Numerical techniques for design calculations of longitudinal bending in buried steel pipes subjected to lateral Earth movements
Bibliographic record
Abstract
This paper presents simplified finite-element analysis procedures based on geometrical nonlinearity and ductile Mohr-Coulomb-Davis plasticity for analysis of bending behaviour of steel pipes subjected to lateral soil loading. A simple, and easy to implement, user-defined subroutine to represent soil stiffness using the Janbu model is also presented and discussed. The development of a three-dimensional (3D) finite-element model is presented, and its evaluation against experimental measurements is discussed. Data are presented for different burial depths of the pipe, including soil loading on the pipe as well as 3D responses, longitudinal bending deflections and pressure distribution along the pipe. It was shown that numerical analyses which include soil modulus dependency on confining pressure lead to effective 3D calculations of pulling forces, bending moments along the pipeline and flexural deformations, based on measured soil parameters. The 3D analysis model requires the use of lower order (linear displacement) elements, which overestimated peak mobilized load. However, those 3D calculations effectively provided the progress of both the load-deflection and longitudinal bending response of the steel pipe at embedment ratios up to 5 where most energy pipelines are buried.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".