MétaCan
Menu
Back to cohort
Record W4386027618 · doi:10.1590/1679-78257764

Experimental and Numerical Study on Ballistic Impact Response of Vehicle Tires

2023· article· en· W4386027618 on OpenAlex
Yangziyi Ji, Xiangdong Li, Lanwei Zhou, Xingfeng Liu

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

VenueLatin American Journal of Solids and Structures · 2023
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsMD Precision (Canada)
Fundersnot available
KeywordsBallistic limitPenetration (warfare)Materials scienceWarheadStructural engineeringRadial tireProjectileComposite materialNatural rubberEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Tires are a critical component of military wheeled vehicles and are exposed to the threat of fragment caused by explosion of warhead on the battlefield. To study the ballistic impact response of military vehicle tires under fragment, experiments and numerical simulations of spherical fragments impacting tires were carried out. The damage mode of the tires was analyzed. The effects of obliquity, tire thickness, and fragment mass on the dynamic response of tires, as well as the ballistic limit velocity, were analyzed. The results indicate that: (1) The main failure modes of the tire comprise local erosion near the center of the perforation, elastic deformation surrounding the perforation, and tensile fracture of the steel cords. (2) The process of fragment penetration into a tire can be divided into four stages: the entry stage, stable penetration stage, cord layer penetration stage, and fragment exit stage. (3) The cord structure demonstrates its ability to undergo plastic deformation to a certain extent and its restraining effect on the rubber.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.395

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 head0.021
GPT teacher head0.338
Teacher spread0.317 · 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