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Characterization of the dynamic behaviour of ALGOTUF armour steel during impact and in torsion

2015· article· en· W6922012227 on OpenAlexaboutno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2015
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionFusible alloyLiquationHyporeflexiaTSG101Diafiltration

Abstract

fetched live from OpenAlex

\nAlgotuf is a new steel which is proposed as a candidate for armour material. To assess this application, a study of the impact properties of this steel was conducted at the University of Manitoba using two types of Hopkinson Bar systems, namely a torsional bar equipment and a direct impact system capable of producing high strain rates and large strains. Stress strain curves for the steels were obtained in pure shear and in compression. Temperatures of 25 ∘C, 200 ∘C and 500 ∘C were used in the testing. Following the testing, a microstructural examination of the specimens tested was carried out to investigate the effect of microstructure on the mechanism of failure of this material. It was found that, above a value of impact momentum corresponding to a high strain rate, adiabatic shear bands are formed. The microscopic examination showed that the initiation of these shear bands corresponded at locations where martensitic laths were present and around regions of maximum shear stresses. Generally, the shear bands act as precursors to the formation of microcracks that may lead to failure. On the other hand, the high strength and formability of the steel makes it suitable for use as an armour material.\n

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 score0.300
Threshold uncertainty score0.487

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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