Multiphysics modeling and optimization of a methanol-fueled SOFC for distributed power applications
Bibliographic record
Abstract
A comprehensive multiphysics model of a solid oxide fuel cell (SOFC) system externally fueled by a methanol reforming unit (MRU) is developed and validated using experimental measurements. The model enables a combined analysis of the three main operating concerns: electrical efficiency, energy efficiency, and carbon deposition. A 2D axisymmetric finite element model of the SOFC is coupled with a thermodynamic equilibrium model of the MRU to examine the effects of five operating parameters: temperature, methanol feed rate, steam-to-carbon ratio (S/C), air-to-carbon ratio (A/C), and current density. Both models are validated against experimental data, including GC-MS reformate analysis and polarization curves. A full parametric study is then carried out to assess electrical efficiency and overall energy balance. Results show that temperature is the dominant factor, with nearly a 60 % efficiency drop when decreasing from 850 °C to 750 °C. Increasing S/C slightly improves electrical efficiency but adds a significant thermal penalty, while higher A/C consistently reduces efficiency despite potential heat-balance advantages. The optimal operating window is identified at high temperature (800–850 °C), low methanol feed rate, and low S/C or A/C ratios (0.15–0.3). These conditions maximize electrical efficiency, avoid external energy input, and prevent coke formation at the anode.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".