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Research on the recoil reduction efficiency of a recoilless launch gun with high projectile velocity

2024· article· en· W4405848251 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Launch and Propulsion Technology
Canadian institutionsnot available
Fundersnot available
KeywordsProjectileRecoilPhysicsReduction (mathematics)Nuclear physicsAtomic physicsMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract Recoilless launch can improve the adaptability of unmanned platforms to weapons by eliminating recoil, but it has the disadvantage of reducing the initial velocity of the projectile. The initial velocity of the recoilless gun can be improved by increasing the charge mass, so research into the recoilless efficiency of recoilless firing with increasing charge mass is of great importance for future applications of recoilless weapons. Based on the combustible cartridge and induction ignition, the one-dimensional homogeneous flow internal ballistic of a recoilless gun with high initial velocity is established. The effect of the Laval nozzle diameter on the efficiency of the recoilless gun is then investigated. The results show that, compared to conventional guns, the recoil can be reduced to 1N-s without reducing the initial velocity of the projectile. A ballistic test on a slide-rail mount is carried out to verify the results of the analysis. The results should make an important contribution to the development of a recoilless rifle.

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)0.001
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 score0.775
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.268
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