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Record W2091192580 · doi:10.1115/1.3148467

Strain Uniformity in Biaxial Specimens is Highly Sensitive to Attachment Details

2009· article· en· W2091192580 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Biomechanical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsStrain (injury)Materials scienceFinite element methodGeometryEnhanced Data Rates for GSM EvolutionField (mathematics)Point (geometry)Composite materialStructural engineeringMathematicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

Biaxial testing has been used widely to characterize the mechanical properties of soft tissues and other flexible materials, but fundamental issues related to specimen design and attachment have remained. Finite element models and experiments were used to investigate how specimen geometry and attachment details affect uniformity of the strain field inside the attachment points. The computational studies confirm that increasing the number of attachment points increases the size of the area that experiences sensibly uniform strain (defined here as the central sample region where the ratio of principal strains E(11)/E(22)<1.10), and that the strains experienced in this region are less than nominal strains based on attachment point movement. Uniformity of the strain field improves substantially when the attachment points span a wide zone along each edge. Subtle irregularities in attachment point positioning can significantly degrade strain field uniformity. In contrast, details of the apron, the region outside of the attachment points, have little effect on the interior strain field. When nonlinear properties consistent with those found in human sclera are used, similar results are found. Experiments were conducted on 6 x 6 mm talc-sprinkled rubber specimens loaded using wire "rakes." Points on a grid having 12 x 12 bays were tracked, and a detailed strain map was constructed. A finite element model based on the actual geometry of an experiment having an off-pattern rake tine gave strain patterns that matched to within 4.4%. Finally, simulations using nonequibiaxial strains indicated that the strain field uniformity was more sensitive to sample attachment details for the nonequibiaxial case as compared to the equibiaxial case. Specimen design and attachment were found to significantly affect the uniformity of the strain field produced in biaxial tests. Practical guidelines were offered for design and mounting of biaxial test specimens. The issues addressed here are particularly relevant as specimens become smaller in size.

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 score0.263
Threshold uncertainty score0.734

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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