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Record W2315100523 · doi:10.1115/pvp2013-98028

An Evaluation of the Protection Against Local Failure in ASME Section VIII, Division 2: Finite Element Model Considerations

2013· article· en· W2315100523 on OpenAlexaff
Trevor G. Seipp

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsFinite element methodSection (typography)Element (criminal law)Structural engineeringGaussDivision (mathematics)Stress (linguistics)LimitingPlasticityPoint (geometry)Code (set theory)State (computer science)Function (biology)Computer scienceEngineeringMathematicsMechanical engineeringMaterials scienceGeometryAlgorithmPhysicsLawComposite material

Abstract

fetched live from OpenAlex

The local failure criteria was a relatively new inclusion in the 2007 Edition of ASME Section VIII, Division 2. The elastic-plastic evaluation criteria for this failure mechanism was brand new to the Code. This failure mechanism introduced to the Code the concept of local strain limits based on the triaxial state of stress. In implementing the evaluation of this failure mechanism, an interesting phenomenon was discovered. The triaxiality was to be calculated “everywhere” in the model, and used to create a limiting strain to be compared to the plastic strain at the point where said triaxiality was calculated. As is well known, in the finite element method, stresses and strains are calculated at the Gauss Points, and extrapolated to the nodes. This uses the element shape function. One question that arises is: if the triaxiality is calculated at the Gauss Points, can it be extrapolated to the nodes using the same element shape functions? Another question that arises is: can the extrapolated values of stress and strain be adequately used to calculate the triaxiality at the nodes? This paper discusses the validity of both approaches, and introduces a third option: a material property called Ductile Damage Initiation Criteria, and provides and example that demonstrate all three methods. Recommendations are provided about the best approach to be implemented.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.287

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 integrity0.0000.000
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 head0.033
GPT teacher head0.271
Teacher spread0.238 · 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
GenreEmpirical

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

Citations1
Published2013
Admission routes1
Has abstractyes

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