Assessment of Parameters Influencing Mechanical Response of Constrained and Unconstrained Dents Using Finite Element Modelling
Bibliographic record
Abstract
Pipelines may experience damage (e.g. dent, gouge) during handling, installation and normal operations due to external interference. Pipelines in offshore environment may be prone to mechanical damage from events such as ice gouging, frost heave, and seismic fault movement. Damage mechanisms can be associated with deformation or metallurgical/metal loss that may include pipe dent, pipe ovality, ice gouging, pipe buckling, corrosion etc. The type and severity of pipe damage may influence operational, repair and intervention strategies. For conventional pipelines, the assessment of mechanical damage plays an important role in the development of integrity management programs that may be of greater significance for pipeline systems located in remote harsh environments due to remote location and logistical constraints. This study examines the effects of plain dents on pipe mechanical response using continuum finite element methods. ABAQUS/Standard (6.10-1) environment was used to simulate damage events and pipe response. Modelling procedures were developed and calibrated against physical and numerical data sets available in public domain. Once confidence in numerical procedures was achieved, an analysis matrix was established to account for a range of influential parameters including Diameter to wall thickness ratio (D/t), indenter diameter to pipe diameter ratio (ID/OD), hoop stress due to internal pressure to yield strength ratio (σh/σy), and kinematic boundary conditions. The results from this study provide a basis to support a broader initiative for developing an engineering tool for the assessment of damage interaction with pipeline girth welds and development of an engineering performance criterion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".