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Record W4280557848 · doi:10.1016/j.watres.2022.118593

Performance evaluation of an industrial ceramic nanofiltration unit for wastewater treatment in oil production

2022· article· en· W4280557848 on OpenAlexfundaboutno aff
Sandra Motta Cabrera, Louis Winnubst, Hans Richter, Ingolf Voigt, Jeffrey R. McCutcheon, Arian Nijmeijer

Bibliographic record

VenueWater Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
FundersOffice of Energy EfficiencyOffice of Energy Efficiency and Renewable EnergyAlberta InnovatesAlberta Innovates - Technology FuturesU.S. Department of Energy
KeywordsNanofiltrationWastewaterMembraneIndustrial wastewater treatmentCeramic membraneBar (unit)ChemistryPulp and paper industryOil fieldCeramicSewage treatmentIonMaterials scienceChromatographyChemical engineeringEnvironmental scienceEnvironmental engineeringOrganic chemistryPetroleum engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

An industrial ceramic nanofiltration membrane (pore size 0.9 nm) was tested in a Canadian oil field for more than 12,500 h to treat wastewater directly from daily operations, without any type of pre-treatment. This wastewater contained a high content of total suspended solids (13 to 510 mg/kg), and total organic carbon (31 to 134 mg/kg). The membrane unit was operated at different transmembrane pressure (TMP) set points (4–16 bar) and recovery set points (40–80%). The data show that ion and compound rejection depend strongly on a combination of both TMP and recovery, with the largest rejection occurring at low recovery values and high TMP values. Two mechanisms were responsible for rejection: sieving, which mostly impacted compound rejection, and electrostatic phenomena that impacted ion rejection. It is shown that ion rejection depends linearly on charge density of the ion. Ion rejection was measured as high as 85% and compounds (such as TSS) were rejected as high as 100%. The specific flux varied between 1–10 L/(m2.h.bar). Results from this field testing indicate the possibility of using these types of ceramic membranes for oil field wastewater treatment.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0010.000

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 head0.217
GPT teacher head0.381
Teacher spread0.164 · 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.

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

Citations36
Published2022
Admission routes2
Has abstractyes

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