damage evolution of four concrete sandwich wallboards subjected to vertical compression by employing the strain energy density increment to enhance identification sensitivity. First, the equivalent elastic modulus model for a wallboard subjected to vertical compression is established based on the material stress–strain relationship. Then, the strain data of concrete, obtained from experiments and numerical simulations, are modeled as the normalized unit approximate strain energy density increments (NUASEDIs), which follow the damage evolution of the wallboard as a more sensitive index. The first cracking formation of wallboard corresponds to the first high NUASEDI. The failure damage state corresponds to the final high NUASEDI, which reflects the process changing from the local to the global failure. Finally, the strain energy density increment theory improves averagely the cracking identification sensitivity of concrete members by 13.32% and the failure identification sensitivity by 3.01%.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".