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Record W4399921134 · doi:10.18280/mmep.110610

Mathematical Modelling and Performance Review of Desalination Technology Based Renewable Energy

2024· article· en· W4399921134 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDesalinationRenewable energyProcess engineeringBiochemical engineeringEnvironmental scienceComputer scienceEngineeringChemistryElectrical engineering

Abstract

fetched live from OpenAlex

This research aims to provide a comprehensive overview and review of the utilization of renewable energy in desalination technology.The study classifies the various methods employed in desalination systems, which encompass both thermal and membrane techniques.The analysis of desalination methods incorporates the concepts of energy, exergy, and economic considerations.A crucial aspect of this study is developing a mathematical model encompassing thermal and membrane desalination methods.The advancement and progress of desalination technology are elucidated and integrated using renewable energy sources.The findings of this review indicate that the thermal desalination method consumes more energy than the membrane method, particularly during the water evaporation process.The wave-based reverse osmosis (RO) technique exhibits a lower production cost among the different methods.This is followed by the solar-powered multi-effect distillation (MED) system, the solarpowered multi-stage flash (MSF) system, and the wind-powered mechanical vapor compression (MVC) system.The mathematical models developed in this study could predict both membrane and thermal desalination systems' performance, thereby assisting readers in modeling and planning environmentally friendly and sustainable desalination technology based on renewable energy sources.

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.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.461
Threshold uncertainty score0.840

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 integrity0.0000.000
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 head0.030
GPT teacher head0.243
Teacher spread0.213 · 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