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Record W1993529996 · doi:10.1109/icinfa.2014.6932808

Active and passive measures to reduce the noise pollution of combustion engines

2014· article· en· W1993529996 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsYork University
Fundersnot available
KeywordsAutomotive engineeringNoise (video)Noise controlActive noise controlAttenuationActuatorCombustionComputer scienceNoise pollutionEnvironmental scienceAcousticsEngineeringNoise reductionElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

In recent years comfort has become an important factor when evaluating the performance of modern automobiles. One important aspect that has negative ramifications on the perception of the quality is the generated noise, which mainly contributes to the disturbing noise level of urban regions. Therefore, an important goal in current research is the attenuation of the noise level of car engines. The paper at hand presents two main approaches, an active and a passive one, to reduce the noise radiation of combustion engines, which is the main noise source of automobiles. In the active approach thin piezoelectric wafers are attached to the structure as sensors and actuators. With an appropriate controller the structural vibrations are reduced, which result in an attenuation of the sound pressure in the environment. The passive approach utilizes a full engine encapsulation, which is also designed to reduce the sound radiation of the engine. By encapsulating the motor the oil temperature can be increased such resulting in decreased fuel consumptions.

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: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.146

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 head0.009
GPT teacher head0.209
Teacher spread0.201 · 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

Quick stats

Citations9
Published2014
Admission routes1
Has abstractyes

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