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Record W7034207677

Selective Laser Melting of a High-strength Steel and Joining of Aluminum and Copper

2021· dissertation· W7034207677 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsnot available
FundersShanghai Jiao Tong UniversityUniversity of TorontoNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsSelective laser meltingMicrostructureMetal powderCopperAluminiumDissolutionLaser
DOInot available

Abstract

fetched live from OpenAlex

Selective laser melting (SLM) is an additive manufacturing technique that employs a high energy density laser beam to fuse metallic powders for producing three-dimensional parts. The first part of this thesis focuses on employing recycled maraging steel powder in the SLM process. The steel samples produced with recycled powder exhibits nearly identical microstructure and mechanical properties to those produced using virgin powders. The second part of this thesis demonstrates that the SLM technique can be used to join dissimilar printed materials (pure Al and Cu, respectively) with 316L stainless steel. Pure Al and Cu powders join the steel through dissolution and melting. This thesis provides a preliminary study towards using recycled metal powders in the SLM processing and paves the way for joining dissimilar materials using the SLM.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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.

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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