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Record W2965213877

Design of Landing Gear for Medium Altitude Long Endurance (Male) Unmanned Aerial Vehicle

2019· article· en· W2965213877 on OpenAlexfundno aff
Alex Avwunuketa, Gabriel Udu, Anthony Adeleke, Lawal Adamu, Oluwatofunmi Ajao, Eze Okoro

Bibliographic record

VenueJournals & Books Hosting (International Knowledge Sharing Platform) · 2019
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsnot available
FundersInnovation, Science and Economic Development Canada
KeywordsLanding gearAutomotive engineeringComputer scienceFixed wingTrack (disk drive)AxleShock (circulatory)Marine engineeringAeronauticsAerospace engineeringWingEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the procedure adopted for the design of UAV landing gear.Aircraft landing gear serves as a mechanism to support weight of the aircraft during landing, take-off , taxiing and also provide a shock absorbing function.The design of landing gear for the Medium Altitude Long endurance unmanned Aerial Vehicle is simple and it is base on safe life and fail safe concept and at the same time, make optimum selection and used of high strength materials for the design.This design considerations for this landing gear are significantly different, but past design procedures were used as guide to this design .Various landing gear configurations and types are in used today.The most common landing gear use for UAV is the fixed tricycle arrangement with one nose wheel (NLG) and two main wheels (MLG) at the rear.The retractable tricycle type was adopted for this design.The most attractive feature for this design is the improve stability during braking and ground maneuvering.The result obtain from this study indicate that the landing gear stability of the UAV could be improve with longer wheel axle, by increasing the wheel track.The approach used for the design, of the landing gear for this Medium Altitude Long Endurance UAV, follows the recommendations from previous designs of UAV landing gear and federal Aviation Regulation (FAR).

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 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 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: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.267
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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations1
Published2019
Admission routes1
Has abstractyes

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