Shallow foundation load testing on natural Florida limestone: single rock layer and rock-over-sand subsurface
Bibliographic record
Abstract
This article presents three shallow foundation load tests under various layer conditions (single rock layer and rock-over-sand subsurface), rock strengths, and limestone formations. Rock coring with laboratory triaxial testing, standard penetration tests, seismic shear tests, and measuring while drilling tests were performed to identify the representative mass bulk dry unit weight ( γdt) and the spatial variability of γdt. The geometric mean and median γdt, together with seismic shear results, were used to characterize rock strength and stiffness. Each footing test was sized at 1.07–1.83 m to fit the 12.20 m load frame (8.01 MN capacity) using laboratory-assessed bilinear strength envelopes of the rock. Predicted bearing capacities with Florida bearing capacity equations provided reasonable estimates for three load tests. Mean and differential settlement, including spatial variability for a single footing on a heterogeneous rock layer, were captured with the Fenton and Griffiths method. For the settlement prediction of rock-over-sand subsurface, a parametric study was conducted for typical footing size, rock thickness, and mass properties with the finite element method (FEM), and a Winkler approach with a stress-dependent weighted harmonic mean modulus ( Eeq). The proposed method achieved good agreement with the FEM results and was validated with load tests.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".