Upper-bound solutions of three-dimensional passive earth pressures
Bibliographic record
Abstract
This paper presents a novel approach to the determination of passive soil pressures: using the upper-bound method within the framework of limit analysis theory. It is based on a three-dimensional, kinematically admissible, rotational, hyperbolical failure mechanism. The failure mechanism is composed of the central and two lateral bodies, which are connected by a common velocity field. This approach is similar to two-dimensional stability analyses, where the log spiral potential failure surface is considered. The front surface of the central body interacts with the retaining wall; the upper surface can be loaded by surcharge loading; and the log spiral segment defines the curved failure surface of the central part. The cross sections of the lateral bodies are in agreement with the cross section of the central body. On the outer side, they are laterally bounded by a curved and kinematically admissible hyperbolic surface, which is defined by enveloping the hyperbolical half cones and part of the case surface of the leading half cone. The results give values for the passive soil pressure coefficients that are for most cases lower than the values determined by the upper-bound method of limit analysis for a translational failure mechanism, as published in the literature.Key words: limit analysis, earth pressure, passive pressure, failure surface, soilstructure interaction.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".