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Record W4385457286 · doi:10.1002/cjce.25055

Global optimization of the design of intensified shell and tube heat exchanger using tube inserts

2023· article· en· W4385457286 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 · 2023
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Multi-Objective Optimization Algorithms
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesChongqing UniversityNational Natural Science Foundation of China
KeywordsTrimmingHeat exchangerShell and tube heat exchangerTube (container)BaffleMechanical engineeringProcess (computing)Multi-objective optimizationSet (abstract data type)Shell (structure)Computer sciencePareto principleEngineeringMathematical optimizationMathematics

Abstract

fetched live from OpenAlex

Abstract This paper investigates global optimization of the detailed design of intensified shell and tube heat exchangers using two tube inserts: twisted tape and coiled wire. Three objectives, including heat exchanger area, total annualized cost, and environmental impact, are respectively minimized. All the design variables are considered as the ones that have discrete values based on their physical nature or manufacturing standards. We present, for the first time, a tailored global optimization approach for the design of intensified shell and tube heat exchanger: Set trimming procedure. We compare the computational performance of our set trimming procedure, exhaustive enumeration, and commercial solvers. The proposed three objectives have certain competitive relationships and multi‐objective optimization is performed to analyze the conflicts among them. Two literature examples are tested for illustration purposes. The solution results indicate that the intensified heat exchanger designed using tube inserts compares well to the regular heat exchanger using plain tube. Compared with commercial solvers, set trimming procedure runs fast and can converge to global optimum without initial value. The pareto‐optimal solutions of multi‐objective optimization provide holistic trade‐offs between different objectives, hence helping the process designer make proper decisions for the design of intensified shell and tube heat exchangers.

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: Methods · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.252

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 head0.023
GPT teacher head0.224
Teacher spread0.201 · 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