Characterization and quality control of stone columns using surface wave testing
Bibliographic record
Abstract
Seismic surface waves are well-suited for the study of the elastic profile of soils. This study evaluates the application of surface waves in characterizing the properties of laterally heterogeneous soil, specifically for use in the quality control of stone columns used for ground improvement. Here, laterally heterogeneous soil refers to the gravelly sand material being formed into cylindrical columns and inserted into a homogenous clay bed. A scaled-down model of typical stone columns in a clay matrix was constructed. Measurements were made on stone columns of different dimensions, as well as on a defective column, under controlled conditions so that the properties of the materials used in the model under test were within limited ranges. Shear moduli obtained from the phase velocity determined from the controlled tests showed close agreement with those measured indirectly with the vane shear test. The dispersive curve produced in this study demonstrated an increased phase velocity with increasing wavelength for the measurements on the clay (between columns), and decreased phase velocity with increasing wavelength for the measurements on the column. More interestingly, the results showed that in the characterization of lateral nonhomogeneities, the phase velocity versus wavelength relationship varies for stone columns of different diameters and densities. These results point to the potential for estimating the phase velocity and, thus, the shear modulus of an effective region that spans both the lateral and depth axes, and also demonstrate that the results can be influenced by the positioning of sensors with respect to the survey target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".