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Record W7028842733

High-pressure frame design for gasketed plate heat exchangers: Enhanced engineering design for manufacturability, distribution, and maintenance

2024· other· en· W7028842733 on OpenAlexaboutno aff

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersLunds Universitet
KeywordsComponent (thermodynamics)Frame (networking)Modular designEngineering design processWork (physics)Frame workProcess (computing)New product development
DOInot available

Abstract

fetched live from OpenAlex

Alfa Laval is the market leader within gasketed plate heat exchanger (GPHE) technology. To remain the leader of the GPHE sector, Alfa Laval regularly performs design studies to investigate new solutions and find inspiration for possible functions. Alfa Laval always work to improve their products, regarding many aspects, such as manufacturability, distribution, and maintenance as well as sustainability. The objective of this thesis was to perform a design study of large high-pressure GPHE frame designs to enhance manufacturability, distribution, and maintenance. The output of the project was intended to give new design perspectives for Alfa Laval’s development projects. The project process included interviewing stakeholders in Alfa Laval’s organization, problem decomposition, concept generation, concept selection and calculation analysis. The method applied in the project was mainly based on the methods outlined by Ulrich and Eppinger in the book Product Design and Development. The project resulted in four main concepts. The concepts incorporated wire ropes, beams, modular designs, and external supports. The most promising concept incorporated wire ropes substituting large tightening bolts to simplify maintenance processes. The project concluded that the current frame, in many ways, already is optimized, especially regarding a cost-efficient manufacturing process. While the proposed new concepts offer advantages in some areas, they also introduce new challenges. Therefore, future work should first analyze whether any of the concepts contribute to an overall improvement of the product and then refine the most promising concepts on a component level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2024
Admission routes1
Has abstractyes

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