Effect of footing width on<i>N</i><sub><i>γ</i></sub>
Bibliographic record
Abstract
By incorporating the dependency of soil friction angle (ϕ) on mean principal stress (σ m ), the effect of footing width (B) on bearing capacity factor (N γ ) is examined for a rough strip footing. The analysis is performed by means of a numerical lower bound limit analysis in conjunction with triangular finite elements and linear programming. To account for the variation of ϕ with σ m , a solution is obtained by using an iterative procedure. Two well defined ϕ–σ m curves from the literature, associated with Hoston and Toyoura sands that correspond to relative densities of 18% and 74.5%, respectively, are used. The magnitude of N γ is computed for different footing widths. It is noted that for B greater than about 0.2 m, the magnitude of N γ varies almost linearly with B on a log–log scale. For different footing widths, a good comparison is seen between the obtained rigorous solution and that obtained by using a constant value of ϕ, which corresponds to the equivalent mean normal stress level as defined by De Beer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".