Heat recovery from hydrothermal carbonization slurry product by coupling processes of flash and organic <scp>Rankine</scp> cycle: Thermodynamic analysis
Bibliographic record
Abstract
Abstract Hydrothermal carbonization (HTC) is a promising and effective technology for upgrading the fuel quality of high‐moisture organic wastes. However, a large amount of energy is required to heat the feedstock to high temperature for HTC. Therefore, the maximum waste heat should be recovered to increase the energy efficiency of the HTC process. In this work, a flash‐organic Rankine cycle (FSPG‐ORC) system was coupled after HTC to recover the heat contained in the HTC slurry product. Various operating factors including the flashing temperature, the HTC temperature, the solid‐water ratio (S/W) of the feedstock, and the organic working fluids in the ORC section were studied to obtain their influences on thermodynamic performance of the coupled system. Results indicated that the net power ( W net ) of the FSPG‐ORC system increased from 185.64 to 774.30 kW through the increase of the HTC temperature from 160 to 280°C. In addition, the W net and exergy efficiency of the FSPG‐ORC system also increased with increasing the flashing temperature of HTC slurry product. The coupled FSPG‐ORC system converted waste heat to electric energy and increased the energy efficiency of the HTC process.
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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) | 0.000 | 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) | 0.001 | 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".