The role of heating and cooling in viscous sintering of pairs of spheres and pairs of cylinders
Bibliographic record
Abstract
Purpose This study aims to develop mathematical models for the determination of the effects of heating or cooling on neck growth in Selective Laser Sintering (SLS) and Fused Filament Fabrication (FFF). Two particle shapes are studied: spherical and cylindrical. Design/methodology/approach The time required for the coalescence (sintering) process is determined by balancing the work of surface tension forces and viscous dissipation. Heating and cooling effects are studied by incorporating temperature dependence of viscosity in an exponential form. Heating by a laser, convective and/or radiative heat transfer is assumed. It is also assumed that there are no temperature gradients within the coalescing molten polymers (lumped parameter heat transfer analysis). Findings The models predict faster sintering with heating and slower with cooling, as expected because of the effect of temperature on viscosity. For the isothermal case of pairs of cylinders, the present model predicts significantly longer time for completion of sintering than a previously developed and frequently cited model by Hopper. Originality/value An isothermal sintering model for two spheres was reworked for two long cylinders, and for the first time it has been compared to other models available in the literature. The mathematical models are capable of predicting neck growth under non-isothermal conditions for both spheres and cylinders. They are useful in assessment of bonding in selective laser sintering and fused deposition fabrication.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".