A Quantitative Approach to Tensile Strain Capacity of Pipelines
Bibliographic record
Abstract
Tensile strain rupture is an ultimate limit state. A limit state is stated in generic terms of “load” and “resistance” or alternatively termed “demand” and “capacity.” The “demand” of tensile rupture limit state is mostly related to displacement-controlled loading, such as that induced by frost heave, landslide, and seismic activities. The “capacity” is most often controlled by girth weld tensile strain limits, as girth welds tend to be the weakest link in pipelines experiencing high tensile strains. The tensile strain limits of girth welds are affected by a large number of factors: tensile and toughness properties of the pipe and weld, weld geometry, stress state, defect size and location. Consequently, closed-form solutions for tensile strain limits of girth welds do not yet exist in codes and standards. PRCI and TransCanada have funded a number of projects in recent years to develop fracture-mechanics-based procedures aimed at quantitative determination of girth weld tensile strain limits. The results of these projects, along with the reviews and examination of available experiment data by the authors, have culminated in a set of recommended procedures that enable the quantitative determination of the tensile strain capacity of pipelines. The required input parameters, formulae for the computation of tensile strain limits, limits of applicability, and suggested methods of applications are specified in the proposed procedures. This paper covers the technical basis of the procedures. Particular emphasis is placed on the validation of these procedures. The limitations of the procedures and future directions of improvements are suggested. It is believed that these procedures may lay the initial groundwork towards the eventual code implementation of a comprehensive set of tools for quantitative strain-based design of pipelines.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".