Kolloquiumsvortrag Kunal Purohit, 05.11.2024 (Betreuer Dibaei Asl)
Analysis and optimization algorithm for fault tree
The safety and reliability of complex, high-hazard systems such as aircraft and nuclear power plants are paramount. Fault tree analysis (FTA) is one of the most important methods for assessing the reliability of such systems. Binary decision diagrams (BDDs) allow for more efficient system analysis and reliability assessment and are one of the most common methods for analyzing a fault tree.
Converting fault trees into BDDs is not unique and heavily depends on the ordering of the variables. Poor variable ordering can lead to large BDDs, increasing computational complexity and reducing analysis efficiency. There is a need to develop a more effective variable ordering method to generate compact BDDs for fault tree analysis.
This thesis explores existing variable ordering heuristics, specifically combining the priority ordering method and in-order traversal to experiment with fault tree analysis. These methods, which incorporate elements of both weight-based and structure-based techniques, were applied to fault trees from the FFORT dataset, a benchmark suite for industrial fault trees. After simplifying the fault trees, the XFTA tool was used to perform qualitative analysis, including extracting minimal cut sets. This exploration aims to investigate their potential for generating more compact BDD structures for efficient system analysis.
The results highlight relevant outcomes from the experiments, suggesting the potential for reducing computational overhead. This exploration provides insight into more efficient qualitative analysis, contributing to the reliability assessment of high-risk systems.
Zeit: 10:15 Uhr
Ort: Raum 04.137, Martensstr. 3, Erlangen
oder
Zoom-Meeting beitreten:
https://fau.zoom-x.de/j/68350702053?pwd=UkF3aXY0QUdjeSsyR0tyRWtLQ0hYUT09
Meeting-ID: 683 5070 2053
Kenncode: 647333