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Record W2901551029 · doi:10.25071/10315/35388

Application Of FBG Optical Sensors To In-Situ Monitoring The Thermo-Mechanical Behaviour Of Cold Spray Coated Samples

2018· article· en· W2901551029 on OpenAlex
Bahareh Marzbanrad, Farid Ahmed, Hamid Jahed, Ehsan Toyserkani

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

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceIn situOptical fiberTemperature measurementComposite materialOpticsMeteorologyPhysics

Abstract

fetched live from OpenAlex

In this research, a fiber Bragg grating (FBG) sensor is employed for monitoring thermal and mechanical strain induced by severe plastic deformation during high thermal and mechanical strain rate of cold spray technique. The FBG sensors are embedded in magnesium alloy substrates and the strain evolutions of the substrates are recorded during the cold gas spray coating process. In these experiments, the localized transient thermo-mechanical strain induced in the close vicinity of the substrate surface is monitored. Qualitative analysis of the complicated spectra shapes obtained during coating and cooling processes demonstrates the repeatability and sensitivity of the sensors in this condition. In addition, the obtained result from FBG sensors reveals the existence of compressive strain in the substrate near the interface during peening; however, it is released after a few second because of the high impact temperature of cold spray coating.

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)
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 score0.025
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
Bibliometrics0.0000.001
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 head0.248
Teacher spread0.237 · 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