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Record W2901352903 · doi:10.5539/mas.v12n12p102

Laser Shock Peening Application as Alternative Method to Determine the Mechanical Properties of Aluminum

2018· article· en· W2901352903 on OpenAlexvenueno aff
Saad N. Abood

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldEngineering
TopicSurface Treatment and Residual Stress
Canadian institutionsnot available
FundersAl-Nahrain University
KeywordsMaterials sciencePeeningDuctility (Earth science)Shock (circulatory)AluminiumModulusComposite materialSubstrate (aquarium)Elastic modulusUltimate tensile strengthStress (linguistics)Shock waveParticle (ecology)Residual stressThermodynamics

Abstract

fetched live from OpenAlex

The structural, physical, and mechanical properties of laser-induced shock peening (LSP) of Aluminum before and after depositing films of different metals (Cu, In, and Al) were investigated. The deposition of single and double films was conducted, and the physical property (density), shockwave properties (shock pressure, particle velocity, and shock velocity), mechanical properties (stress, strain, Young's s modulus, and Hardness) were calculated, Young's s modulus measured of aluminum was measured by classical method (Tensile test ) and by LSP technique, and it was found that the measured using LSP is closer to the standard value than classical method .Single film Cu and sandwich Al / Cu deposited on Al substrate showed an enhancement in the mechanical properties rather than other films, while the deposited films of (In, In / Cu, and Al /In) on Al substrate revealed more strain and higher ductility than others.

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 score0.357
Threshold uncertainty score0.277

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 head0.028
GPT teacher head0.272
Teacher spread0.243 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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