Numerical Investigation and Nondimensional Analysis of the Dynamic Performance of a Thermal Energy Storage System Containing Phase Change Materials and Liquid Water
Bibliographic record
Abstract
The dynamic performance of a thermal energy storage tank containing phase change material (PCM) cylinders is investigated computationally. Water flowing along the length of the cylinders is used as the heat transfer fluid. A numerical model based on the enthalpy-porosity method is developed and validated against experimental data from the literature. The performance of this hybrid PCM/water system was assessed based on the gain in energy storage capacity compared to a sensible only system. Gains can reach as high as 179% by using 50% packing ratio and 10 °C operating temperature range in water tanks. Gains are highly affected by the choice of PCM module diameter; they are almost halved as diameter increases four times. They are also affected by the mass flow rate nonlinearly. A nondimensional analysis of the energy storage capacity gains as a function of the key nondimensional parameters (Stefan, Fourier, and Reynolds numbers) as well as PCM melting temperature was performed. The simulations covered ranges of 0.1 < Stẽ < 0.4, 0 < Fo < 600, 20 < Re < 4000, 0.2<(ρCP)*<0.8, and 0.2<θm<0.8.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".