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Record W2139712475 · doi:10.24908/pceea.v0i0.4055

HEAT EXCHANGER NETWORK OPTIMIZATION AND CONTROLLABILITY USING DESIGN RELIABILITY THEORY

2011· article· en· W2139712475 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of Calgary
FundersLehigh University
KeywordsControllabilityFlexibility (engineering)Reliability (semiconductor)Reliability engineeringProbabilistic designConstraint (computer-aided design)Heat exchangerComputer scienceControl theory (sociology)Mathematical optimizationControl (management)EngineeringEngineering design processMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

For a given heat exchanger network (HEN) it is often necessary to determine its behaviour to disturbances in supply temperature and/or inlet flow rate variations, that is its ability/flexibility to meet the design requirements at new operating conditions. An analysis of the HEN flexibility is very useful to assess other design options and in the design of a robust control structure. The use of design reliability theory coupled with fuzzy design uncertainties can be used to determine the possibility of violating the HEN constraints. This measures the potential of the design failure rather than the frequency of failure, the latter being measured by probability theory. The HEN constraints considered in this work are the target temperatures, hot/cold utility flow rate and heat transfer area/overall coefficient (UA). If the design under consideration results in a significant value of the failure possibility for any of these constraints, then this HEN design will require either a modification of the design or the establishment of a specific requirement in the control system. The case study treated in this paper shows that design reliability theory is a useful tool for determining HEN constraint violations that will require special attention from a control point of view, that is controllability analysis. Thus this approach has proven to be a useful tool for determining design changes and for developing a workable control scheme for HEN designs.

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: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.660

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 head0.012
GPT teacher head0.185
Teacher spread0.173 · 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