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Record W2313232828 · doi:10.2514/6.2007-4075

Trajectory Prediction Tool Comparisons for Spinning and Non-Spinning Projectiles

2007· article· en· W2313232828 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venue25th AIAA Applied Aerodynamics Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicGuidance and Control Systems
Canadian institutionsDefence Research and Development Canada
FundersDefence Research and Development Canada
KeywordsSpinningProjectileTrajectoryComputer scienceMaterials sciencePhysicsComposite material

Abstract

fetched live from OpenAlex

The field of artillery must meet ever more stringent operational needs in the delivery of precise effects. Closely connected to meet these needs for the Canadian Forces, DRDC Valcartier studies solutions of guidance and control. DRDC Valcartier undertook to compare different suites of tools to predict the trajectory of projectiles in order to study the various concepts with a sufficient degree of confidence. Two reference projectiles were studied, namely, the Basic Finner and a 105 mm spin stabilized projectile. The MMCL (Munition Model Component Library) was benchmarked against PRODAS trajectory module using the aerodynamic coefficients predicted by PRODAS for the 105 mm configuration. Then, the MMCL package was validated using a spin-stabilized projectile. Then, trajectories of the reference model were simulated and compared for PRODAS and the MMCL. Finally, the trajectories obtained were compared with available experimental data. The results indicate that Missile Datcom generated aerodynamic coefficients are sufficiently accurate to predict the overall trajectories of the projectiles.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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