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Record W2999224220 · doi:10.1139/cjce-2019-0548

Prediction of perforation velocity of hard missile impacts on reinforced concrete wall panels

2020· article· en· W2999224220 on OpenAlexaffvenue
Andaç Lüleç, Vahid Sadeghian, Frank J. Vecchio

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsMissilePerforationStructural engineeringRange (aeronautics)Empirical modellingCompression (physics)Computer scienceEngineeringSimulationMechanical engineeringMaterials scienceAerospace engineering

Abstract

fetched live from OpenAlex

This study reviews and compares the most commonly used models for computing the local effects of hard missile impacts. The accuracies of the models in predicting perforation velocity are evaluated using a dataset of 95 impact tests collected from the literature. It is found that the majority of the models are unable to accurately predict perforation velocity or have a limited application range because of their empirical nature. To address these limitations, a semi-analytical model based on the Modified Compression Field Theory and the principle of work and energy is proposed. Unlike most existing models, the proposed model is capable of considering the influence of in-plane and shear reinforcement. The performance of the proposed model is assessed against experimental results obtained from the compiled dataset as well as other existing models.

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 score0.012
Threshold uncertainty score0.548

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)0.0010.000

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 head0.032
GPT teacher head0.215
Teacher spread0.184 · 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
Published2020
Admission routes2
Has abstractyes

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