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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 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)0.000
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 score0.198
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
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 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

Citations4
Published2019
Admission routes1
Has abstractyes

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