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Record W2590949673 · doi:10.4271/2017-01-0447

Bench Test Method for Fuel Tank Vent Valve Noise Induced by EVAP System Pressure Pulsation

2017· article· en· W2590949673 on OpenAlexfundno aff
Zhe Li, Mike Dong, Dennis Harrigan, M. Gardner

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
FundersUniversity of WaterlooFord Motor Company
KeywordsTest benchMarine engineeringEnvironmental scienceFuel tankNoise (video)Aerospace engineeringAeronauticsPetroleum engineeringNuclear engineeringComputer scienceEngineeringMechanical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">In gasoline Powertrain systems, the evaporative emission control (EVAP) system canister purge valve (CPV) can be actuated by pulse-width modulated (PWM) signals. The CPV is an electronically actuated solenoid. The PWM controlled CPV, when actuated, creates pressure pulsations in the system. This pulsation is sent back to the rest of the EVAP system. Given the right conditions, the fill limit vent valve (FLVV) inside the fuel tank can be excited. The FLVV internal components can be excited and produce noise. This noise can be objectionable to the occupants. Additional components within the EVAP system may also be excited in a similar way. This paper presents a bench test method using parts from vehicle’s EVAP system and other key fuel system components. The test method achieves the following objectives: first, re-create the conditions that result in excitation; second, establish a controlled environment that provides insight into the noise phenomenon; and finally, set the ground work for further studies which may lead to further noise mitigation methods. The key system parameters controlled in this method are: frequency and duty cycle of the PWM signal, liquid level inside the fuel tank and tank grade/orientation. The output data includes: EVAP system purge flow rate, pressure signal inside the EVAP system (one near the CPV and one near the FLVV) and acceleration in Z (vertical) direction on the top tank surface near the FLVV mounting location.</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.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0020.002
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 head0.017
GPT teacher head0.286
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
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

Citations3
Published2017
Admission routes1
Has abstractyes

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