Formal analysis of fault tree using probabilistic model checking: A solar array case study
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
Fault Tree Analysis (FTA) is a widespread technique used to assess the reliability of safety-critical systems. The traditional way of conducting FTA is either through paper and pencil proof or through computer simulation techniques, which are inefficient and prone to inaccuracy. In this paper, we propose the use of probabilistic model checking to automatically analyze fault trees of safety-critical systems. Our methodology consists in the probabilistic formalization of the gates used in a fault tree to a Discrete-Time Markov Chain (DTMC) and a Markov Decision Process (MDP), and the subsequent probabilistic verification using PRISM tool to quantitatively analyze the system. To illustrate the proposed approach we perform the fault tree analysis of a solar array system, used as power source for the DFH-3 satellite. The results show that harsh thermal environment is the main cause of system failures.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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