Modelling Phase Change Material Thermal Storage Systems
Why this work is in the frame
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Bibliographic record
Abstract
In order to increase the overall efficiency of energy use in a community, excess thermal energy from inefficient processes can be stored and used for heating applications. A one-dimensional analytical conduction model is therefore developed for sizing of phase change material thermal energy storage systems. The model addresses rectangular channels of phase change material separated by flow channels for the addition and removal of thermal energy. The analytical model assumes a planar melt front and linear temperature profiles throughout the thermal storage cell. Heat flux and interface temperatures are calculated at various melt fractions based on a quasi-steady electrical analogue analysis of the instant in question. Compensation is made for the sensible energy change between melt fractions by adding this energy at the calculated heat flux. A two dimensional, conduction only computational fluid dynamics model is used to compare the response of the analytical model to changes in the input parameters and shows good agreement. A test apparatus and a three dimensional computational fluid dynamics model are also created and melt-time results compared to analytical model predictions. These comparisons also show good agreement. Finally, a thermal storage system is sized for a specific application, H<sub>2</sub>Green Energy Corporation's Distributed Storage System, with sizing based on the heat load requirements of McMaster Innovation Park during the winter months. Technical feasibility of this system is shown with analysis also included on economic feasibility. It is determined that the analytical model is sufficient for initial assessment of phase change material thermal energy storage systems where detailed geometry is unavailable. Recommendations are made for further validation of the model and the development of a phase change material properties database. Suggestions are also presented on additional sources of revenue for the H<sub>2</sub>Green Distributed Storage System that will increase its economic feasibility.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.036 | 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 it