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System Dependability Evaluation Including S-dependency and Uncertainty - Model-Driven Dependability Analyses (Hardcover, 1st ed. 2018)
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System Dependability Evaluation Including S-dependency and Uncertainty - Model-Driven Dependability Analyses (Hardcover, 1st ed. 2018)
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The book focuses on system dependability modeling and calculation,
considering the impact of s-dependency and uncertainty. The best
suited approaches for practical system dependability modeling and
calculation, (1) the minimal cut approach, (2) the Markov process
approach, and (3) the Markov minimal cut approach as a combination
of (1) and (2) are described in detail and applied to several
examples. The stringently used Boolean logic during the whole
development process of the approaches is the key for the
combination of the approaches on a common basis. For large and
complex systems, efficient approximation approaches, e.g. the
probable Markov path approach, have been developed, which can take
into account s-dependencies be-tween components of complex system
structures. A comprehensive analysis of aleatory uncertainty (due
to randomness) and epistemic uncertainty (due to lack of
knowledge), and their combination, developed on the basis of basic
reliability indices and evaluated with the Monte Carlo simulation
method, has been carried out. The uncertainty impact on system
dependability is investigated and discussed using several examples
with different levels of difficulty. The applications cover a wide
variety of large and complex (real-world) systems. Actual
state-of-the-art definitions of terms of the IEC 60050-192:2015
standard, as well as the dependability indices, are used uniformly
in all six chapters of the book.
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