Analytical and Numerical Modeling of the Thermal Performance of 3D System-in-Package (SiP)
Bibliographic record
Abstract
The study will investigate the heat dissipation capabilities of three-dimensional (3D) stacked System-in-Package (SiP) configurations using computational fluid dynamics (CFD) simulations for heat transfer analysis (HTA). The model introduced in this paper will be utilized to assess the thermal viability boundaries of 3D electronics and to pinpoint necessary enhancements to conventional packaging methods for accommodating functional 3D-SiPs effectively. By employing the finite element method (FEM) in combination with COMSOL Multiphysics® software, both modeling and simulation processes will be executed to verify heat dissipation pathways, aiming to reinforce the thermal performance of 3D-SiP assemblies. The investigation will primarily consider the impact of distinct geometrical attributes and thermophysical characteristics on the heat dissipation capabilities of SiPs. The investigation's results, which reduced the maximum temperature within the SiP by 84 %, could serve as an essential foundation for the development of thermal design guidelines specifically adapted to 3D-SiPs. In so doing, they would make a significant contribution to the skilful reinforcement of thermal management strategies.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".