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Record W2084625539 · doi:10.1021/ie9009155

Energy Requirement of a Distillation/Membrane Parallel Hybrid: A Thermodynamic Approach

2010· article· en· W2084625539 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2010
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsNatural Resources Canada
FundersOffice of Energy Research and DevelopmentNatural Resources Canada
KeywordsSolverComputer scienceDistillationSplitterBinary numberFractionating columnNonlinear programmingCoupling (piping)Nonlinear systemMathematical optimizationChemistryMathematics

Abstract

fetched live from OpenAlex

This paper presents a new thermodynamic approach, based on the notion of power of separation, for the retrofit problem of finding the minimal energy requirement of an existing binary distillation column when coupling it in parallel with a membrane unit. A new geometric interpretation of this concept, which is supported by a rigorous mathematical proof, is introduced. From it results an efficient and accurate shortcut method to tackle the aforementioned problem. Numerical examples are considered for the energy intensive separation of olefins from paraffins, namely the retrofit of a C 3 -splitter and the retrofit of a C 2 -splitter through parallel hybridization with facilitated transport membranes. The results of the proposed shortcut method are compared to those obtained via the nonlinear programming optimization solvers GAMS-CONOPT and GAMS-CoinIpopt for a superstructure based problem formulation, which act as a reference. In both case studies, the shortcut method results in a significant reduction in problem size and in the number of solver iterations, while yielding only a small error on the minimal energy requirement of the column within the hybrid and on the hybrid architecture (i.e., the position of side-streams along the column). It could therefore be used to carry out a rapid screening of alternatives (e.g., different membrane technologies) in order to evaluate potential energy improvements. The proposed approach could also provide mathematical programming algorithms with a good initial guess of the solution.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.279
Teacher spread0.233 · 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