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Record W2562844970 · doi:10.1002/cjce.22770

Thermodynamically‐based response time as controllability indicator in heat exchanger networks

2016· article· en· W2562844970 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsControllabilityHeat exchangerNetwork controllabilityConsistency (knowledge bases)Process (computing)Dissipative systemComputer scienceProcess controlMeasure (data warehouse)Work (physics)Control theory (sociology)Control (management)Point (geometry)Control engineeringMathematicsEngineeringMechanical engineeringThermodynamicsData miningApplied mathematics

Abstract

fetched live from OpenAlex

Abstract Recently, research and development has focused on how to integrate process design and process control, considering that the most outstanding process design does not always result in the best dynamic performance, involving plant controllability. A steady‐state controllability and resiliency analysis provides useful information for the assessment of heat exchanger networks (HEN) and requires less work than the dynamic analysis. In the interests of obtaining the best balance between process integration and controllability, a thermodynamic analysis from the dissipative point of view can be a starting point. This paper presents a simultaneous approach for finding controllability and economic goals in early stages of process design. An index based on response time is obtained, which is a controllability measure of the system. It is applied to a HEN and the results obtained are compared with known controllability and resiliency measures tools on steady state, showing consistency. The proposed methodology serves as a starting point for controllability evaluation, making it possible to relate the stages of process control and design.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.282

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 integrity0.0000.000
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 head0.003
GPT teacher head0.173
Teacher spread0.170 · 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