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Equilibrium Theory–Based Analysis of Nonlinear Waves in Separation Processes

2013· article· en· W2148538625 on OpenAlexaff
Marco Mazzotti, Arvind Rajendran

Bibliographic record

VenueAnnual Review of Chemical and Biomolecular Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDistillationDispersion (optics)Nonlinear systemSeparation (statistics)Separation processProcess (computing)Partial differential equationStatistical physicsDifferential equationPrecipitationComputer scienceApplied mathematicsMechanicsPhysicsMathematicsChemistryMeteorologyMathematical analysisChromatography

Abstract

fetched live from OpenAlex

Different areas of engineering, particularly separation process technology, deal with one-dimensional, nonstationary processes that under reasonable assumptions, namely negligible dispersion effects and transport resistances, are described by mathematical models consisting of systems of first-order partial differential equations. Their behavior is characterized by continuous or discontinuous composition (or thermal) fronts that propagate along the separation unit. The equilibrium theory (i.e., the approach discussed here to determine the solution to these model equations) predicts this with remarkable accuracy, despite the simplifications and assumptions. Interesting applications are in adsorption, chromatography and ion-exchange, distillation, gas injection, heat storage, sedimentation, precipitation, and dissolution waves. We show how mathematics can enlighten the engineering aspects, and we guide the researcher not only to reach a synthetic understanding of properties of fundamental and applicative interest but also to discover new, unexpected, and fascinating phenomena. The tools presented here are useful to teachers, researchers, and practitioners alike.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.004
GPT teacher head0.244
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations69
Published2013
Admission routes1
Has abstractyes

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