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Existing methods to predict software reliability using the Markov chain are based on assumed state-transition probabilities. A new prediction approach applied to a nuclear plant's feed-water system yielded results that were 96.9 percent accurate relative to the system's actual reliability. Across 38 operational datasets, the average accuracy was 99.67 percent.
Instrumentation and Control systems are the nervous system of a nuclear power plant. They monitor all facets of the plant’s health and help respond with care and adjustments needed, thus ensuring goals of efficient power production and safety. Due to safety significance of I&C, it becomes increasingly important to have a design verification methodology which ensures I&C systems fully functional...
Computer based safety critical systems are progressively replacing analog systems in safety-critical applications like nuclear power plants. Hence these systems require modeling techniques to estimate performability in the early stages of the system development life cycle. This paper addresses the dynamic modeling of Test Facility of a safety critical system used in Nuclear Power plant. System function...
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