Assessment of a Geothermal Combined System with an Organic Rankine Cycle and Multi-effect Distillation Desalination
Bibliographic record
Abstract
Abstract An analysis is reported of a geothermal-based electricity-freshwater system in which an organic Rankine cycle is integrated with a multi-effect distillation desalination unit. The system is driven by geothermal hot water extracted from the production well. Mass, energy, entropy, and exergy rate balances are written for all system components, as are energy and exergy efficiency expressions for each subsystem. The exergy destruction rate associated with the temperature and chemical disequilibrium of the freshwater and brine with the reference environment are taken into account to reveal accurate results for irreversibility sources within the desalination process. The developed thermodynamic model is simulated using thermodynamic properties of the working fluids (i.e., ammonia, seawater, distillate, and brine) at each state point. A sustainability analysis is performed that connects exergy and environmental impact concepts. That assessment expresses the extent of the contribution of the system to sustainable development and reduced environmental impact, using exergy methods. Results of the sustainability analysis indicate that, with an increase in the reference environment temperature from 20 to 35 $$^\circ{\rm C}$$ ∘ C , the exergy destruction rate decreases for the multi-effect distillation and organic Rankine cycle systems respectively from 6474 to 4217 kW and from 16,270 to 13,459 kW. Also, the corresponding sustainability index for the multi-effect distillation and organic Rankine cycle systems increases from 1.16 to 1.2 and 1.5–1.6, respectively, for the same increase in reference environment temperature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".