MétaCan
Menu
Back to cohort
Record W2965557802 · doi:10.1177/1350650119866046

Experimental study on the high-speed impact of a sand particle on Ti–6Al–4V

2019· article· en· W2965557802 on OpenAlexaboutno aff
Cheng Yan, Wei Chen, Zhenhua Zhao

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsnot available
Fundersnot available
KeywordsImpact craterSupersonic speedDragParticle (ecology)AirflowMaterials scienceParticle velocityMechanicsNozzleImpactGeotechnical engineeringStructural engineeringGeologyAerospace engineeringEngineeringPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

When sand is ingested by a helicopter engine, it collides with the compressor blades at a high relative speed, causing severe erosion damage. A test was conducted on the high-speed impact of sand particles on the target of Ti–6Al–4 V alloy to enhance the understanding of high-speed impact damage mechanism. The test apparatus was used to create supersonic airflow, which was produced by normal temperature air flowing through a special Laval nozzle. The supersonic airflow produced the drag force to increase the velocity of sand particles up to about 400 m/s. The experiment demonstrated that fractured sand particle caused less damage than nonfractured particle under similar impact conditions. The nonfractured particle directly cut the target more easily than the fractured at a relatively low impact velocity. When the impact speed exceeded 300 m/s, the crater depth increased exponentially with the increase of velocity. Impact angle determined the mode of material failure.

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 score0.002
Threshold uncertainty score0.007

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part J Journal of Engineering TribologySame topicErosion and Abrasive MachiningFrench-language works237,207