Investigation of Reverse Thermosyphoning in an Indirect SDHW System
Bibliographic record
Abstract
Thermal energy storages with thermosyphon natural convection heat exchangers have been used in solar water heating systems as a means of increasing tank stratification and eliminating the need for a second circulation pump. However, if the storage system is not carefully designed, under adverse pressure conditions, reverse thermosyphoning can result in increased thermal losses from the storage and reduced thermal performance of the system. To investigate this phenomenon, tests were conducted on a single tank and multi-tank thermal storage under controlled laboratory conditions. Energy storage rates and temperature profiles were experimentally measured during charge periods, and the effects of reverse thermosyphoning were quantified. A further aspect of this study was to empirically derive performance characteristics and to develop numerical models to predict the performance of the heat exchanger during reverse thermosyphon operation, and to quantify the relative magnitude of these effects on the energy stored during typical day-long charge periods. Results of this study show that the magnitude of the reverse flow rate depends on the pressure drop characteristics of the heat exchange loop, the system temperatures and the geometry of the heat exchanger and storage tank. In addition, the results show that in the case of a multi-tank thermal storage, the carry over of energy to the downstream thermal energy storages depend on the effectiveness of the exchangers used in the system.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".