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Progressive Failure and Energy Absorption of Aluminum Extrusion Damage

2011· article· en· W1801079062 on OpenAlex
Ali Dadrasi, Mahmoud Shariati

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnergy science and technology · 2011
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsCrashworthinessExtrusionResponse surface methodologyMaterials scienceDeformation (meteorology)AluminiumStructural engineeringFinite element methodComposite materialAluminium alloyTube (container)Computer scienceEngineering

Abstract

fetched live from OpenAlex

Aluminim Tubular structures are of interest as viable energy absorbing components in vehicular front rail structures to improve crashworthiness. Desirable tools in designing such structures are models capable of simulating damage growth in Aluminim materials. This paper studied the deformation and damage behaviors of aluminum-alloy under crushing loadings.  The numerical analysis is carried out by Abaqus software. Subsequently, the collapse behavior of aluminim extrusion damage was experimentally characterized. Finally in order to find more efficient and lighter crush absorber and achieving minimum peak crushing force, response surface methodology (RSM) has been applied for optimizing the square aluminim extrusion tube. Key words : Damage; RSM; Crashworthiness; FEM

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 score0.085
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.012
GPT teacher head0.230
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