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Record W4317240841 · doi:10.5539/jas.v15n2p25

Design of Venturi-Type Fertilizer Injectors to Low-Pressure Irrigation Systems

2023· article· en· W4317240841 on OpenAlexvenueno aff
Arturo García-Saldaña, María D. R. Castañeda-Chávez, Arturo Pérez‐Vázquez, Juan Pablo Martínez-Dávila

Bibliographic record

VenueJournal of Agricultural Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsVenturi effectInjectorIrrigationFertigationFertilizerEnvironmental scienceComputational fluid dynamicsComputer scienceEngineeringMechanical engineeringInletChemistryAgronomy

Abstract

fetched live from OpenAlex

Twenty prototypes of Venturi-type fertilizer injectors for low-pressure agricultural irrigation systems were designed based on functional hydraulic pressure head and variation of their structural designs. These prototypes were modelled in three dimensions (3D) and evaluated using simulation through Computational Fluid Dynamics software (CFD). The main structural design characteristics come from a real necessity to complement an low pressure multigate irrigation system project named in Spanish “El Manzano” (The Apple tree) and bring it the fertigation possibility. The aim of this research was to select the best prototype, in order to identify the convergent and divergent angles, throat diameter and hydraulic pressure head to efficiently produce a Venturi-type injector for use in gated-irrigation pipe irrigation systems for use in a future in “El Manzano” project. As a result of the simulations, the physical characteristics of the injector were defined. The inlet and outlet diameters should be 152.4 mm, the throat diameter 76.2 mm and the suction diameter of 50.8 mm. The convergent and divergent angles showing most improved performances were 7.5 and 10°, respectively. This methodology can be used to construct Venturi-type fertilizer injectors for low-pressure gated-pipe agricultural irrigation systems, which, on one side, can reduce significantly the fertilizer application costs and, on the other side, the fertilizer management efficiency can be also improve considerably to save water resources. There is relatively very little experience in using this type of fertilizer injectors in low-pressure irrigation systems.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.155

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.034
GPT teacher head0.252
Teacher spread0.218 · 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 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

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