MétaCan
Menu
Back to cohort
Record W2084033100 · doi:10.1002/apj.5500140317

Heat Exchanger Network Dynamic Analysis

2006· article· en· W2084033100 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

VenueDevelopments in Chemical Engineering and Mineral Processing · 2006
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of CalgaryJacobs (Canada)
Fundersnot available
KeywordsHeat exchangerFlexibility (engineering)Process integrationProcess (computing)HeuristicCapital costDynamic simulationProcess controlProcess engineeringComputer scienceEngineeringMechanical engineeringSimulation

Abstract

fetched live from OpenAlex

Abstract The continued high cost of energy has mandated that the Chemical Process Industries reduce operational and capital costs through process heat integration. However, the heat integration of process streams can lead to process structures that are difficult to operate and control. This paper addresses the control of heat exchanger networks and it shows the importance of dynamic simulations in the synthesis of workable control structures. Steady‐state simulations were used to delineate the trade‐off between flexibility and capital costs of networks. Dynamic simulations were used to assess the placement of the by‐pass on the process‐to‐process heat exchangers. Steady‐state and dynamic simulations showed that the use of stream splitting should be avoided as a control scheme. The analysis of several simple case studies allowed the proposal of heuristic rules to identify the best control strategy for a heat exchanger network.

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 score0.190
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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