A High Power Density Thermal Management Approach Using Multi-PCB Distributed Cooling (MPDC) Structure
Bibliographic record
Abstract
This paper presents a new thermomechanical PCB design that uses a multi-PCB cooling (MPDC) structure to achieve higher power density while maintaining thermal performance. The new MPDC structure focusses on three design principles: multiple vertically stacked PCB's for more efficient use of space, component sorting based on losses for improved cooling, and integrated liquid cooling for maximum thermal dissipation. Liquid cooling method is utilized to implement the thermal management problem with very high power density. Finite element analysis (FEA) based thermal analysis was conducted on the 1.3kW converter with two-PCB integrated liquid cooling model. Same thermal estimation as single PCB structure was verified. An experimental prototype with one PCB and cooling setup with liquid and air cooling was built. A 1.3 kW LLC power converter was developed, 50% less temperature rise on critical devices and 0.6% better efficiency are achieved. Thereafter, the proposed MPDC structure was investigated based the single PCB design. The two-layer MPDC prototype repeats the same efficiency and thermal performance while achieving 31% improvement in power density.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".