Sustainable Design and Engineering: A Relationship Analysis between Digital Destructive and Non-Destructive Testing Process for Lightweight Concrete
Bibliographic record
Abstract
The development of sustainable lightweight materials is a promising field solution in this era. The production of sustainable materials by replacing coarse aggregates with some lightweight alternative provides a good quality construction material. In this study, rocky coarse aggregates were replaced by an ultra-lightweight material (i.e., expanded polystyrene beads) to produce an equivalent rock-solid mass of concrete. Using an M15 grade of concrete composition, expanded polystyrene (EPS) beads were added in place of aggregates in amounts ranging from 5% to 40% at a water–cement (w/c) ratio of 0.60. The specimen size as per American Society for Testing and Materials (ASTM) specification was 150 mm in diameter and 300 mm in length. Furthermore, statistical analysis for the relationship study for destructive testing (DT) (i.e., compressive test machine) and non-destructive testing (NDT) (i.e., rebound hammer and ultrasonic pulse velocity (UPV)) has been performed at developed specimens under 7- and 28-day curing conditions. In the end, the results showed that NDT predicts higher compressive strength than that of DT with the addition of EPS beads up to 20% aggregate replacement, after that it is vice versa for up to 40% aggregate replacement. This study will not only help in the production of sustainable lightweight materials, but especially concrete block production can also be performed at a large scale as a sustainable engineering solution.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".