Optimal orientation of phase change material energy storage systems for different performance indicators and charging levels
Bibliographic record
Abstract
This paper establishes the contradictory relationship between the storage orientation and both the charging levels and the performance indicators of single-stage latent heat thermal energy storage systems (LHTESS). The performance indicators (cycle charging capacity, charging time, charging rate, and average effectiveness) at seven inclination angles (0, 15, 30, 45, 60, 75, and 90°) and six charging levels (0.5, 0.7, 0.9, 0.98, 0.99, and 1.0) are obtained. A three-dimensional transient simulation model based on the enthalpy porosity technique is developed to evaluate the LHTESS performance. The results showed that the best inclination angle for the single-stage LHTESS is strongly related to the charging level and the considered performance indicator. The charging time and charging rate are more sensitive to the orientation and charging level than the effectiveness or cyclic charging capacity. Conversely, the maximum cycle charging capacity is independent of the charging level, as it always occurs with the horizontal LHTESS. At the complete charging level, the lowest charging time, the highest charging rate, and average effectiveness happen at an inclination angle of 60°. In contrast, the highest charging rate occurs at inclination angles of 15, 30, 45, and 60° at charging levels of 0.50, 0.70–0.90, 0.98–0.99, and 1.0, respectively. Also, the highest average effectiveness occurs for the horizontal LHTESS at liquid fractions of 0.50 and 0.70, 30° for a liquid fraction of 0.90, and 45° for liquid fractions of 0.98 and 0.99.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".