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Record W1540754468 · doi:10.1002/mawe.201400310

The robustness of the two‐colour assumption in pyrometry of solidifying AISI D2 alloy droplets

2014· article· en· W1540754468 on OpenAlexafffundabout
P. Delshad Khatibi, H. Henein

Bibliographic record

VenueMaterialwissenschaft und Werkstofftechnik · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSolidification and crystal growth phenomena
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsPyrometerShadowgraphMaterials scienceEmissivityDrop (telecommunication)SuperheatingMetallurgyTemperature measurementOpticsMechanical engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

A drop tube‐impulse atomization technique was used to produce D2 tool steel powders. Shadowgraph (Sizing Master Shadow from LaVision GmbH in Göttingen, Germany) was utilized to measure in‐situ velocity and droplet size. Simultaneously, the DPV‐2000 (Tecnar Automation Ltée, St. Hubert Quebec, Canada) was used to measure the radiant energy and droplet size of atomized droplets. These devices were mounted on a 3D translation stage which was designed, constructed and installed in the drop tube. The measurements were done at three different distances from the molten metal crucible, 4 cm, 18 cm and 28 cm. A thermal model of droplet cooling was coupled with the temperature of primary phase undercooling for D2 tool steel. The results from this model were used in order to find the emissivity behaviour of the droplets. It is shown that emissivity of the droplets is a function of size and temperature. It was concluded that the DPV‐2000 should be considered as a single color pyrometer since the gray body assumption for D2 tool steel falling droplets using DPV‐2000 during is invalid for the range of measurements taken.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.263
Teacher spread0.251 · 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 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

Citations3
Published2014
Admission routes3
Has abstractyes

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