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Record W4390703671 · doi:10.1115/1.4064467

A Unified Fracture Model for X65 Pipeline Material Under Various Constraints Using the Extended Finite Element Method (XFEM)

2024· article· en· W4390703671 on OpenAlexaff
M. M. Shahzamanian

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExtended finite element methodFracture (geology)Finite element methodStructural engineeringMaterials sciencePlane stressStress (linguistics)Pipeline (software)Computer scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract It is generally accepted that the fracture strain is dependent on geometry/constraints in metals. However, the currently available implementation of extended finite element method (XFEM) assumes a fixed fracture strain criterion independent of the constraints. The objective of this paper is to develop and implement a variable fracture strain criterion in XFEM that is capable of predicting a wide range of fracture conditions in X65 pipeline steels with various crack tip constraints. Various small-scale tests with different out-of-plane constraints obtained from the literature were simulated using the XFEM in abaqus software. These tests included smooth bar, notched bar, single edge notch tension (SENT), and single edge notch bending (SENB) tests. For each test, the value of the maximum principal strain (Maxpe) as a fracture initiation criterion in the cohesive zone model (CZM) in XFEM framework was varied while keeping the fracture energy constant until the model was able to accurately replicate the reported experimental results. For each test, the crack tip constraints were characterized and the stress triaxialities and Lode angle parameters at the onset of fracture initiation were calculated from the models. The results allowed expressing of the fracture strain as an explicit function of stress triaxiality which was then implemented in abaqus XFEM using UDMGINI subroutine. For the sake of comparison, the tests were simulated in finite element method (FEM) using a similar damage initiation model, namely, the Johnson–Cook (J–C) model. A single model in XFEM was able to accurately replicate the experimental observations for all specimens and compared well to experiments in the way simulated by FEM damage model. However, it was observed that XFEM was more suitable to simulate specimens with pre-existing cracks such as in SENT and SENB tests since the crack grew through elements when mesh refinement was not required around the crack tips. Lastly, the simulated results were found to be less mesh sensitive in XFEM than in FEM damage models.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.291
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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