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Record W4409544967 · doi:10.1121/10.0036496

Propagation of laser weak shock waves in a three-dimensional woven composite composite

2025· article· en· W4409544967 on OpenAlexaff
E Cuenca, Mathieu Ducousso, Nicolas Cuvillier, Laurent Berthe, François Coulouvrat

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldEngineering
TopicSurface Treatment and Residual Stress
Canadian institutionsSafran Electronics (Canada)
FundersCentre National de la Recherche Scientifique
KeywordsMaterials scienceAnisotropyShock waveShock (circulatory)LaserComposite materialOpticsMechanicsPhysics

Abstract

fetched live from OpenAlex

The propagation of a laser-driven shock wave in an aeronautic composite material is investigated. The material, made of three-dimensional carbon fiber lattices embedded in an epoxy matrix, is heterogeneous and anisotropic, due to the intrinsic anisotropy of the carbon fibers and to the weaving process. The shock is generated by a 10 ns laser pulse, focused on the material surface. Its ablation results in an expanding plasma, which induces a shock wave in the material with a peak compression stress of a few GPa. Starting from an optical microscopy visualization of the weaving, a differentiation between resin and fibers and a segmentation of the fibers lead to an evaluation of the material's local elastic properties below the laser spot position. The shock propagation is simulated using a nonlinear source model, combined with a time domain finite difference discretization of the equations of linear elastodynamics with Lebedev's scheme adapted to the material anisotropy. The high frequency content of the signal, the material heterogeneity and anisotropy induce a complex propagation. A measurement campaign has been performed for several samples and repeated laser illuminations. Experimental data are statistically compared to the model outputs and discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.228

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 head0.007
GPT teacher head0.227
Teacher spread0.219 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicSurface Treatment and Residual StressFrench-language works237,207