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Record W1993258401 · doi:10.1063/1.3035831

Reconstruction of depth profiles of thermal conductivity of case hardened steels using a three-dimensional photothermal technique

2008· article· en· W1993258401 on OpenAlexaff
Hong Qu, Chinhua Wang, Xinxin Guo, Andreas Mandelis

Bibliographic record

VenueJournal of Applied Physics · 2008
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsThermal conductivityThermal diffusivityPhotothermal therapyMaterials scienceCollimated lightLaserOpticsThermalInverse problemPhotothermal spectroscopyThermal conductivity measurementConductivityEmissivityCube (algebra)Composite materialThermodynamicsGeometryChemistryPhysicsMathematicsNanotechnology

Abstract

fetched live from OpenAlex

A method of retrieving thermophysical depth profiles of continuously inhomogeneous materials is presented both theoretically and experimentally using laser infrared photothermal radiometry. This method represents the three-dimensional (3D) extension of earlier one-dimensional thermal-wave inverse-problem techniques for reconstructing inhomogeneous thermal-conductivity or diffusivity depth profiles. A 3D theoretical model suitable for characterizing solids with arbitrary continuously varying thermophysical property depth profiles and finite (collimated or focused) laser beam spotsize is developed. A numerical fitting algorithm to retrieve the thermophysical profile was demonstrated with three case hardened steel samples. The reconstructed thermal conductivity depth profiles were found to be well anticorrelated with microhardness profiles obtained with the conventional indenter method.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.581

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 head0.025
GPT teacher head0.227
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 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

Citations33
Published2008
Admission routes1
Has abstractyes

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