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A Computational Model to Estimate the Performance of 8 inches RO Membranes in Pressure Vessel

2012· article· en· W2102159576 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

VenueJournal of Membrane and Separation Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReverse osmosisDesalinationSeawaterMembraneChemistryVolumetric flow ratePressure vesselPermeationRange (aeronautics)ChromatographyAnalytical Chemistry (journal)EngineeringMaterials scienceMechanical engineeringThermodynamicsComposite materialPhysicsBiochemistryBiology

Abstract

fetched live from OpenAlex

A computational model for estimating RO system performance was developed in this study. Wide range of seawater concentrations 32000 mg/L, 35000 mg/L, 38000 mg/L, and 43000 mg/L were used as feed solution. Two different types of Filmtec RO membranes were investigated; SW30HRLE-440i and SW30HR-380. A pressure vessel of four RO elements was simulated in this paper. The recovery rate, ions rejection rate, flow arte, and permeate concentration was simulated for each element in the pressure vessel. The results from this study were compared with Reverse Osmosis System Analysis (ROSA) software assuming that the simulation results from ROSA are reasonably accurate. It was found that the results from this study were in a good agreement with ROSA. The model was also validated against a commercial RO system for seawater desalination, feed concentration 43000 mg/L. An agreement more than 85% was achieved between the model and the experimental data.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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