Effects of Processing Parameters on Friction Stir Welded Lap Joints of AA7075-T6 and AA6022-T4
Bibliographic record
Abstract
Friction stir welding (FSW) is a solid-state welding process that has a number of advantages over traditional fusion welding techniques when attempting to join aluminum or dissimilar material workpieces. It is expected to play a large role in the automotive industry, where aluminum alloys are becoming more prevalent in mass-production vehicles. \n \nThe research in this thesis evaluates overlap FSW joints between thin sheets of AA7075-T6 and AA6022-T4 when the welding parameters of tool geometry and welding speed are varied. The resulting joints are characterized by optical microscopy, overlap shear tests, microhardness tests, and temperature measurements. The effect of a post-weld heat treatment is also examined. The main objective of the research are to determine a tool geometry that can produce good quality welds over a wide range of operating conditions, for use in an industrial setting. \n \nFriction stir welds of good quality are made successfully at speeds of up to 500mm/min, and it is found that weld microhardness and joint strength are greater at faster welding speeds; whereas temperatures in the weld area are lower at faster welding speeds. Five different tool geometries are tested, and the tool design that delivers the best performance is a one that uses a concave shoulder shape, and a pin with a tapered profile, threads, and 3 flats. A post-weld heat treatment at 180°C for 30 minutes is found to increase joint strength by approximately 10%. \n \nFuture studies involving transmission electron microscopy, corrosion testing, and fatigue testing are recommended in order to supplement the results presented in this thesis.
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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) | 0.001 | 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".