Sensitivity Analysis of a SOFC-GT Based Power Cycle
Bibliographic record
Abstract
This paper presents the sensitivity analysis of tubular Solid Oxide Fuel Cell (SOFC) stacks. The macro level modelling implemented in AspenPlus™ for the simulation of hybrid SOFC-gas turbine systems. The macro level thermodynamic first law analysis was previously performed on the same model. This sensitivity analysis is the continuation towards investigating the effects of different fuel compositions and turbine and compressor efficiencies on cycle efficiency and other parameters. The model is 0-dimensional, can accept hydrocarbon fuels with user inputs of current density, fuel and air composition, flow rates, temperature, pressure and fuel utilization factor. The model outputs the composition of the exhaust, work produced, heat available for reformer, etc. The model was developed considering the activation, concentration and ohmic losses within SOFC and mathematical expressions for these were chosen based on available studies in recent literatures. In this paper different fuels such as reformed natural gas, biogas with different compositions are considered to investigate the effect of fuel composition on the performance of the hybrid SOFC-gas turbine systems. In order to monitor the performance of the system parameters such as thermal efficiency, cycle specific work, SOFC specific work, gas turbine specific work, and work ratio (SOFC work / gas turbine work) are investigated. Furthermore, for specific fuel the effect of turbine and compressor efficiencies on system’s overall performance are studied for entire range from 50% to 100%, keeping gas turbine efficiency constant and increasing compressor efficiency by 5% and vice versa. For instance, if the fuel is switched from natural gas (with 100% CH4) to biogas (with the composition of 70% CH4, 25% CO2 and 5% H2) and the other parameters are kept constant (isentropic efficiency 85% for both turbine and compressor) the overall thermal efficiency will decrease by 1.4%, whereas the cycle specific work will increase by 36.7%. In addition, the work ratio will increase by 25.1% showing that more power is generated in SOFC in comparison to gas turbine. In addition, if the efficiency of turbine and compressor increase from 85% to 90%, the efficiency and cycle specific work of the system will increase by 3.1% and 3%, respectively whereas, the work ratio will decrease by 5.6%, due to the more power generated in gas turbine.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".