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Record W2789844382 · doi:10.1080/13588265.2018.1433348

An experimental study on the energy absorption characteristics of single- and bi-layer cups under quasi-static loading

2018· article· en· W2789844382 on OpenAlexafffund
M. A. Ghasemabadian, Mehran� Kadkhodayan, William Altenhof, Matthew Bondy, John Magliaro

Bibliographic record

VenueInternational Journal of Crashworthiness · 2018
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialExplosive materialLayer (electronics)WeldingAluminiumAdhesiveAbsorption (acoustics)Explosion weldingStructural engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Experimental testing was conducted to study the mechanical behaviour and energy absorption characteristics of single- and bi-layer cups under axial quasi-static compressive loading. Bi-layer plates were fabricated by explosive welding or joined by adhesive and were formed by a deep drawing process to produce the cup . The tests were performed at a rate of 10 mm/min. The effect of geometric parameters and other apparatus parameters were considered in this study. Results from the experimental tests showed that the layer order of the bi-layer cup significantly influences energy absorption capacities of the cup such that the structures with stainless steel as the outer layer has total absorbed energy and mean crush force 8% and 14% higher, respectively, than those of cups with the aluminium outer layer. Furthermore, it was observed that cups fabricated by explosive welding displayed mean crush force and specific energy absorption 1.5 times greater than those fabricated with adhesive.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.304
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2018
Admission routes2
Has abstractyes

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Same venueInternational Journal of CrashworthinessSame topicMechanical Behavior of CompositesFrench-language works237,207