Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".