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Record W4408302012 · doi:10.1080/15376494.2025.2471034

Study on the low-velocity impact response and mechanism of polyaspartic ester polyurea coated aluminum plate

2025· article· en· W4408302012 on OpenAlexaff
Suchao Xie, Kunkun Jing, Jing Zhang, Yuxing Cui, Lingzhi Yang, Fengyi Zhang

Bibliographic record

VenueMechanics of Advanced Materials and Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsMinistry of Education and Child Care
FundersScience and Technology Program of Hunan ProvinceNational Natural Science Foundation of China
KeywordsPolyureaMaterials scienceMechanism (biology)AluminiumShakerPolyaspartic acidComposite materialStructural engineeringEngineeringChemistryPhysicsPolyurethaneAcousticsOrganic chemistry

Abstract

fetched live from OpenAlex

To enhance the impact resistance of aluminum plates, polyaspartic ester polyurea (PEP) coatings were applied. Low-velocity drop-weight impact tests and numerical simulations were conducted to investigate the dynamic response. The results demonstrate the impact side coating had the best impact resistance.A 4 mm coating increases the structural stiffness by 37.21%, reduces the maximum residual deformation of the aluminum plate by 35.75%, and decreases Ed by 36.90%. These findings offer significant value in guiding the design of impact protection structures with PEP coatings, enhancing their energy absorption capacity, and improving the impact resistance of the structures.

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)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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