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Record W2031382734 · doi:10.1063/1.3670005

Effects of cryogenic temperature on dynamic fragmentation of laser shock-loaded metal foils

2011· article· en· W2031382734 on OpenAlexfundno aff
T. de Rességuier, E. Lescoute, D. Loison, J.-M. Chevalier, F. Ducasse

Bibliographic record

VenueJournal of Applied Physics · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
FundersHeart and Stroke Foundation of Canada
KeywordsHypervelocityShadowgraphyMaterials scienceSpallationBrittlenessInertial confinement fusionLaserCharpy impact testShock (circulatory)Composite materialAluminiumThermal shockUltimate tensile strengthOpticsNeutronNuclear physicsThermodynamics

Abstract

fetched live from OpenAlex

Although shock-induced fracture and fragmentation of materials at low temperatures are issues of considerable interest for many applications, such as the protection from hypervelocity impacts in outer space or the ongoing development of high energy laser facilities aiming at inertial confinement fusion, little data can be found on the subject yet. In this paper, laser driven shock experiments are performed on gold and aluminum samples at both ambient and cryogenic (down to about 30 K) temperatures. Complementary techniques including transverse optical shadowgraphy, time-resolved velocity measurements, and post-recovery analyses are combined to assess the effects of target temperature upon the processes of microjetting, spallation, and dynamic punching, which are expected to govern fragments generation and ejection. The results indicate that cryogenic temperature tends to reduce the resistance to tensile and shear stresses, promotes brittle fracture, and leads to slightly higher fragments ejection velocities.

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 score0.046
Threshold uncertainty score0.492

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 head0.230
Teacher spread0.223 · 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

Citations14
Published2011
Admission routes1
Has abstractyes

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