Effect in Thermal Conductivity due to Compaction of Powdered Stainless-steel 316L used in Additive Manufacturing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Metallic and plastic powders have been used in additive manufacturing for many years. Unfortunately, in processes such as powder bed fusion, the mechanical properties of the parts are different than using traditional machining methods. Some of the deficits of printed parts are directly attributed to the layer by layer process, where the density of the printed parts is overall lower because of the voids generated between the powder particles. Such voids can be generated by insufficient material and/or melting energy. In the previous years, several parametric studies in 3d printing processes have been performed. At this moment, experimental studies using powders are limited because its complexity. The presented research studied on the different thermal distribution of the powder particles under different arrangements in order to improve their thermal conductivity. Our experiments show that compacting the powder helped to reduce the gradients in temperature under certain temperatures more than 50%.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 it