MétaCan
Menu
Back to cohort
Record W4389504481 · doi:10.5004/dwt.2023.29729

Evaluating the production and exergetic performance of point-of-use reverse osmosis devices for brackish water desalination

2023· article· en· W4389504481 on OpenAlexfundno aff
Sahil Shah, Amos G. Winter

Bibliographic record

VenueDesalination and Water Treatment · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAbdul Latif Jameel Water and Food Systems Lab, Massachusetts Institute of Technology
KeywordsReverse osmosisBrackish waterDesalinationGeothermal desalinationEnvironmental scienceReverse osmosis plantProcess engineeringProduction (economics)Environmental engineeringEngineeringChemistryMembraneEconomicsGeologyOceanographySalinity

Abstract

fetched live from OpenAlex

An exergy analysis was conducted to investigate the high specific energy consumption (SEC) of point-of-use reverse osmosis (POU RO) devices. The RO module from one such device was experimentally characterized for desalination of 650, 1,000 and 1,800 mg/L sodium chloride solutions at 70-630 kPa feed pressures. The minimum SEC was 1.54 0.04 kWh/m 3 , while the maximum second law efficiency and recovery ratio were 1.80% 0.05% and 24.6% 0.8%, respectively. Losses at the motor, pump, RO element, and flow restrictor respectively accounted for 36%, 25%, 8%, and 29% of the SEC at the intermediate concentration. By highlighting these inefficiencies, we also identified potential avenues for improving the system performance. Recovering brine pressure can decrease SEC significantly. Elevated feed pressures could also decrease SEC and raise recovery ratio but permeate flux would exceed recommended design limits (< 30 L/m 2 h), thus increasing fouling risk. The same could be achieved by increasing membrane area provided that the resulting increase in cost and size of the system are acceptable. This work will help guide new developments to decrease the energy consumption of POU RO desalination.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.188

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.063
GPT teacher head0.314
Teacher spread0.252 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueDesalination and Water TreatmentSame topicMembrane Separation TechnologiesFrench-language works237,207