Feasibility Study of an Organic Rankine Cycle System Coupled to a Diesel Engine
Bibliographic record
Abstract
A feasibility study has been conducted for an organic Rankine cycle (ORC) system coupled to the exhaust of a Diesel engine generator. The objective of this study was to determine the possible electrical generation of the ORC using the exhaust gas of a 78 kW diesel engine as its energy input. A thermodynamic model was developed to predict the possible electricity generation of the ORC. Using this model it was determined that the preferred working fluid for the ORC was R245ca. The calculated maximum ORC thermal efficiency was 14.3%. The net electrical power generated from the ORC was 5.36 kWe. The ORC would require no additional fuel and would not generate any additional emissions. The most cost-effective and simple means to develop a small packaged ORC system is to high volume production HVAC system components. An ORC system consisting of air conditioning system components, including a scroll expander, yielded a projected ORC efficiency of 10.7%, and a net electrical power of 4.02 kWe. The total capital cost of the ORC system was $2,140 CAD. Three engine usage scenarios were developed, with the time to payback of the initial capital cost of the ORC ranging from 12.8 to 0.58 years, depending on low or high usage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".