MétaCan
Menu
Back to cohort
Record W4406291881 · doi:10.1016/j.jajp.2025.100283

Neutron diffraction analysis of residual stress distribution in the lubricant-free TR-AFSD AA7075 repair coupled with SPH simulations

2025· article· en· W4406291881 on OpenAlexaff
Ning Zhu, Trevor Hickok, Kirk Fraser, Dunji Yu, Yan Chen, Ke An, Luke N. Brewer, Paul Allison, J.B. Jordon

Bibliographic record

VenueJournal of Advanced Joining Processes · 2025
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsNational Research Council Canada
FundersOak Ridge National LaboratoryStrategic Environmental Research and Development ProgramOffice of ScienceBaylor University
KeywordsResidual stressNeutron diffractionLubricantMaterials scienceResidualDiffractionComposite materialPhysicsOpticsComputer science

Abstract

fetched live from OpenAlex

This work examines the residual stress in high-strength aluminum alloy repaired by lubricant-free additive friction stir deposition (AFSD) using the same aluminum alloy feedstock. Specifically, a milled groove in an AA7075-T651 substrate was repaired using the twin rod additive friction stir deposition (TR-AFSD) without using any graphite lubricant on the feedstock materials, which is required for conventional square feedstock AFSD. Residual stress distribution in the repaired substrate at different depths was quantified via neutron diffraction, where the distribution of longitudinal residual stress in the TR-AFSD repair was found comparable to materials subjected to other friction-based processes, with an M-shaped or bell-shaped distribution. The tensile longitudinal residual stress, with a peak of 171.3MPa, spanned the center region around 36 mm, while compressive longitudinal residual stresses, ranging between -112.9 MPa and -12.3 MPa, were balanced outside the center at both the advancing side and retreating sides. The transverse and normal residual stresses were consistent across the repair, with smaller magnitudes between -52 MPa and 68.3 MPa. The non-destructive and high penetrate depth nature of the neutron diffraction method enabled the calculation of von Mises stress by interpreting the three measured orthogonal residual stresses as the principal stresses. By normalizing the calculated von Mises stress to the microhardness, this quantified ratio indicates the influence of the embedded residual stresses relative to the material's strength. The higher normalized ratio observed at a deeper depth closer to the bottom of the repair, suggests that the magnitude of residual stresses is closer to the material's strength, indicating a higher potential for residual stress-induced failure at this location. We also calibrated the state-of-the-art smooth particle hydrodynamic (SPH) TR-AFSD process model to predict the von Mises stress distribution in the TR-AFSD AA7075 repair. The experimentally measured residual stress, coupled with the SPH simulation, could further help the research community to minimize the tensile region and alleviate substrate distortion in materials subjected to friction-based processes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.257
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Advanced Joining ProcessesSame topicWelding Techniques and Residual StressesFrench-language works237,207