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Record W2765914947 · doi:10.1063/1.4999918

Standoff high energy laser induced oxidation spectroscopy (HELIOS)

2017· article· en· W2765914947 on OpenAlexaff
J.-F. Daigle, Dominik Pudo, F. Théberge

Bibliographic record

VenueJournal of Applied Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsLaserSpectroscopyAluminiumOpticsOxideMaterials scienceBeam (structure)Laser beamsOptoelectronicsPhysicsMetallurgy

Abstract

fetched live from OpenAlex

High Energy Lasers (HELs) used for defense applications require operational distances ranging from few hundred meters to several kilometers. As the distance increases, the incident beam properties and, consequently, the anticipated effect delivered to the sample become less predictable. Therefore, the direct observation of the event induced by the laser can become an asset. In this paper, we propose a novel spectroscopic method that analyses in real time the spectral components present in the flames produced during the interaction of a HEL with a metallic piece at a long distance. This method was used on aluminum and carbon steel samples placed 200 m away from the laser system. It was discovered that the aluminum and iron oxides created as a by-product of the HEL reaction with the samples emitted clear fingerprint signatures that could be detected remotely using a spectroscopic receiver placed beside the HEL beam director. The real-time assessment of the laser-induced effect can be achieved by monitoring the temporal evolution of the oxide signatures, hence providing information to the operator about the reaction and the nature of the sample illuminated.

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 score0.018
Threshold uncertainty score0.758

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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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