Simulation of GPHE diagonal based on full material history
Bibliographic record
Abstract
The objectives for this thesis is to further develop a finite element analysis methodology where the material history is evaluated in every step. The processing of the plate from coil to fully formed plate mounted in a heat exchanger should be taken into consideration. Material phenomena such as necking and springback are important to capture. The first attempt was to do the simulation in ANSYS. This was not possible due to bugs in the software. The analysis was therefore carried out in LS-PrePost with LS-Dyna as a solver. A forming simulation, a springback analysis and a gasket simulation were performed where the springback simulation was an addition to the method, lacking from the current method performed at Alfa Laval. The forming and gasket simulation was performed with similar setup and settings as the current method with some changes to fit the purpose of this dissertation. To capture material phenomena, two material models were evaluated, Barlat 91 and YLD2000, and possible improvements to the finite element analysis was tested. The forming and the springback of the plate was analysed with the material models with 5, 7 and 11 integration points. Even though ANSYS is a more user-friendly software, the LS-Dyna method was the favourable workflow. LS-Dyna is better suited to work with metal forming and the mapping of stresses and strains between the simulations, which were important to capture the material history, were successful. The mapping of the stresses and strains for the plates were successful and in the final gasket simulation, residual stresses and plastic strains were present, meaning that the material history is taken into consideration at the final stage. The simulations also showed different results depending on the material model and number of integration points but further analysis with physical tests are necessary to determine which model is the most similar to the actual plate.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
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".