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Record W1512514214 · doi:10.4271/2005-01-0654

Optimization of the Exhaust Mass Flow Rate and Coolant Temperature for Exhaust Gas Recirculation (EGR) Cooling Devices Used in Diesel Engines

2005· article· en· W1512514214 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 technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsExhaust gas recirculationExhaust gasCoolantEnvironmental scienceDiesel fuelDiesel exhaustMass flowFlow (mathematics)Mass flow rateNuclear engineeringPetroleum engineeringAutomotive engineeringWaste managementMechanicsMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">An experimental investigation was conducted to characterize the operational transients of a small-scale 6-tube exhaust gas recirculation (EGR) cooling device, designed to simulate operating conditions of commercial devices, for a wide range of exhaust mass flow rates and different coolant temperatures. The transient pressure drop across the device and the thermal performance were measured for exhaust mass flow rates varying over a full range typically used in commercial devices. The coolant temperatures tested ranged from 25 °C to 55 °C. The temperature distribution on the outer shell surface of the small-scale EGR cooling device was also measured periodically using a thermal imaging camera to characterize the secondary side flow in the experiments. The results show that both the exhaust mass flow rate and the coolant temperature had a significant influence on the transient performance of the 6-tube EGR cooling device.</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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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