Bibliographic record
Abstract
Sustainable engineering requires that engineering products are not only socially acceptable, economically feasible, and environmentally friendly, but also safe against all possible serviceability and ultimate limit states. Laterally loaded piles are mostly designed against the serviceability limit state of excessive lateral deflection. This study takes into account the uncertainties associated with the response of laterally loaded piles and focuses on their load and resistance factor design based on the serviceability limit state of excessive lateral deflection. Resistance factors are obtained for laterally loaded piles embedded in clay deposits in which the soil properties are assumed to be random variables. Pile capacities are determined based on a specified allowable lateral deflection at the pile head. The pile load-displacement curves are generated using the p-y method. Model uncertainties and bias factors are incorporated in the analysis. The uncertainties associated with the lateral capacity, for a specified lateral head deflection, are quantified, and the probability distribution of the lateral capacity is determined using Monte Carlo simulations. The applied dead and live loads are assumed to follow normal and lognormal distributions, respectively. First order reliability analysis is then performed using the distributions of loads and capacity to determine the load and resistance factors.
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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 | 0.002 |
| 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".