Bibliographic record
Abstract
Geotechnical design engineers used to rely on arbitrary rules and definitions of "factor of safety" on peak soil strength in limit analysis calculations. They used elastic stiffness for deformation calculations, but the selection of equivalent linear elastic models was always arbitrary. Therefore, there is a need for a simple unified design method that addresses the real nature of serviceability and collapse limits in soils, which always show a nonlinear and sometimes brittle response. An approach to this method can be based on a new application of the theory of plasticity accompanied by the introduction of the concept of "mobilizable soil strength." This approach can satisfy both safety and serviceability and lead to simple design calculations within which all geotechnical design objectives can be achieved in a single step of calculation. The proposed method treats a stress path in an element, representative of some soil zone, as a curve of plastic soil strength mobilized as strains develop. Designers enter these strains into a plastic deformation mechanism to predict boundary displacements. The particular case of a cantilevered retaining wall supporting an excavation in clay is selected for a spectrum of soil conditions and wall flexibilities. The possible use of the mobilizable strength design (MSD) method in decision-making and design is explored and illustrated.Key words: retaining wall, plasticity theory, design, finite element.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".