Behaviors of Drained Lateral Extension for Saturated Sand and Their Applications
Bibliographic record
Abstract
Abstract Practically all retaining walls may rotate, yet movements of the wall could be restricted, particularly under working conditions. Since the earth pressure on the retaining wall often deviates from the fully active state, there is a need for predicting the earth pressure at any wall movement. The shearing behavior of backfill behind the wall plays an essential role for predicting the redistributions of earth pressure for different wall movements. This paper studies 25 sets of test for analyzing the drained lateral extension behaviors of saturated Ottawa sand. Three methods are used to interpret the active state of specimens and it is found that the monotonic increasing property of the σ'cs– εrpplot obtained by using the (q')maxmethod is more obvious than those obtained by the other two methods. Where σ'csis an initial confining stress of specimen for lateral extension test, and εrpis a radial strain of specimen developed at the active state. The specimens, with the relative density between 15% ∼ 90% and with the confining stress between 80kPa ∼ 280kPa, range their values of εrpfrom −1.18% to −2.99%. The magnitude of εrpcan be used to judge the secure level of deformation for a retaining structure. Subsequently, this study derives a formula to predict the redistribution of earth pressure on a retaining wall when the wall moving outwards based on the results of those lateral extension tests. This prediction method is a new approach to study the problems of earth pressure. Comparisons of predicted results from numerical solutions technique and observations from model tests show that the performance of this method is reasonable.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".