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Preliminary Design and Performance Analysis of A Solar-Powered Jumping-Gliding Martian Aircraft

2022· article· en· W4317242578 on OpenAlex
Bin Lou, Anhuan Xie, Shiqiang Zhu, Yaru Liu, Jason Gu

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

Venue2022 IEEE International Conference on Robotics and Biomimetics (ROBIO) · 2022
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFuselageAerospace engineeringMartianMars Exploration ProgramAerodynamicsJumpingEnvironmental scienceMarine engineeringEngineeringAstrobiologyGeologyPhysics

Abstract

fetched live from OpenAlex

A solar-powered jumping-gliding Martian aircraft is proposed as a new tool for Mars exploration, designed especially to perform long-term wide-range detection. A completely new way of continues detection performed by aircraft is created. A preliminary design of the jumping-gliding Martian aircraft is carried out while its flight performance is analyzed afterwards. The conceptual design of a large-aspect ratio foldable wing with a thin fuselage and a jumping device is put forward. The solar energy model, aerodynamic model and weight mode are all built. The energy balance models are established for the periods of detecting mission that the aircraft lands on the ground for harvesting solar energy and flies in the sky. The gliding performance of this aircraft is particularly discussed here.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.810

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 head0.029
GPT teacher head0.231
Teacher spread0.203 · 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