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Record W3131502038 · doi:10.1115/1.4050277

Experimental and Numerical Analysis of Shear Process of a High Particle Content Bonding Material

2021· article· en· W3131502038 on OpenAlexaff
Yizhan Yang, Jiliang Li, Jiankang Chen

Bibliographic record

VenueJournal of Applied Mechanics · 2021
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsImpact
FundersNational Safety Academic FundNational Natural Science Foundation of China
KeywordsMaterials scienceComposite materialShear (geology)MicrostructureAdiabatic shear bandPolymerExplosive materialShear bandChemistry

Abstract

fetched live from OpenAlex

Abstract In this study, polymer-bonded sugar (PBS) is used as a substitute material for polymer-bonded explosive (PBX), and the shear failure process of PBS under compressive loading. First, the shear failure process of PBS was analyzed by a series of experiments, and it was found that the shear band appearing on the surface of the specimen was not symmetrical. Further theory analysis showed that it was triggered by the evolution of asymmetric damage caused by internal defects in the material. In addition, through investigating the distribution of experimental scatters, we found that the material undergoes a relatively long period of internal microstructure adjustment before shear failure occurs, this adjustment will undoubtedly affect the evolution of the shear band. More importantly, a data density method was used to quantify the adjustment process. Finally, by using finite element simulation, the effects of matrix–particle interface strength on the mechanical response or damage evolution of the PBS were thoroughly examined. This research has reference significance for understanding the damage evolution process of high particle content composite materials.

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 score0.020
Threshold uncertainty score0.238

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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