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Record W2733193753 · doi:10.4050/f-0073-2017-12029

Bell V-280 Valor Hydraulic System Optimization for Accelerated Development

2017· article· en· W2733193753 on OpenAlexaff
Robert E. Reynolds

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsHydraulic machineryComputer scienceEnvironmental scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The V-280 Valor is Bell Helicopter's next-generation tiltrotor, represented as the Air Vehicle Concept Demonstrator (AVCD), designed for the Joint Multi-Role Technology Demonstrator (JMR-TD) program under a Technology Investment Agreement (TIA) with the US Army. The aircraft incorporates a Fly-By-Wire flight control system with a triplex redundant hydraulic system. The hydraulic system design was developed by conducting component and system level analysis in parallel with the broader design process. The parallel effort ensured that the hydraulic system would meet technical performance requirements and program goals for cost and schedule. Hydraulic system performance was evaluated in several areas including: Hydraulic Line Sizing, Thermal Performance and the Evaluation of Integrated Subsystems. The hydraulic system sizing iterations used a combination of steady state spreadsheet based analysis and dynamic system level analysis to achieve the necessary power delivery and thermal performance for the aircraft. The completed hydraulic system architecture maximizes performance while achieving minimum weight, cost and development time.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.028
GPT teacher head0.244
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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