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Record W2767492024 · doi:10.1115/smasis2017-3755

Crashworthiness Study of Helicopter Skid Landing Gear System Equipped With a Magnetorheological Energy Absorber

2017· article· en· W2767492024 on OpenAlexaffabout
Muftah Saleh, Ramin Sedaghati, Rama Bhat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsDamperMagnetorheological fluidEngineeringMagnetorheological damperLanding gearAutomotive engineeringShock absorberStructural engineeringGimbalStroke (engine)Aerospace engineering

Abstract

fetched live from OpenAlex

The present study concerns with the performance of a skid landing gear (SLG) system of a rotorcraft impacting the ground at a vertical sink rate of 5.0 m/s. The impact attitude is per chapter 527 of the Airworthiness Manual (AWM) of Transport Canada Civil Aviation and FAR Part 27 of the U.S. Federal Aviation Regulation. A single degree of freedom helicopter model is investigated under two rotor lift factors 0.67 and 1.0. Three Configurations are evaluated: a) A conventional SLG; b) SLG equipped with a passive viscous damper and c) SLG incorporated with a magnetorheological energy absorber. The non-dimensional solutions of the helicopter model show that the passive damper system could reduce the maximum acceleration experienced by the helicopter occupants by 21% and 19.8% in comparison to the undamped system for the above rotor lift factors, respectively. However, the passive damper fails to constrain the non-dimensional energy absorption stroke of the damper within the given 18 cm maximum stroke and a bottoming out of the damper piston was noticed. Therefore, the alternative and successful choice was to employ a magnetorheological energy absorber (MREA). To improve the MREA controllability and to resettle the payload with no oscillations, i.e. in one cycle, two different Bingham numbers for compression stroke and rebound stroke were defined in the non-dimensional solution. Several simulations were conducted for different values of Bingham numbers. Among these numerical simulation results, the solution that implemented the optimum Bingham numbers was found to be the only one feasible solution. In this case the MREA with optimum Bingham number for compression could utilize the full energy absorption stroke to attain soft landing. In the rebound stroke, the generated optimal on-state damping force successfully controls the bounce of the payload until the payload settles down to its original equilibrium position with no oscillations.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.457

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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2017
Admission routes2
Has abstractyes

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