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An Integrated Creep-Fatigue Theory for Material Damage Modeling

2014· article· en· W2070270865 on OpenAlexaff
Xi Wu

Bibliographic record

VenueKey engineering materials · 2014
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCreepMaterials scienceCoalescence (physics)SuperalloyNucleationGrain boundaryFracture mechanicsStructural engineeringComposite materialThermodynamicsMicrostructureEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents an integrated creep-fatigue (ICF) theory to describe the non-linear creep-fatigue interaction during thermomechanical loading. The ICF theory recognizes the damage evolution as a holistic process consisting of nucleation and propagation of surface or subsurface cracks in coalescence with internally distributed damage, leading to final fracture. In a polycrystalline material under combined cyclic and dwell loading, crack nucleation and propagation occurs by fatigue or oxidation mechanisms, whereas internally distributed damage often occurs in the form of grain boundary cavities or microcracks due to creep or dwell effects, particularly at high temperatures. Based on the above mechanism, a damage evolution equation is mathematically derived, and the generality of the above physical mechanisms warrants the applicability of the ICF theory over a wide range of stresses and temperatures. This paper uses Mar-M 509, a cobalt base superalloy, as an example to illustrate how the ICF theory describes creep and low cycle fatigue (LCF).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.012
GPT teacher head0.214
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations13
Published2014
Admission routes1
Has abstractyes

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