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Record W4225793072 · doi:10.22215/etd/2022-14834

Investigation of the Feasibility of Deploying Electro-rheological Dampers in a Drop Tower to Replicate the Impact Profiles of High Speed Craft

2022· dissertation· en· W4225793072 on OpenAlexaff
Muhammad Zahid

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsCarleton University
FundersNational University of Science and TechnologyNational University of Sciences and Technology
KeywordsReplicateDamperDrop (telecommunication)Structural engineeringDrop testShock absorberEngineeringShock (circulatory)Drop impactSuspension (topology)TowerMechanical engineeringAutomotive engineering

Abstract

fetched live from OpenAlex

High-speed craft (HSC) occupants are subjected to a harsh environment due to repeated shock loading and vibration which results in serious potential for injury to the occupants. Various suspension seats have been developed to attenuate such shocks. In order to study the shock mitigating effectiveness of suspension seats and the injury mechanisms associated with shock loading, it is important that these seats be studied and characterized in the laboratory by reproducing the impacts that HSC are subjected to at sea. The motivation of this work is to investigate the feasibility of deploying electro-rheological (ER) dampers in a drop tower in order to replicate the impact profiles that HSC and their seats experience at sea.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.278
Teacher spread0.254 · 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 designBench or experimental
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

Citations0
Published2022
Admission routes1
Has abstractyes

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