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Record W2936107965 · doi:10.1139/tcsme-2018-0247

Analysis of material motion characteristics of vertical nonlinear synchronous vibration dryer

2019· article· en· W2936107965 on OpenAlexvenueno aff
Xiaohao Li, Rui Gao, Tao Shen

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsVibrationExcitationNonlinear systemDisplacement (psychology)CorrectnessMechanical engineeringSynchronization (alternating current)Motion (physics)Computer scienceEngineeringAcousticsPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

The nonlinear characteristics of a vertical dryer prototype under the synchronous excitation of vibration motors were analyzed. The vibration synchronization conditions of the two excitation motors of the vertical dryer were pursued. The analysis of motion characteristics of the material granules on the vertical dryer was conducted. The relationship between the structure parameters of the vertical dryer powered by two excitation motors and the motion characteristics of the material granules were discussed. Experimental results and discussion were used to verify the correctness of the theoretical analysis. This research demonstrated that the displacement of the material granules in the moving direction increased as the installment angle of the two excitation motors increased. This can improve the production efficiency; however, too large an installment angle destabilized the response of the dryer, no longer satisfying the design and use requirements. The research methods and conclusions presented in this paper can provide theoretical support and experimental basis for future development of a vibration dryer powered by two excitation motors.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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