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Record W4391300999 · doi:10.2514/6.2024-1538

System Integration Study for a Hybrid-Electric Commuter Aircraft Concept with a Solar Auxiliary Power System

2024· article· en· W4391300999 on OpenAlexaff
Gala Licheva, Vijesh Mohan, Andrew K. Jeyaraj, Parush Bamrah, Mohammad Mir, Susan Liscouët-Hanke

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsAuxiliary power unitAerospace engineeringPower (physics)Electric power systemComputer scienceHybrid powerAutomotive engineeringElectrical engineeringEngineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

Commuter and regional aircraft are promising candidates as testbeds for technologies that aim to reduce emissions. Among these technologies, the electrification of the propulsion system and the subsystem architectures is a potential research avenue. However, to find promising candidate architectures, particularly in a retrofitting context, multiple design disciplines must be considered in combination with systems integration. This paper investigates the retrofitting of the Dornier 228 regional commuter aircraft with a combination of hybrid-electric propulsion, more-electric subsystems, and an auxiliary solar power system, using a conceptual multidisciplinary design analysis and optimization (MDAO) framework. It includes an auxiliary solar power system sizing and performance analysis tool, which allows the analysis of power generated by aircraft-mounted solar panels and the associated impact on aircraft weight and mission fuel burn. The sensitivity of such a system concept to solar panel technology, aircraft operation, and available solar radiation is explored in conjunction with system electrification and hybridization of the propulsion system. Systems integration and safety considerations are also studied. The authors first present a step-by-step evaluation of the effect of propulsion hybridization, system electrification, and the solar power system individually on the aircraft performance and emissions profile. The impact of the combination of these three technologies is assessed on the aircraft mission fuel burn and CO2 emissions. Finally, this paper provides insights into the viability of such a combined system for commuter aircraft missions, investigates how each system contributes to the overall fuel burn reduction at the aircraft level and explores the management of battery weight by using the electric component of the hybrid-electric power train in specific combinations of flight phases.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.609

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 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
Published2024
Admission routes1
Has abstractyes

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