Thermodynamic Analysis of an Integrated SOFC, Solar ORC and Absorption Chiller for Tri‐generation Applications
Bibliographic record
Abstract
Abstract Thermodynamic performance assessment of an integrated tri‐generation energy system for power, heating and cooling production is conducted through energy and exergy analyses. Sustainability assessment is performed and some parametric studies are undertaken to analyze the impact of system parameters and environmental conditions on the system performance. The tri–generation system consists of (a) an internal reforming tubular type solid oxide fuel cell (IR‐SOFC), which works at ambient pressure and fueled with syngas, (b) a combustor and a air heat exchanger, (c) a heat recovery and steam generation unit (HRSG), (d) a two‐ stage Organic Rankine cycle (ORC) driven by exhaust gases of SOFC, (e) parabolic trough solar collectors (PTSC), and (f) a lithium‐bromide absorption chiller (AC) cycle driven by exhaust gases from SOFC unit. The largest irreversibility occurs at the SOFC unit due to high temperature requirement for reactions. Fuel utilization factor, recirculation ratio, dead state conditions, and solar unit parameters have influential effects on the system efficiencies. Energy and exergy efficiencies of tri‐generation unit become 85.1% and 32.62%, respectively, for optimum SOFC stack and environmental conditions. The overall system energy and exergy efficiencies are 56.25% and 15.44% higher than that of conventional SOFC systems, respectively.
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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".