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Record W7028335219

Electron Beam Wire-fed Deposition of Titanium Alloys for Repair Applications

2023· dissertation· en· W7028335219 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsTitanium alloyDeposition (geology)TitaniumCathode rayAlloyElectron beam welding
DOInot available

Abstract

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Additive manufacturing (AM) has revolutionized manufacturing with its numerous advantages and applicability in various sectors.In aerospace, many components are fabricated from high strength materials, such as superalloys and titanium alloys.Hence, it is unsurprising that application of AM to fabricate and/or repair the wrought form of the workhorse titanium alloy -Ti-6Al4Vhas been of considerable research interest.However, during service, the aerospace components will be subjected to wear, corrosion, damage and, in critical loaded structures, high cycle fatigue stresses.Currently, the capability of suitable AM repair techniques to meet performance criteria and extend the service life of these components is unknown.Though full part replacement may be the only viable option in the case of extensive foreign object damage, considering the cost of high value materials and manufacturing sustainability challenges, repair through additive deposition on wrought or AM parts is inevitable.Therefore, reliable and cost efficient AM repair procedures are required for Ti-6Al-4V components in aerospace industry.First, a fully coupled 3D transient thermo-mechanical finite element model was developed to simulate and control the electron beam wire-fed (EB-WF) deposition process.Developed model has been validated using multiple single-layer and 10-layer EB-WF build Ti-6Al-4V coupons.Simple wall geometry wrought plates of 3 mm thickness were used as substrates.Thermocouple measurements were recorded to validate the simulated thermal cycles.The model was proven to be quite reliable in terms of predicted temperatures, residual stresses, and distortion profiles.The average error in the model was as low as 3.7% in terms of thermal predictions.The model proved to be extremely successful for predicting the cooling rates, grain morphology, and the microstructure.Mechanical validation measurements showed that the maximum deviations in the model were as low as 100 MPa in residual stresses and 0.05 mm in distortion.Tensile residual stresses were observed in the deposit and the heat-affected zone, while compressive stresses were observed in the core of the substrate.The highest tensile residual stress observed in the deposit was approximately 1.0 σys (yield strength).The highest distortion on the substrate was approximately 0.2 mm.Since the substrate material in repair applications is component with post-service residual stresses, the effect of initial residual stresses on the repair integrity are critical.Hence, the effect of the Résumé La fabrication additive (FA) a révolutionné la fabrication avec ses nombreux avantages et son applicabilité dans divers secteurs.Dans l'aérospatiale, de nombreux composants sont fabriqués à partir de matériaux à haute résistance, tels que les superalliages et les alliages de titane.Par conséquent, il n'est pas surprenant que l'application de la technologie FA pour fabriquer et/ou réparer la forme corroyée de l'alliage de titane à toute épreuve -Ti-6Al4V -ait suscité un intérêt considérable pour la recherche.Cependant, pendant le service, l'alliage AM sera soumis à l'usure, à la corrosion, aux dommages et, dans les structures chargées critiques, aux contraintes de fatigue cyclique élevée.Actuellement, la capacité des techniques de réparation AM appropriées à répondre aux critères de performance et à prolonger la durée de vie de ces composants est inconnue.Bien que le remplacement complet des pièces par la technologie AM puisse être la seule option viable en cas de dommages importants par des corps étrangers, compte tenu du coût des matériaux de grande valeur et des défis de durabilité de la fabrication, la réparation par dépôt additif sur des pièces en matériau forgé ou AM est inévitable.Par conséquent, des procédures de réparation fiables et rentables sont nécessaires pour le Ti-6Al-4V forgé et AM.Tout d'abord, un modèle d'éléments finis thermomécaniques transitoires 3D entièrement couplé a été développé pour simuler et contrôler le processus EB-WF.Le modèle développé a été validé à l'aide de plusieurs coupons de construction EB-WF monocouche et 10 couches Ti-6Al-4V.Des plaques forgées à géométrie de paroi simple de 3 mm d'épaisseur ont été utilisées comme substrats.Des mesures de thermocouple ont été enregistrées pour valider les cycles thermiques simulés.Le modèle s'est avéré assez fiable en termes de températures prévues, de contraintes résiduelles et de profils de distorsion.L'erreur moyenne du modèle était aussi faible que 3,7 % en termes de prévisions thermiques.Le modèle s'est avéré extrêmement efficace pour prédire les vitesses de refroidissement, la morphologie des grains et la microstructure.Les mesures de validation mécanique ont montré que les déviations maximales du modèle étaient aussi faibles que 100 MPa en contraintes résiduelles et 0,05 mm en distorsion.Des contraintes résiduelles de traction ont été observées dans le dépôt et la zone affectée thermiquement, tandis que des contraintes de compression ont été observées au cœur du substrat.La contrainte résiduelle de traction la plus élevée observée dans le dépôt était d'environ 1,0 σys (limite d'élasticité).La distorsion la plus élevée sur le substrat était d'environ 0,2 mm.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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