Remote Sensing for Ground Improvement Performance Verification—Hydrocarbon Storage Tanks Constructed on Deep Soil Mix Columns
Bibliographic record
Abstract
InSAR satellite-based settlement monitoring was performed on a 47.3-m diameter 18.3-m tall tank constructed over deep soil mix columns. Design settlement calculations estimated perimeter settlements between 60 and 90 mm. InSAR-based settlement measurements conducted over 1,792 days showed undulations corresponding to draining and filling operations and settlements between 52.4 and 70.4 mm at four locations on the tank perimeter. A calibrated soil-ground improvement model was developed to assess the validity of the InSAR settlements. Settlements predicted by the soil-ground improvement settlement model agreed with the InSAR measurements. The model also indicated the tank was between one-quarter and one-half full during the monitoring period, which explains why the InSAR detected and modeled settlements were less than the original settlement calculations. This study shows that InSAR can be used to monitor settlements of hydrocarbon storage tanks constructed over improved ground successfully.
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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 | 0.000 |
| 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) | 0.001 | 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".