A Study of Influence of Density on Al-Cu Composition During Compaction Process
Bibliographic record
Abstract
Powder metallurgy is a technology used for producing machine parts and oil-impregnated bearings from a metal powder. Highly accurate products can be efficiently mass-produced, and for that the powder metallurgy is indispensable particularly in automobile industry. Therefore powder characteristics are important because they often determine the choice of a particular processing route. In general, a mixed powder that is a metal powder is moulded by compression and the resultant green compact is then dewaxed. Subsequently, in powder metallurgy, the compact is sintered at a temperature of about 550 oC.In this sintering process, the mixed metal powder forms an alloy, thereby increasing the strength of the compact. It is done under a protective atmosphere with or without fusion of a low melting point constituent only so as to develop metallic or metal like bodies with satisfactory strength, density and without losing the essential shape [1]. A cutting operation is then performed on the resultant sintered compact. Metal powders are produced in various methods such as atomization, shotting, stamping and ball milling but pot mill is preferable. Spherical and dendritic metal powders are produced by atomization methods and flake shaped metal powders are produced by ball milling method. For the investigation purpose a quantity of copper powder is added to aluminium powder and mixed well by using pot mill to get homogeneous mixture. The aim of this paper is to establish the correlation among flow rate, compaction and sintering process and densities of compact of 3 % of Cu in Al.
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 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".