Residual stress measurement in engine block—an overview
Bibliographic record
Abstract
Abstract Significant residual stresses are often generated during the manufacturing of cast Al-Si alloy engine blocks due to differential cooling rates, the mismatch in the thermo-physical properties of adjacent materials in direct contact and volumetric changes caused by solid-state phase transformations during cooling. These may be modified during heat treatment and operation. These residual stresses may lead to distortion (affecting performance and economy) or premature failure of the engine block. For this reason, it is of fundamental importance to have reliable numerical and experimental methods for characterizing the residual stresses in the engine blocks at several steps during the manufacturing process. Sectioning and neutron diffraction techniques have been widely used to determine the residual stresses in the engine blocks. Numerical techniques have been developed to predict these residual stress but require experimental validation. The authors reviewed several numerical and experimental studies of residual stress evolution in engine blocks and showed how the residual stresses, microstructures, and mechanical properties are correlated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".