Dice Method: A Novel Approach to Evaluate Stress States Across aRetaining Wall Backfill
Bibliographic record
Abstract
An analytical approach to predict the stress distribution across a frictional-cohesive backfill, considering pseudo-static inertia forces, is presented herein. Vertical slices adopted in a recently proposed log-spiral-Rankine method are discretized further into dices. The governing equations to determine unknown inter-dice forces acting on a dice are formulated by considering the requirements of force equilibrium, balance of angular moment, and a shape function for the shear stress distribution. Local and global iteration schemes are employed to solve highly coupled non-linear equations. Outcome of the proposed method for the variations of the normal and shear stresses are shown sound agreement with the results obtained from finite element analysis. The information of this method can be used to analyse the strain distribution, and then the deformation of the backfill, which can create a basis to develop a performance based design criteria for earth retaining systems.
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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 | 0.000 |
| 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".