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Record W7015416158

Switched reluctance motor analysis and design for a lunar roving vehicle

2013· dissertation· en· W7015416158 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsnot available
FundersCanadian Space Agency
KeywordsSwitched reluctance motorPropulsionProcess (computing)Rotor (electric)Electrically powered spacecraft propulsionTraction motorElectric motorSimple (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

In the 21st century, many countries launched robotic space exploration programs, including the Discovery Program in United States, the Chandrayaan Program in India and the Chang'e Program in China. The lack of an atmosphere in outer space makes electric motors the only viable choice for the propulsion systems of a space exploration robot. This thesis proposes the switched reluctance motor (SRM) as a potential candidate for a traction drive. The SRM has a simple and robust rotor structure, an inherent degree of fault tolerance, high efficiency over a wide speed range, and a low cost. This thesis also presents the complete design process of an SRM, starting with its user requirement. Numerical experiments are carried out to analyze both the motoring and the regenerative braking modes of the SRM, and to verify the proposed design. Additionally, evolutionary strategy (ES) single- and multi-objective optimizations are performed to refine the geometric parameters.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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
Published2013
Admission routes1
Has abstractyes

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