Tunc Aldemir

Abstract:

The Markov/cell-to-cell mapping technique (CCMT) is a systematic procedure to describe the dynamics of both linear and non-linear systems in discrete time and in system state space previously partitioned into computational cells in a similar manner used by finite difference or finite element methods [1]. An important feature of the Markov/CCMT is its capability to model the long term dynamics of chaotic systems in a probabilistic format. Markov/CCMT has been used for the failure modeling of different types of control systems, as well as for state/parameter estimation and diagnostics, accident management and global analysis of reactor dynamics. Some example applications are provided in [1-5]. A continuous-time, discrete state-space version of Markov/CCMT has also been developed [6] and implemented for dynamic probabilistic risk/safety assessment [7]. An overview of the Markov/CCMT is presented, including computational tools for applications.