Monitoring of solid oxide fuel cell systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Fault detection and isolation of critical equipments as well as process operation is an important part of automation. Failure to detect fault can contribute to process safety incident, violation of environmental regulation and, as a result, reduce profit from the unit affected by the fault. Even though there has been a lot of work done on the modeling and control of the solid oxide fuel cell, little attention has been paid to its monitoring methodology. The need of reliable SOFC operations and current effort toward commercialization call for advanced monitoring technology, which constitutes one of the most important directions for SOFC research and development. In this article, as an attempt toward monitoring of SOFC systems a hybrid monitoring approach is developed which formulates the fault detection problem as a linear matrix inequality (LMI). The formulation is then illustrated through its application to the solid oxide fuel cell and its system to handle constraints and detect faults early. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.
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.
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 it