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Software Development Based on Object-Oriented Design for Parachute Design and Performance Analysis

2011· article· en· W1997565048 on OpenAlex
Li Yu, Han Cheng, Zhu Yin

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.

Bibliographic record

VenueApplied Mechanics and Materials · 2011
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsHewlett-Packard (Canada)
Fundersnot available
KeywordsSoftwareObject (grammar)Computer scienceSoftware designEngineeringSystems engineeringSoftware developmentOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a powerful, user-friendly parachute design and performance analysis software (PDPA) is introduced. This software provides researchers a convenient and efficient parachute design tool. The functions such as parachute structure design, material selection, performance analysis, calculation verification, view display, document output, can be achieved. PDPA can be used for all types parachute design (flat circular parachute, ring-sail parachute, etc.) except parafoil, and combine the first stage parachute with main parachute to make up of a parachutes system. As a result, six types of performance plots, two structure figures, and three types of documents can be obtained. These remarkable features make the software more practical.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.738

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 head0.021
GPT teacher head0.178
Teacher spread0.157 · 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