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Record W2094500533 · doi:10.1002/cjce.22119

Towards the modelling of a heat‐exchanger reactor by a dynamic approach

2014· article· en· W2094500533 on OpenAlexvenueno aff
Juan Carlos Marin Gallego, Nelly Olivier‐Maget, Gilles Hétreux, Nadine Gabas, M. Cabassud

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsExothermic reactionHeat exchangerInitializationDynamic simulationTransient (computer programming)Computer scienceSteady state (chemistry)Partial differential equationBounded functionControl theory (sociology)Applied mathematicsSimulationMathematicsEngineeringMechanical engineeringThermodynamicsChemistryPhysicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract The aim of this paper is to present the development of a simulation tool in order to assess the inherently safe characteristics of a heat‐exchanger reactor (HEX) operating reaction systems. The modelling of steady and transient states of a HEX reactor is performed following a hybrid dynamic approach. The global dynamic behaviour of this reactor can be represented by several continuous models, which are bounded by state or time events. Each continuous model is defined as a system of partial differential‐algebraic equations. The numerical scheme is based on the method of lines. Special attention is paid to the model initialization and a simulation strategy of the start‐up phase is presented. The validation of the model is made by numerous examples, such as the simulation of an exothermic reaction.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.166
Teacher spread0.157 · 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 designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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