Modeling and Optimal Operation of Thermoelectric Microgrids with Phase-Change Material Thermal System
Bibliographic record
Abstract
Given that the building sector takes up nearly 40% of all energy consumed worldwide and is responsible for 33% of Greenhouse Gas (GHG) emissions [1], the adoption of more energy-efficient solutions is critical. Thus, integrating clean-energy microgrids (MGs) with advanced thermal management systems is paramount. In this context, Phase-Change Materials (PCMs) have gained significant attention due to their potential to enhance the thermal performance of buildings, providing economical benefits. PCMs are thermal storage media that operate on the principle of latent heat storage, i.e., they absorb or release thermal energy through phase transitions while maintaining an almost constant temperature. When thermal energy is supplied, a PCM changes its physical state from solid to liquid or vice versa. Due to their significantly higher energy density compared to sensible heat storage systems, PCMs are well-suited for compact and efficient thermal management applications.
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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) | 0.001 | 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".