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Record W2402791433

Deformation Optimization of Plate Heat Exchangers

2016· article· en· W2402791433 on OpenAlexaboutno aff
Mattias Norén

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsDeformation (meteorology)Heat exchangerPlate heat exchangerMaterials scienceMechanical engineeringEngineeringComposite material
DOInot available

Abstract

fetched live from OpenAlex

The thesis was conducted in collaboration with Alfa Laval which is a global company operating in three key product areas: heat transfer, separation and fluid handling.One major product segment within the heat transfer area is the gasket mounted plate heat exchanger, which this thesis has focused on.In a plate heat exchanger (PHE) the different mass flows are separated from each other with corrugated plates, made out of sheet metal.The key part of the plate is the heat transferring area which often consists of a wavelike pattern.When every other and other plate is rotated and mounted together contact points occur at the wave tops.When the equipment is pressurized deformations may occur in the contact points.The aim of the thesis was to understand how to optimize the wave pattern geometry to minimize the deformations.The thesis was divided into three major parts: two parts with different simulation models and a third which consisted of laboratory experiments.The first simulation model was made with rough simplifications in order to obtain an automatized setup to scan a design space.The second simulation model was based on Alfa Laval's existing simulation procedure.It included more aspects to obtain realistic results, but was more time consuming since every simulation had to be prepared manually.This led to fewer simulated design points and each design point had to be chosen more carefully.The object of the experimental part was to validate the correctness of the simulation models.The results showed that the geometry could be optimized in certain ways.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.976
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

Explore more

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