A porous medium based heat transfer and fluid flow model for thermal energy storage in packed rock beds
Bibliographic record
Abstract
Abstract Thermal energy storage in packed rock beds helps to reduce energy costs and carbon footprint’s on an industrial, commercial and residential scale. Fluid flow and heat transfer in large-size packed rock beds used in mining applications such as heating/cooling of mine intake air or ventilation of block-caved mines have recently received significant attention. Understanding the porous structure of such packed rock beds is a necessity in the design of such systems. The pressure drop across a rock bed directly affects its heat exchange performance, as it requires additional fan power to circulate air during periods of storage/extraction. In this study, the fluid flow behavior inside a packed rock bed thermal energy storage system is investigated by developing a computational fluid dynamics model and a heat transfer model. The model offers useful information for evaluating the performance of rock beds packed with large rocks or in caved zones. Finally, the main goal of this study is to perform a practical energy saving analysis for porous media composed of large particles by changing the physical properties of the porous medium, such as porosity and permeability. The findings of this study also show that while the total thermal energy storage capacity of the system is not significantly affected by the mass flow rate, a lower mass flow rate can provide a longer working period for thermal energy storage systems.
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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".