Energy transfer and grain size effects during the Standard Penetration Test (SPT) and Large Penetration Test (LPT)
Bibliographic record
Abstract
The Standard Penetration Test (SPT) is the most widely used in-situ soil test in the world. "Large Penetration Test" (LPT) is a term used to describe any scaled up version of the SPT. Several types of LPT have been developed around the world for the purpose of characterizing gravel deposits, as SPT blow counts are less reliable in gravels than in sands. Both tests suffer from the lack of a reliable means of determining transferred energy. Further, the use of LPT blow counts is generally limited to calculation of equivalent SPT blow counts using correlation factors measured in sands. Variation of LPT blow counts with grain size is assumed to be negligible. This research shows that safety hammer energies can be reliably estimated from measurements of hammer impact velocity for both SPT and LPT. This approach to determining transferred energy is relatively simple, and avoids the primary limitation of existing methods, which is the inability to calibrate the instrumentation. Transferred energies and hammer impact velocities are collected from various sources. These data are used to determine the ratio between the hammer kinetic energy and the transferred energy (energy transfer ratio, ETR), which is found to follow a roughly Normal distribution for the various hammers represented. An assessment of uncertainty is used to demonstrate that an ETR based approach could be superior to existing energy measurement methods. SPT grain size effects have primarily been characterized as the variation of an empirical relative density correlation factor, (CD)SPT, with mean grain size. In this thesis, equivalent (CD)LPT data are back-calculated from measured SPT-LPT correlation factors (CS/L). Results of a numerical study suggest that SPT and LPT grain size effects should be similar and related to the ratio of the sample size to the mean grain size. Based on this observation, trend-lines with the same shape as the (CD)SPT trend-line are established for the back-calculated (CD)LPT data. A method for generating the grain size effect trend-line for LPT is then proposed. These trend lines provide a rational approach to direct interpretation of LPT data, or to improved prediction of equivalent SPT blow counts.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".