Performance of Biogas Fueled Hybrid Solid Oxide Fuel Cell (SOFC) and Gas Turbine Cycle
Bibliographic record
Abstract
The macro level model of a solid oxide fuel cell (SOFC) system was developed considering fundamental equations of thermodynamics, chemical reactions, and electrochemistry. The SOFC model was implemented in a hybrid SOFC-gas turbine (GT) cycle model using Aspen Plus® to simulate two configurations, system with and without anode recirculation. In order to monitor the performance of the system, parameters such as SOFC and system thermal efficiency; SOFC, GT, and cycle net and specific work; as well as air to fuel ratio, and air and fuel mass flow rate were investigated. The results of simulation for different types of fuel, namely, pure methane, natural gas, coal syngas, different types of biomass syngas, and farm and sewage biogas showed that system output and operation parameters were greatly influenced by changes in the fuel composition. Therefore, in feasibility study of a SOFC-GT hybrid cycle fueled by biogas, gasified biomass, and syngas, it is vital that possibility of variation of inlet fuel composition and its impacts on system performance to be considered and investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 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".