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Record W2008512379 · doi:10.1021/ie050088v

A Method for Steady-State Simulation of Multistage Three-Phase Separation Columns

2005· article· en· W2008512379 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColumn (typography)Steady state (chemistry)Phase (matter)Nonlinear systemFractionating columnStability (learning theory)DistillationSeparation (statistics)Computer scienceControl theory (sociology)ChromatographyChemistryPhysics

Abstract

fetched live from OpenAlex

The development of a new algorithm for steady-state modeling of multistage three-phase separation columns is presented. In the developed algorithm, prior knowledge of phase pattern in the column is not required. The phase pattern determination and equilibrium calculations are carried out simultaneously. The stability of a phase is determined by coupling a stability equation with the model equations of the column. The resulting nonlinear model equations of the system are solved using an “inside-out” method. The ability and flexibility of the algorithm for the simulation of three-phase separation columns are shown by solving a variety of three-phase distillation column examples. The algorithm is also applicable to two-phase separation columns.

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)0.001
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: none
Teacher disagreement score0.908
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.115
GPT teacher head0.434
Teacher spread0.319 · 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