Evaluating Mechanical Properties of Lightweight Cellular Concrete Backfill with Dynamic Cone Penetration Tests
Bibliographic record
Abstract
Dynamic cone penetrometer (DCP) has been commonly used for the evaluation and quality control/assurance of soils before, during, and after construction in civil engineering projects. This test equipment has been increasingly used for geotechnical engineering applications but not yet been used to evaluate lightweight cellular concrete (LCC) as a backfill material. This technical note reports laboratory and field DCP tests to evaluate the properties of LCC. To establish the relationship between DCP data and other material properties, unconfined compressive strength and California bearing ratio (CBR) tests were conducted on this material. The test results showed that the measured unconfined compressive strength and CBR of LCC increased as its density increased. The DCP indices (DCPI) for the LCC specimens at different densities were almost constant with the penetration depth. This technical note proposes the correlations between the DCPI and the unconfined compressive strength and CBR, which may be used for future applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".