Fuel Composition Transients in Fuel Cell Turbine Hybrid for Polygeneration Applications
Bibliographic record
Abstract
Transient impacts on the performance of solid oxide fuel cell/gas turbine (SOFC/GT) hybrid systems were investigated using hardware-in-the-loop simulations (HiLSs) at a test facility located at the U.S. Department of Energy, National Energy Technology Laboratory. The work focused on applications relevant to polygeneration systems, which require significant fuel flexibility. Specifically, the dynamic response of implementing a sudden change in fuel composition from syngas to methane was examined. The maximum range of possible fuel composition allowable within the constraints of carbon deposition in the SOFC and stalling/surging of the turbine compressor system was determined. It was demonstrated that the transient response was significantly impact the fuel cell dynamic performance, which mainly drives the entire transient in SOFC/GT hybrid systems. This resulted in severe limitations on the allowable methane concentrations that could be used in the final fuel composition when switching from syngas to methane. Several system performance parameters were analyzed to characterize the transient impact over the course of 2 h from the composition change.
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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) | 0.000 | 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".