Heat transfer enhancement in shell and tube Latent Heat Thermal Energy Storage units for waste heat recovery applications: A 3D numerical study on melting–solidification kinetics
Bibliographic record
Abstract
This study presents a novel three-dimensional (3D) numerical investigation of a finned diamond-shaped multi-tube latent heat thermal energy storage (LHTES) unit for low-temperature industrial waste heat recovery applications. Unlike existing studies that rely on simplified two-dimensional (2D) simulations and square shaped tubes geometry, this work introduces an innovative diamond-shaped tube configuration with longitudinal fins, enhancing both melting and solidification dynamics. The proposed heat storage unit is compared at iso-volume of PCM to a finless multi-tube unit, considered a reference case. Using erythritol as phase change material (PCM) and Hytherm 600 as heat transfer fluid (HTF), the study demonstrates that the proposed design achieves reductions of 24.5 % and 45.5 % in the melting and solidification times, respectively, compared to a finless reference case. Additionally, the influence of axial temperature gradients and Reynolds number variations on phase change dynamics is thoroughly examined, revealing non-negligible three-dimensional effects and significant improvements in heat transfer performance. The axial temperature gradient in the tubes and the tridimensionality effect involved influence phase change dynamics with a difference exceeding 17 % and 16.36 % in melting and solidification, respectively. Moreover, the Reynolds number effect is more significant during the melting process and for the enhanced configuration. Up to 14 % and 8 % reductions in melting and solidification times is achieved for the improved configuration, compared with 12.1 % and only 3 % for the reference case when the Reynolds number was increased from 1000 to 2000.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".