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Experimental study on hydrogen-induced crack propagation of X80 steel under alternating pressure fluctuations

2024· preprint· en· W4404884282 on OpenAlex
Xiao Xing, Baogang Wang, Ruijing Jiang, Ruyu Nie, Gan Cui, Jianguo Liu, Yi Zhang, Han Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicMaterial Properties and Failure Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHydrogenMaterials scienceAlternating currentMechanicsMetallurgyPhysicsThermodynamics

Abstract

fetched live from OpenAlex

In this study, cyclic loading is applied to the specimen placed in an autoclave with varied hydrogen gas pressure. The effect of hydrogen pressure and stress fluctuations on the fatigue crack growth rate is analyzed. The results show that the crack growth rate increases with the increase of hydrogen pressure, and under 3 MPa hydrogen pressure, the crack growth rate can be enhanced by one order compared with that in air. With the increase of loading frequency, the crack propagation rate of a single block decreases in hydrogen, while the crack growth rate remains constant in air. As the maximum stress is fixed during cyclic loading, the fatigue crack growth rate increases with the stress range. Based on the experimental results, a predictive model is proposed to quantify the crack growth rate under different hydrogen pressure and loading conditions.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.301
Teacher spread0.254 · 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