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Record W4221042560 · doi:10.18280/ijdne.170104

Pineapple Drying Analysis in Packing Plants Through Computational Fluid Dynamics

2022· article· en· W4221042560 on OpenAlexvenueno aff
Alexis Cordovés García, Alexis Cordovés Rodríguez, Karla Tatiana Núñez Buñay, Arlys M. Lastre Aleaga, Leandro L. Lorente-Leyva

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsComputational fluid dynamicsDiffuser (optics)Pressure dropMechanicsInletEngineeringMechanical engineeringEnvironmental scienceMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The aim of this research is to determine the average fluid velocity values and the average total pressure at the outlet of the ventilation system conduit for the drying, by air impulsion, of pineapples in packing plants, in order to ensure the required humidity level of the crown for its proper packaging. The CAD model of the air conduction was obtained in Solidworks and Computational Fluid Dynamics (CFD) techniques were applied to simulate the performance of the ventilation system. Air was indicated as the type of fluid, and an internal analysis of the pipe with roughness Rz = 3.2 μm. As a computational domain, the pipeline was established, from the connection to the fan to the outlet diffuser. As boundary conditions were established; a W and Z Manufacturing regenerative fan at the inlet of the flow pipe 618,439 m3/h, and at the outlet of the pipe the value of atmospheric pressure. As a result of the simulation, an average velocity value at the diffuser outlet of 127.294 m/s was obtained, higher than the required 96.06 m/s. An average total pressure value of 111718.73 Pa was obtained in the conduit suitable for the proposed purposes. For the conveyor belt, it is recommended to use, in each row of pineapples, the simulated fan with a simple diffuser with a rectangular section of 1 x 20 cm, or a regenerative fan with a flow of 1248.77 m3/h and a diffuser with two-outlet bifurcation.

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 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: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of Design & Nature and EcodynamicsSame topicFood Drying and ModelingFrench-language works237,207