Assessment of shear strength from measuring while drilling shafts in Florida limestone
Bibliographic record
Abstract
The focus of this research is the real-time assessment of drilled shaft capacity based on the unconfined compressive strength (qu) obtained from measuring while drilling (MWD). Measures of qu, a function of rock strength commonly used in drilled shaft design, are provided through five monitored drilling parameters: torque, crowd, rotational speed, penetration rate, and bit diameter. Monitored shaft installations took place at three separate locations on drilled shafts, which were subsequently load tested. Using the qu values obtained from MWD, side shear was estimated in portions of each shaft where instrumented segments indicated the side shear was fully mobilized for direct comparison. To consider all of the current side shear equations used in Florida drilled shaft design, the estimation of tensile strength (qt) in real time was also needed. This led to a theoretical approach to establish the qt/qu relationship that was later verified empirically and provided new correlations between material and mechanical properties of Florida geomaterials. A comparative analysis indicated that the results from multiple established side shear equations, used with qu from MWD, align well with the results obtained from load testing. This suggests that estimating drilled shaft capacity from MWD is viable to reduce spatial uncertainty.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".