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Record W4409088373 · doi:10.1115/1.4068348

Depth and Velocity of Ablation Under a Constant Heat Flux

2025· article· en· W4409088373 on OpenAlex
Patricio F. Méndez, Umberto Prisco

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

VenueASME Journal of Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConstant (computer programming)AblationHeat fluxFlux (metallurgy)MechanicsMaterials scienceGeologyPhysicsHeat transferComputer scienceEngineeringAerospace engineeringMetallurgy

Abstract

fetched live from OpenAlex

Abstract Explicit closed-form expressions for the velocity, depth of ablation front, and penetration of the thermal profile valid up to a Stefan number of 30 (the vast majority of technological materials have a value below 10) and for all times in the problem of ablation under a constant heat flux are derived. The analysis is based on the blending of the asymptotic, transient, and steady-state, regimes of the above-mentioned quantities. Expressions to estimate the characteristic values representative of intermediate behaviors are also proposed. The prediction of depth and velocity of penetration calculated with the expressions proposed resulted in a maximum absolute error below 8% in comparison to the numerical solution. This model assumes a thick substrate and a criterion for minimum thickness is also proposed. Equations to predict the thickness of the heat-affected zone and of the mushy zone in ablation are also derived. The ultimate aim of this work is to provide simple and accurate expressions to predict the progress of the ablation or to select optimal process parameters in case ablation is used in manufacturing.

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)0.000
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 score0.054
Threshold uncertainty score0.302

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 head0.009
GPT teacher head0.225
Teacher spread0.217 · 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