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Record W2906245559 · doi:10.32920/ryerson.14657127.v1

Pressure sensing and control of an aircraft passenger seat

2021· preprint· en· W2906245559 on OpenAlexaff
Gabriel H. Campos

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCushionDeflection (physics)MorphingAirplaneAutomotive engineeringEngineeringSurface pressureDiscretizationWingStructural engineeringSimulationComputer scienceAerospace engineeringMechanicsMathematics

Abstract

fetched live from OpenAlex

The premise of this work is to address aircraft seat comfort. This thesis presents the development of an automatic morphing backrest used to reduce pressure experienced by the passenger from the seat. Uncomfortable, high surface pressure zones on the backrest can be alleviated by decentralizing the occupant’s weight. The improved pressure distribution is intended to decrease discomfort during flight while taking different comfort/discomfort models into consideration. Pressure distribution data from the embedded sensor mat is used to compute the seat’s cushion deflection and corresponding backrest contour caused by the passenger’s weight. The surfaces of interest - the passenger’s back and the seat, are modelled and discretized. The discretized surface contact pressure is integrated into the hyperelastic contact model to determine the loading profile. From this, the current pressure distribution and the cushion’s surface change are computed and used in the control system to create the corresponding actuation of the surface.

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 score0.814
Threshold uncertainty score0.868

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)0.0010.000

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 head0.285
Teacher spread0.273 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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