Bibliographic record
Abstract
This thesis addresses the analytical interpretation of selfboring pressuremeter testing curves in sands. Emphasis is placed on the development of a new approach to analyze the data and hence to derive reliable predictions of the basic soil parameters, namely the friction angle, the lateral stress and the shear modulus. The new methodology of interpretation relies on a “curve fitting” technique to match the experimental and idealized (model) curves, from which a set of fundamental soil parameters are derived. These parameters are linked to each other in the framework of the cavity expansion model adopted. Some of the elasto-plastic models currently available are adopted for use under the new methodology of interpretation. A new model that extends the rheological equations of Hughes et al, 1977 is also developed. Pressuremeter tests under controlled conditions are analyzed in order to verify the basic assumptions of the chosen models. Some of the best calibration chamber data from the University of Cambridge (Fahey, 1986) and from the Italian ENEL-CRIS laboratory (Bellotti et a!, 1987) are used for this purpose. Once the reliability of the chosen models is established, the new methodology of interpretation is applied to field pressuremeter data. Several high quality tests carried out by the writer in a granular site in Vancouver, Canada are analyzed. The results of both field and chamber tests confirm the reliability of the new interpretation approach proposed here. The new interpretation approach also provides the engineer with a technique to numerically quantify the disturbance of the testing curve. Using the new disturbance criterion ranges for “undisturbed”, “disturbed” and “highly disturbed” testing curves are proposed. This criterion aided in the establishment of the insertion procedure of the UBC selfboring pressuremeter, allowing optimization of the insertion technique and minimization of soil disturbance during selfboring. It is believed that the contribution given in this thesis aids pressuremeter practitioners to design more economical engineering works based on reliable soil parameters derived from the selfboring pressuremeter test. Simplicity and reliability are the essential features of the proposed methodologies of insertion, testing and interpretation described herein.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".