THE INFLUENCE OF SEQUENTIAL LOADING IN RESIDUAL STRESS GENERATION
Bibliographic record
Abstract
Mechanical structures, under the influence of external loads, can develop cross section partial yielding, which in turn can generate residual stresses. Also, when the structure's operation stresses are combined with residual stresses, it can lead to "unexpected" premature failures. For this reason, it is important to understand how these residual stresses are generated, and what can be done to minimize their values. To access the main variables that could influence the residual stress cross section distribution, a numerical approach was implemented. The Finite Element Method was utilized to simulate several combinations of loading in two cycles: with positive or negative curvatures, with two loading levels and allowing or not the spring back. The combinations were applied on a metallic wire structure. For each case, the graphs Stress versus Strain, and the residual Stress distribution versus the wire cross section thickness, were provided. In function of a simple variable recombination, the preliminary results show a very different residual stress distribution. The variable combinations, which can diminish the residual stress cross section distribution, were also presented and discussed.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".