The Effects of Heat Treatment on the Microstructure and Tensile Properties of an HPDC Marine Transmission Gearcase
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".