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Record W3136112989 · doi:10.3390/met11030517

The Effects of Heat Treatment on the Microstructure and Tensile Properties of an HPDC Marine Transmission Gearcase

2021· article· en· W3136112989 on OpenAlexaff
Joshua Stroh, D. Sediako, Ted Hanes, Kevin R. Anderson, Alex Monroe

Bibliographic record

VenueMetals · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsAlloyUltimate tensile strengthMicrostructureMaterials scienceVolume fractionIntermetallicMetallurgyResidual stressComposite material

Abstract

fetched live from OpenAlex

The drive for continuously improving the performance and increasing the efficiencies of marine transportation has resulted in the development of a new alloy, Mercalloy A362™. This alloy was designed to lighten Mercury Marine’s lower transmission gearcase while also improving the alloy’s recyclability. The new prototype gearcase was subjected to Mercury Marine’s standard service conditions, which resulted in the premature failure of the prototype. A previous study revealed that a large accumulation of unwanted residual stress (~120 MPa) was present in the gearcase following the high pressure die casting process. Fortunately, the T5 heat treatment reduced the magnitude of stress by approximately 50%. However, the effects that the T5 heat treatment had on the microstructure and mechanical properties of the alloy were not discussed. Thus, this research article characterizes the effects that the T5 heat treatment has on the volume fraction and morphology of the intermetallics, as well as the tensile performance of the alloy. It was found that the T5 heat treatment led to only minor increases in the volume fraction of Fe-bearing intermetallics, leading to similar tensile properties in both the as-cast and T5 condition. These results suggest that the T5 heat treatment can alleviate residual stress without significantly altering the mechanical properties of the alloy. The results from the previous stress analysis and the current study were used to optimize the manufacturing process which led to the successful introduction of the gearcase into the competitive marine industry.

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 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 score0.036
Threshold uncertainty score0.219

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 head0.010
GPT teacher head0.190
Teacher spread0.181 · 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 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

Citations6
Published2021
Admission routes1
Has abstractyes

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