Exploring the parametric design space to manage computational weld mechanics analyses using design of experiment
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.
Bibliographic record
Abstract
Development of a computational weld mechanics (CWM) framework that automates multiple set-ups and evaluations is required to practically explore a design space by given design of experiment (DOE) matrices. Saving an expert-user’s time to prepare several analyses and allocating CPUs to be utilised efficiently make this framework cost effective and time effective to manage designer-driven optimisation and control application of CWM. A validation analysis is conducted in this framework to identify the CWM control vector that minimises the difference between the computed and experimental data. Actual CWM problems with continuous and/or discontinuous parametric design spaces are solved in this framework to minimise weld distortion using derivative-free optimisation algorithms and DOE matrices that become attractive in this framework.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it