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Record W2412995785 · doi:10.1109/pcicon.2015.7479353

Review of upcoming motor and drive systems efficiency regulations in U.S. and Europe

2015· article· en· W2412995785 on OpenAlexaboutno aff
John Malinowski, W. G. Hoyt, Peter Zwanziger, Bill Finley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsnot available
Fundersnot available
KeywordsHorsepowerScope (computer science)Gas compressorEuropean unionEfficient energy useInduction motorEngineeringElectric motorAutomotive engineeringProduct (mathematics)Motor driveComputer scienceBusinessVoltageElectrical engineeringMechanical engineeringInternational trade

Abstract

fetched live from OpenAlex

The U.S. Department of Energy (DOE) issued new efficiency regulations in May of 2014 [1] for integral horsepower motors effective June 2016. This paper will provide an update on these new regulations for one (1) through 500 horsepower (HP) low voltage AC induction motors. The scope of coverage has been expanded to cover more configurations than in previous regulations. 56 frame enclosed motors are covered. Motor regulations for Canada and Mexico generally follow what is adopted in the U.S. Europe is updating succeeding regulations for LV motors (<;1000 Volts) and drive systems with an “extended product approach” from 0.12 through 1000 kW by 2018. Additionally, the DOE is studying pump, fan and compressor systems and how the efficiency can be regulated. We will provide an overview of the DOE proposals and the new European standard for efficient drive systems in case any users wish to follow and become involved with comments. This paper will review the motor and system efficiency regulations for the U.S. which are being issued by the DOE and also discuss extended product regulations under development by the European Union (EU).

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.203

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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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