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Record W4255128606 · doi:10.3384/lic.diva-99382

Design Automation of Complex Hydromechanical Transmissions

2013· book· en· W4255128606 on OpenAlexaff
Karl Pettersson

Bibliographic record

VenueLinköping University Electronic Press eBooks · 2013
Typebook
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsEngineering Link (Canada)
Fundersnot available
KeywordsAutomationEfficient energy useEngineeringAutomatic transmissionTransmission (telecommunications)Process (computing)Energy consumptionPower transmissionEnergy modelingTorqueComputer scienceControl engineeringAutomotive engineeringPower (physics)Mechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

This thesis proposes an automated methodology for the design of complex multiple-mode hydromechanical transmissions. High fuel prices and strict emission regulations are today drivers of the development of new fuel-efficient drive transmissions for construction machinery. Hydromechanical transmissions have high energy efficiency and a wide torque/speed conversion range. They are today strong candidates to replace the fuel-thirsty torque converters conventionally used in heavy construction machines. The trend towards more complex transmission architectures increases the need for more sophisticated product development methods. Complex multiple-mode transmissions are difficult to design and prototype and can be realised in a great number of different architectures. This increases the need for reliable concept evaluation in early design stages. The design of the transmission is also strongly coupled to its energy consumption and for a fair comparison between transmission concepts optimal designs are necessary.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.647
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.185
Teacher spread0.160 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations8
Published2013
Admission routes1
Has abstractyes

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