Study of a Plastic Strain Limit Damage Criterion for Pipeline Mechanical Damage Using FEA and Full-Scale Denting Tests
Bibliographic record
Abstract
Pipeline constructed in rocky terrain is vulnerable to damages such as denting, gouging and other mechanical damages. In-line inspection (ILI) of these pipelines often reported several hundreds or even thousands of dents. Although most of these reported dents are well below 6% outside diameter (OD) depth limit as per ASME B31.8, few dents (sharp rock dents) with high strain could pose threat to integrity of the pipeline. Recently, strain-based models have been proposed to assess mechanical damage severity in pipelines. Attempts have also been made to characterize cracking susceptibility in rock dents using the critical strain based ductile failure damage indicator (DFDI) model. The objective of this study is to validate this model using full-scale denting tests conducted at the laboratory. Additionally, validation also extends to against the simplified DFDI model without finite element analysis (FEA). In this paper, the existing ASME strain limit and strain limit damage models are reviewed. The critical strain based strain damage model known as Ductile Failure Damage Indicator (DFDI) is then presented. The theoretical aspect of this model, including early work by Hancock and Mackenzie on strain limit (εf, reference failure strain) for ductile failure, is reviewed. The experimental aspect of material critical strain and its measurement using uni-axial tensile testing are then described. An elastic-plastic finite element analysis is employed to calculate DFDI, which is used to quantify the accumulated plastic strain damage and its susceptibility to cracking, and is validated using six full scale denting tests. Finally, the simplified strain limits for plain dent is proposed and validated.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".