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Record W2097206981 · doi:10.4271/2012-01-1749

Experimental Analysis of Engine Exhaust Waste Energy Recovery Using Power Turbine Technology for Light Duty Application

2012· article· en· W2097206981 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSAE International Journal of Engines · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsVolvo (Canada)
Fundersnot available
KeywordsTurbineAutomotive engineeringEnvironmental sciencePower (physics)Energy recoveryHeavy dutyGas turbinesWaste managementEngineeringEnergy (signal processing)Process engineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">An experimental analysis was executed on a NA (Natural Aspirated) 4-stroke gasoline engine to investigate the potential of exhaust waste energy recovery using power turbine technology for light duty application. Restrictions with decreasing diameter were mounted in the exhaust to simulate different vane positions of a VGT (Variable Geometry Turbine) and in-cylinder pressure measurements were performed to evaluate the effect of increased exhaust back pressure on intake- and exhaust pumping losses and on engine performance. Test points in the engine map were chosen on the basis of high residence time for the vehicle during the NEDC (New European Driving Cycle). The theoretically retrievable power was calculated in case a turbine is mounted instead of a restriction and the net balance was obtained between pumping power losses and recovered energy.</div></div>

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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