MétaCan
Menu
Back to cohort
Record W2939100804 · doi:10.5267/j.esm.2019.4.001

Experimental investigation and numerical prediction for the fatigue life durability of austenitic stainless steel at room temperature

2019· article· en· W2939100804 on OpenAlexvenueno aff
Muhammad Khairul, S.M. Sapuan, Faris M. AL‐Oqla, E.S. Zainudin

Bibliographic record

VenueEngineering Solid Mechanics · 2019
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilityMaterials scienceAusteniteMetallurgyAustenitic stainless steelLow-cycle fatigueComposite materialMicrostructureCorrosion

Abstract

fetched live from OpenAlex

This work investigated and predicted the fatigue life durability of Austenitic Stainless Steel 316L at room temperature due to its importance in plant industries worldwide.Modelling and simulations were performed to clarify the fracture as well as stress distribution using integrated mechanism.Experimental fatigue validations were also carried out to demonstrate the effect of various fatigue life parameters.Various loading conditions with variable load amplitudes were validated utilizing a frequency of 5 Hz and a stress ratio of 0.1.The accuracy of the simulation results were also verified based on the experimental data.High consistencies between the predicted fatigue life and the experimental results were achieved which increases the validity of the built model.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
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 designBench or experimental
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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEngineering Solid MechanicsSame topicFatigue and fracture mechanicsFrench-language works237,207