Mitigation of Distortion in an Edge-Welded Bar by Clamping Parameters
Bibliographic record
Abstract
The objective is to demonstrate a capability developed to explore a design space to minimize distortion and evaluate the sensitivity of the distortion of an edge weld on a 152 × 1220 × 12.5 mm bar of Aluminum 5052-H32 wrt clamping. For each point in the design space, a full computational model that includes transient 3D thermal and stress analysis is solved using VrWeld software [1]. The bar has no displacement constraints other than rigid body constraints and the resulting camber from welding bends the bar. The minimum distortion in this discrete design space is assumed to be the optimal design to minimize the final distortion, i.e., objective function. The design space parameters chosen are clamping parameters, i.e., prescribed displacements, and the release time value in the design space. The bar is fixed at both ends and subjected to a range of prescribed displacements opposite to the direction of the camber. In the first set of tests the prescribed displacement is applied directly in the middle of the bar and in the second set of tests the displacement field is prescribed as a parabolic displacement along the full length of the bottom of the bar. In addition to the effect of the prescribed displacement on final distortion is shown to be highly correlated with the delay time at which the prescribed displacement is released after the weld is finished. The best pair of the prescribed value and the release time value in the design space. The distortion and residual stress fields in the mitigated bar with a nodal prescribed displacement in the middle of the bar and the mitigated bar with a parabolic prescribed displacement along the bottom surface of the bar are compared.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".