H. Boudali and J. Dugan, “A New Bayesian Network Approach to Solve Dynamic Fault Trees,” Proceedings of Annual Reliability and Maintainability Symposium, Alexandria, 24-27 January 2005, pp. 451-456. doi:10.1109/RAMS.2005.1408404

has been cited by the following article:

• TITLE: The Dynamic-to-Static Conversion of Dynamic Fault Trees Using Stochastic Dependency Graphs and Stochastic Activity Networks

  AUTHORS: Gabriele Manno, Ferdinando Chiacchio, Francesco Pappalardo

  KEYWORDS: Dynamic Fault Tree; Stochastic Dependency Graphs; Stochastic Activity Network; Continuous Time Markov Chain

  JOURNAL NAME: Engineering, Vol.5 No.2, February 6, 2013

  ABSTRACT: In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.