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Identification of structural defects and their impact on the magnetic memory, static and cyclic strength of VNS9-SH thin sheet trip-steel

2024· article· en· W4398247640 on OpenAlex
A. A. Dubov, A. V. Yamchuk, A. A. Sobranin, A.K. Slizov, A. V. Arsenov, D. V. Prosvirnin, A. Yu. Marchenkov

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

VenueIndustrial laboratory Diagnostics of materials · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsMaterials scienceIdentification (biology)Composite materialStructural engineeringForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Identification of microstructure defects, which are stress concentrators (SC) during the operation of mechanical engineering products, is an important scientific and practical task relevant for manufacturing enterprises. This problem becomes especially urgent and difficult for critical helicopter parts made of sheet TRIP steel VNS9-Sh (23Kh15N5AM3-Sh) and operating under cyclic loads due to the complex microstructure of the steel and small thickness of strips and sheets. To assess the impact of structural defects on the cyclic strength of products made of the steel under study, the specimens were preliminary sorted proceeding from the results of their testing using the method of metal magnetic memory (MMM) and metallographic studies. The MMM method is a structure-sensitive procedure which provides information about the presence of structural defects that arise during the manufacture. Magnetic anomalies in the form of sharp local changes in the intrinsic stray magnetic field (SSMF) ( H ) and its gradient |Δ H | along the length of the controlled section Δ x , were identified on the surface of sheets cut from five different batches. A conventional classification of the identified anomalies was made according to the magnitude of the magnetic field gradient. The specimens of two types were cut in zones of magnetic anomalies and outside them: type 1 — for cyclic tests and type 2 — for metallographic studies. The geometric parameters and field gradient values of magnetic anomalies on specimens of type 1 and type 2 were the same. Metallographic studies in zones of maximum magnetic field gradient on type 2 specimens revealed defects in the form of a strip at the boundary of different structures, which is a structural stress concentrator (SSC) and a source of the inhomogeneity and changes in the magnetic properties. Type 1 specimens with similar magnetic anomalies and Type 1 specimens cut from sheets outside zones of magnetic anomalies were then selected for cyclic testing. Comparative tests for cyclic strength of the specimens with and without specified SSC were carried out. It is shown that the presence of SSC zones in the specimens reduces the number of cycles to failure during cyclic tests by 1 – 2 orders of magnitude compared to the specimens free of SSC. Based on cyclic tensile tests of specimens, a limiting value of the magnetic field gradient was determined that corresponds to the acceptable level of stress concentration on structural defects. This value is recommended for use as a rejection criterion when examining a new tape by the MMM method.

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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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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