Investigating the Effects of Build Height on Mechanical Behavior of Large‐Scale Laser Wire Directed Energy Deposited Nickel Titanium Alloy
Bibliographic record
Abstract
This article presents the first comprehensive investigation coupling phase transformation, mechanical properties, and tribological behavior across build height in large scale laser wire directed energy deposition (LW‐DED) fabricated NiTi alloy. A 140 × 135 × 10 mm wall is deposited to conduct location specific characterization and tribo‐mechanical testing that can reveal the phase and property heterogeneity along the build height. X‐ray diffraction quantified B2 austenite decreasing from 23 wt% at the upper region to 0 wt% at the lower region while R‐phase peaked at 45 wt% in the middle region of printed NiTi wall. Differential scanning calorimetry showed martensite start temperatures ranging from 30.20 to 34.21 °C along the build height. Tensile testing demonstrated ultimate strength variations from 412 MPa in the lower region to 578 MPa in the upper region, representing ≈40% strength increase. Reciprocating wear tests on sectioned NiTi samples against AISI 52100 counter ball revealed build height dependent wear resistance, with the upper region exhibiting higher wear volume despite similar friction coefficients. The middle region presented a balance between strength and tensile ductility with the highest R‐phase content, suggesting the crucial effects of thermal gyration during LW‐DED on tribo‐mechanical behavior in large scale NiTi components.
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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".