Process Flow Model of Combined High Temperature Fuel Cell Operated With Mixture of Methane and Carbon Dioxide
Bibliographic record
Abstract
This paper investigates the impacts of carbon dioxide concentration in the inlet fuel on the performance of a hybrid tubular solid oxide fuel cell (SOFC) and gas turbine (GT) cycle with two configurations: system with and without anode exhaust recirculation. The reference case is introduced when the system is fueled by pure methane. Then, the performance of the hybrid SOFC-GT system is investigated when methane is partially replaced by CO2 from concentration of 0% to 90% with an increment of 5% at each step. The steady-state macro level model of the SOFC-GT hybrid system was developed in Aspen Plus® using built in and user-defined modules. The performance of the system was monitored by estimating and recording performance parameters, such as SOFC and system thermal efficiency; net and specific work of SOFC, GT, and cycle as a whole; air to fuel ratio; and mass and molar flow rate and temperature of various streams. The results demonstrate that the CO2 fraction in the inlet fuel has remarkable influences on the system’s operating parameters, such as efficiency and specific work.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".