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Record W3090501323

Spiral wound modules for high viscosity solutions at high temperature: Carrageenan concentration with ultrafiltration

2003· article· en· W3090501323 on OpenAlexaboutno aff
Frank Lipnizki, Carl Erik Nielsen

Bibliographic record

VenueLund University Publications (Lund University) · 2003
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSpiral (railway)ViscosityUltrafiltration (renal)Materials scienceMembraneComposite materialMechanical engineeringChemistryChromatographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Spiral wound modules are the most common modules in the industry due to their low investment and replacement costs plus high packing density. The use of spiral wound modules is often restricted to feed streams with a low temperature (< 75°C) and a low viscosity. The focus of this paper is on a new generation of spiral wound modules, which has been introduced by Alfa Laval Membrane Technology for the treatment of feed streams at high temperatures and viscosity. Key features of these modules are: (1) the use of temperature resistant materials allowing constant operation up to 90°C and (2) integration of an 80 mil feed spacer to process high viscosity products. The use of these spiral wound modules is successfully demonstrated in a case study on the concentration of carrageenan, an additive mainly used in the food industry. In this application, the spiral wound modules operate constantly close to 90°C and concentrate the carrageenan in the retentate up to 3-5% while removing impurities with the permeate. Overall, this paper demonstrates the successful application of a new generation of spiral wound modules, which gives the possibility to treat high-viscous solutions at high temperature.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.152
Teacher spread0.147 · 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 designTheoretical or conceptual
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

Citations0
Published2003
Admission routes1
Has abstractyes

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