Investigation of the effect of traverse speed in friction surfacing of Al–16Si alloy by smoothed-particle hydrodynamics (SPH) simulation and experimental study
Bibliographic record
Abstract
The impact of traverse speed on the microstructure, mechanical properties, and wear resistance of Al–16Si alloy friction-surfaced on AA1050 alloy was evaluated using smoothed-particle hydrodynamics (SPH) simulation and experimental techniques. Results revealed a 54% and 20% decrease in the height and width of the coating, respectively, as traverse speed increased from 75 to 115 mm/min. Moreover, a corresponding increase in the unbonded zone at the interface was observed. Simulation results showed the maximum shear stress at the coating/substrate interface for samples coated at traverse speeds of 75, 95, and 115 mm/min to be 83, 95, and 112 MPa, respectively. As traverse speed escalated from 75 to 115 mm/min, the predicted torque and vertical force required for friction surfacing increased by 92% and 22%, respectively. The surface roughness declined while interface roughness increased by 49% and 86%, respectively, upon raising the traverse speed from 75 to 115 mm/min. An increase in the traverse speed from 75 to 95 mm/min resulted in a 11% grain size reduction and 13%, 12%, and 8% increases in hardness, strength, and wear resistance, respectively, when compared to the AA1050 substrate.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".