Residual stress determination in a shot-peened nickel-based single-crystal superalloy using X-ray diffraction
Bibliographic record
Abstract
A residual stress depth profile up to 1 mm is determined with the Ortner method in a single crystal of a nickel-based superalloy which has been subjected to shot-peening. An optimization procedure is assessed to minimize uncertainties connected to Bragg angle, mosaic spread and numerical stability. The theoretical background is reviewed to highlight the connections between Bragg angle positions and the stress tensor components in different coordinate systems and also to obtain a mathematically consistent formulation. Transformation matrices required to express the strain components with respect to the initial state are provided for the general case. It is shown that, when a stress gradient occurs beneath the sample surface plane, the value of the σ 33 component of the stress tensor determined from measurements is twice its true value. For a sample surface oriented along a 〈100〉 crystallographic direction, the data analysis shows that the compressive stresses which develop in the 150 µm-thick surface layer are compensated for by small tensile stresses developing at long scale rather than a specific layer of finite size featuring high tensile stresses. At least 17 Bragg angles are required to have stable solutions with standard deviations close to 30 MPa. Maximum compressive stresses of 1000 or 1400 MPa depending on the assumption used to describe the initial state occur at a 30 µm depth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".