NUMERICAL STUDY OF THE EFFECTS OF FINS AND THERMAL FLUID VELOCITIES ON THE STORAGE CHARACTERISTICS OF A CYLINDRICAL LATENT HEAT ENERGY STORAGE SYSTEM
Bibliographic record
Abstract
This thesis work presents a numerical study of the effects of fins and thermal fluid velocities on the storage characteristics of a cylindrical latent heat energy storage system (LHESS). The work consists of two main components: \n1. The development of a numerical method to study and solve the phase change heat transfer problems encountered in a LHESS during charging of the system, which results in melting of the phase change material (PCM). The numerical model is based on the finite element method. The commercial software COMSOL Multiphysics was used to implement it. The effective heat capacity method was applied in order to account for the large amount of latent energy stored during melting of a PCM, and the moving interface between the solid and liquid phases. The fluid flow, heat transfer and phase change processes were all validated using known analytical solutions or correlations. \n2. Due to the low thermal conductivity of PCMs, the heat transfer characteristics of an enhanced LHESS was studied numerically. The effects of fins and the thermal fluid velocity on the melting rate of the PCM in the LHESS were analyzed. Results obtained for configurations having between 0 and 27 fins show that the heat transfer rate increases with addition of fins and thermal fluid velocity. The effect of the HTF velocity was observed to be small with few fin configurations since the thermal resistance offered by the LHESS system, mostly PCM, is vastly more important under these conditions; while its effect becomes more pronounced with addition of fins, since the overall thermal resistance decreases greatly with the addition of fins. The total energy stored after 12 hours for 0 and 27 fins configurations range between 3.6 MJ and 39.7 MJ for a thermal fluid velocity of 0.05 m/s and between 3.7 MJ and 57 MJ for a thermal fluid velocity of 0.5 m/s. The highest system efficiencies for the 0.05 m/s and 0.5 m/s, obtained with 27 fins configuration are 68.9% and 97.9% respectively.
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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) | 0.000 | 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) | 0.000 | 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".