Water Impingement Erosion of Deep-Rolled Ti64
Bibliographic record
Abstract
In this work, the Liquid Impingement Erosion (LIE) performances of deep-rolling (DR) treated and non-treated Ti64 were investigated. Various erosion stages, from the incubation to the terminal erosion stages, could be observed. A full factorial design of experiments was used to study the effect of DR process parameters (Feed Rate, Spindle Velocity, Number of Passes, Pressure) on the residual stress distribution, microhardness and surface roughness of the treated Ti64 specimens. The DR-treated Ti64 specimens exhibited improved surface microhardness, surface roughness, and large magnitude of compressive residual stresses, which were attributed to the amount of cold work induced by the DR process. Although DR improved the mechanical properties of the Ti64, the results showed that the treatment has little or no effect on the LIE performance of Ti64 but different damage modes were observed in these two cases. Evolution of the erosion stages was described based on water-hammer pressure, stress waves, radial wall jetting, and hydraulic penetration modes. The initial erosion stages were mainly influenced by water-hammer pressure and stress waves, whereas the intermediate erosion stages were influenced by the combination of the four modes together. The final erosion stages contain the four modes, however the erosion was greatly driven by the radial jetting and hydraulic penetration modes, where more material was removed. The failure mechanism of the final stages of the LIE test of both DR-treated and non-treated Ti64 was characterized as fatigue fracture. However, a brittle fracture behavior was observed in the initial and intermediate erosion stages of the DR-treated Ti64, whereas a ductile fracture behavior was observed in the non-treated Ti64. This was concluded from the micrographs of the LIE damage through different erosion stages.
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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 | 0.000 |
| 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) | 0.001 | 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".