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Record W4200118466 · doi:10.18280/mmep.080609

Modeling and Investigation of Multistage Flash-Mixing Brine in Aqaba City, Jordan

2021· article· en· W4200118466 on OpenAlexvenueno aff
Khalideh Al bkoor Alrawashdeh, Kamel K. Al‐Zboon, Zakaria Al Qodah

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsDesalinationBrineEnvironmental scienceVolumetric flow rateBoiler feedwaterMixing (physics)Environmental engineeringPetroleum engineeringWaste managementEngineeringChemistryMechanicsBoiler (water heating)

Abstract

fetched live from OpenAlex

Desalination processes are considered an essential solution to meet the water scarcity in Jordan. Among the desalination techniques, the multistage flash (MSF) desalination technique has a significant contribution to water budget in many regions around the world. In this paper, MSF with a mixing brine desalination plant was proposed in Aqaba city of Jordan. The plant will consume 5 MW power to produce about 74 Kg/s of freshwater. Different designs are studied to determine the most appropriate design. Also, the effect of feed sea water flow rate, heating steam flow rate and number of stages on the plant performance were evaluated. The optimum layout consists of 24 stages with 3.6 m width, 2.6 m length, and with a recycled brine flow rate of about 651 Kg/s. The expected plant performance is 9.6.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.215
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2021
Admission routes1
Has abstractyes

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