Hot Tearing in Cast Aluminum Alloys: Measures and Effects of Process Variables
Bibliographic record
Abstract
Hot tearing is a common and severe defect encountered in alloy castings and perhaps the pivotal issue defining an alloy's castability. Once it occurs, the casting has to be repaired or scraped, resulting in significant loss. Over the years many theories and models have been proposed and accordingly many tests have been developed. Unfortunately many of the tests that have been proposed are qualitative in nature; meanwhile, many of the prediction models are not satisfactory as they lack quantitative information, data and knowledge base. The need exists for a reliable and robust quantitative test to evaluate/characterize hot tearing in cast alloys. This work focused on developing an advanced test method and using it to study hot tearing in cast aluminum alloys. The objectives were to: 1) develop a reliable experimental methodology/setup to quantitatively measure and characterize hot tearing; and 2) quantify the mechanistic contributions of the process variables and investigate their effects on hot tearing tendency. The team at MPI in USA and CANMET-MTL in Canada has collaborated and developed such a testing setup. It consists mainly of a constrained rod mold and the load/displacement and temperature measuring system, which gives quantitative, simultaneous measurements of the real-time contraction force/displacement and temperature during solidification of casting. The data provide information about hot tearing formation and solidification characteristics, from which their quantitative relations are derived. Quantitative information such as tensile coherency, incipient crack refilling, crack initiation and propagation can be obtained. The method proves to be repeatable and reliable and has been used for studying the effects of various parameters (mold temperature, pouring temperature and grain refinement) on hot tearing of different cast aluminum alloys. In scientific sense this method can be used to study and reveal the nature of the hot tearing, for industry practice it provides a tool for production control. Moreover, the quantitative data and fundamental knowledge gained in this thesis can be used for validating and improving the existing hot tearing models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".