A Framework for Designer-Driven Exploration of Computational Weld Mechanics Design Space
Bibliographic record
Abstract
This paper demonstrates a framework for analyzing multiple analyses of welds and welded structures as a single run. For each point in the design space a 3D transient thermal-stress analyses is solved for the weld and/or a welded structure. This enables the designer to explore the design state space for the design points specified in a Design of Experiments (DOE) matrix. This makes it simpler and quicker for a human to set up tens or hundreds of analyses. Also the CPU time to solve each analysis must be sufficiently short. Examples of DOE matrices created for Computational Weld Mechanics (CWM) optimization analyses are presented; i) a discontinuous combinatorial optimization of the weld sequence to minimize distortion in a girth weld, ii) a continuous optimization to mitigate distortion of an edge welded bar using side heaters, pre-bending with prescribed deflections at isolated points and pre-bending with a smooth prescribed displacement function.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".