Design and Modelling of a Novel Combustion Heat Exchanger for Household Heating
Bibliographic record
Abstract
The present study is focused on the design and modelling of a novel Combustion Heat Exchanger (CHE), used for heating and hot water supplies in residential buildings.System design includes a combination of an efficient porous burner and heat exchangers.Combined with an Organic Rankine Cycle (ORC) and a Heat Pump (HP), it is meant to deliver higher energy efficiency as well as reduced greenhouse gas emissions.A numerical model has been developed in STAR-CCM+ to evaluate the design.Furthermore, system level heat transfer calculations were acquired to assist with the design process.A step by step approach was undertaken to investigate physical and chemical phenomena in the system.System dimensions, exchanger location and geometry, air/fuel ratio, porous media models, radiation and combustion were investigated along with different exchanger geometries.A novel spiral heat exchanger was introduced in addition to the common coil designs to exhibit both convection and radiation heat transfers.The results indicated that the exhibition of spiral heat exchanger would result in significantly enhanced heat transfer.Overall heat transfer coefficients of 4-5 times higher in comparison to coils could be expected for spiral exchangers.It was shown that radiation heat transfer accounts for a prominent share in the total heat transfer.Furthermore, the CHE could operate at a wide range of lean air/fuel ratios, enabling further decrease in greenhouse gas emissions.As the last part of the study, further investigations on the regular coil exchangers indicated that these exchangers could still be used with the design, but heat transfer enhancement is required to reduce the dimensions.Such enhancements were tested through shell geometry designs with improved results.Overall, the system shows a promising solution for further reduction of CO2 emissions while improving thermal efficiency.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".