Optimization of thermal storage using different materials for cooking with solar power
Bibliographic record
Abstract
Previous studies into the use of solar power have been limited to storage materials and general applications; however, our study focused on the use of solar power for food preparation (cooking) and the selection of materials for the major components (storage material, insulation, convective lid) of a thermal energy storage system to optimize the use of solar power for cooking when sunlight is absent, e.g., evening/night. Our study incorporated different materials for each component, considering system performance and the costs of materials as key evaluation parameters. Based on our results, we optimized the system using selected materials and then compared it with an experimental model used for validation. Solar salt was selected as the storage material, sugarcane fibers were used as insulation, and copper was used as the convective material for the lid of the cooking pot. The results showed that the optimized system was 38.8 % more efficient than the experimental model. Moreover, the materials we selected for the optimized system are inexpensive, increasing affordability and thus encouraging consumers to use this eco-friendly system.
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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".