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Record W4385431872 · doi:10.18280/rcma.330305

Investigation of Vibration Characteristics of Stir Cast Aluminum Reinforced SiC Composite Beam

2023· article· fr· W4385431872 on OpenAlexvenueno aff
Ramanjaneya Reddy Alavala, Omprakash Beedalannagari, Abhishek Dasore, Manoj Panchal

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2023
Typearticle
Languagefr
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsnot available
FundersAll India Council for Technical Education
KeywordsVibrationMaterials scienceBeam (structure)Composite numberDamperDynamic Vibration AbsorberStructural engineeringComposite materialStiffnessBoundary value problemAcousticsEngineeringPhysics

Abstract

fetched live from OpenAlex

In various applications such as plant mines or mechanical systems, machines in operation generate significant vibrations which are transmitted from the foundation to the surrounding environment and precision instruments.In order to minimize these vibrations, they must be either isolated, absorbed, or damped.The current study investigates the effects of an oil damper, passive vibration isolator, and absorbers (single and double) on the vibration frequency of a composite beam made of Al6061 (with 90% weight fraction) and SiC (with 10% weight fraction) produced through the stir casting process.Experimental analysis was conducted on the fabricated composite beam to investigate the frequencies of the fundamental vibration modes under hinged-hinged, fixed-free, and fixed-hinged boundary conditions.Results indicate that the absorber, damper, and isolator have a significant effect in reducing the amplitude of vibrations, resulting in lower frequencies compared to the main frequency.Furthermore, as the number of holes in the beam increases, the frequencies decrease due to a decrease in stiffness.The frequencies are higher for fixed-free end conditions without holes compared to other conditions.The oil damper was found to be more effective in reducing vibrations compared to absorbers and isolators.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.317
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.058
GPT teacher head0.247
Teacher spread0.188 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicAluminum Alloys Composites PropertiesFrench-language works237,207