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Record W3157578296 · doi:10.24908/iqurcp.7737

Inquiry into Extending the Life of Valve Rocker Arms in High Performance and Large Capacity Engine

2017· article· en· W3157578296 on OpenAlexvenueno aff
Kadra Branker

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
Fundersnot available
KeywordsCylinderMechanical engineeringPneumatic cylinderResilience (materials science)Presentation (obstetrics)Computer scienceEngineeringMaterials scienceComposite materialMedicine

Abstract

fetched live from OpenAlex

Valve rocker arms in an engine aid in the timing of the valves. The valves control the air intake and gas exhaust from the cylinder chamber in the engine which affect the efficiency of the engine. Although the rockers are small and fairly inexpensive compared to other parts in the engine the disruption in the timing of the valves can have catastrophic consequences once they fail. Rockers experience considerable cyclic forces due to the repeated tapping on the valves, increasing with the revolutions of the engine. As a result rocker arms exhibit fatigue failure which is amplified by residual stresses that are induced during manufacture. The manufacturing methods employed in making the rockers influence material properties along with the chosen materials which require specific methods of preparation. Proposed solutions include better alloying using powder metallurgy and the use of other materials in the design, such as ceramics, to improve their resilience and strength. The types of testing methods to determine the best solution and other possible areas of consideration, when solving the problem, will also be acknowledged. This presentation will illustrate how inquiry based learning can be used to solve the problem. It will address why valve rocker arms fail while assessing past and present research geared towards finding a solution, with emphasis on the manufacturing methods and material properties

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)0.003
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.090
GPT teacher head0.342
Teacher spread0.252 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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