Evolution of Residual Stress Through The Processing Stages in Manufacturing of Bore-Chilled Sand-Cast Aluminum Engine Blocks With Pressed-In Iron Liners
Bibliographic record
Abstract
Abstract The cumulative global emissions produced by the automotive industry over the last decade has put a tremendous strain on the environment. Consequently, automotive engineers and manufacturers have been forced to improve the efficiencies of their automobiles which is frequently accomplished by increasing the operating pressure, and therefore temperature, of the combustion engine. Unfortunately, in addition to the rise in operational pressures and temperatures, large tensile residual stresses often accumulate in the cylinder bridges during the casting process of aluminum engine blocks due to the use of cast-in iron cylinder liners, leading to combined stress magnitudes above the strength of the currently used aluminum alloys. Thus, the present study aims to characterize the evolution of residual stress, with application of neutron diffraction, at several critical stages of the manufacturing process of sand-cast aluminum engine blocks that have eliminated the iron cylinder liners from the casting process and replaced them with cylinder bore chills that are pressed-out after the thermal sand reclamation process. The replacement of the iron liners shifted the stress mode from purely tension to purely compression until the bore chills were removed. Following removal of the bore chills, the maximum tensile stress at the top of the cylinder bridge was ~70% lower than the engine’s predecessor which was produced with iron liners. Moreover, in the production-ready state (i.e., T7 heat treated, machined and press-fit liners inserted), the stress mode maintains the partially compressive nature with low magnitudes of tension, thereby lowering the material’s susceptibility to crack growth and propagation.
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".