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Record W4409202241 · doi:10.1016/j.addma.2025.104765

Residual stress prediction in machining of parts fabricated by directed energy deposition

2025· article· en· W4409202241 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdditive manufacturing · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMaterials scienceResidual stressMachiningDeposition (geology)Composite materialEnergy (signal processing)Stress (linguistics)Mechanical engineeringEngineering physicsMetallurgyEngineering

Abstract

fetched live from OpenAlex

The residual stress exhibited in post-machined metallic components fabricated by directed energy deposition (DED) determines their final mechanical performance and reliability in mission-critical applications. This study develops a numerical model to predict the final surface residual stress after the orthogonal cutting of DED-produced IN718, which integrates two critical factors: DED-induced initial residual stress states and microstructure properties. Using the developed modeling procedure, the penetration depth of post-machining into the initial residual stress distribution can be effectively quantified, which aligns with residual stress measurements through X-ray diffraction. The developed model is further employed to quantify the cumulative effects of initial residual stress states and grain size on cutting forces and final surface residual stress profiles. The results suggest that, under the given orthogonal cutting conditions of DED parts, variations in the initial residual stress states of the chip formation region have negligible effects on cutting forces. However, magnitudes of surface compressive residual stress in the longitudinal direction reduce by 21.8 %-52.3 % as the initial residual stress states shift from compressive-dominant to tensile-dominant, and decrease by 23.8 %-54.0 % as the built-in grain size ( d g _ x ) increases from 10 μm to 100 μm. With a comprehensive understanding of post-machining DED processes using this numerical modeling procedure, post-treatment techniques can now be tailored to achieve surface residual stress profiles on DED-generated or other additively manufactured metallic components to meet various industrial requirements. • Forces and surface residual stresses are predicted in post-machining of DED-fabricated part. • The model accounts for the cumulative effects of initial residual stress states and grain size. • The initial residual stresses have different effects on forces and final surface residual stresses. • Increasing grain size leads to reduced magnitude of compressive residual stress.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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