Numerical study of waste heat recovery by direct heat exchanger systems
Bibliographic record
Abstract
Abstract Dependency on fossil fuel and associated carbon footprints have increased the urge to look for methods to increase the thermal efficiency of heating and cooling systems. Exhaust air heat recovery system is one of the promising solutions with viable potential in industrial applications such as mine ventilation and so on. Direct contact heat exchangers can be feasibly used in these applications due to their characteristic advantages such as the ability to exchange at low temperature differences. Given the numerous advantages of such systems, there is a need for thorough understanding of the complex fluid flow and heat transfer performance of these heat exchangers. While water spray is commonly used for capturing the heat from exhaust air in direct heat exchange systems, performance of such system is highly dependent on the various operating parameters such as droplet size distribution, continuous phase temperature, velocity and relative humidity, spray nozzle angle and discrete phase temperature and velocity which is required to be studied in greater depth. Computational Fluid Dynamics can play a key role to investigate the performance of these two-phase flow systems. In this paper, a three-dimensional two-phase model has been presented to study heat recovery from exhaust air by using direct spray water heat recovery systems. Also, an analytical model has been developed using a self-written MATLAB code and compared to the numerical one. The results of the study show that the analytical model can capture the CFD runs outcomes with a high degree of accuracy. Also, the conducted parametric study confirms the dominant impacts of droplet size distribution and air flow rate on the performance of 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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".