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Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error boundSemi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.
Document ID
19910016427
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
White, Allan L. (NASA Langley Research Center Hampton, VA, United States)
Palumbo, Daniel L. (NASA Langley Research Center Hampton, VA, United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1991
Subject Category
Statistics And Probability
Report/Patent Number
L-16862
NASA-TP-3089
NAS 1.60:3089
Meeting Information
Meeting: Annual Reliability and Maintainability Symposium
Start Date: January 1, 1990
Accession Number
91N25741
Funding Number(s)
PROJECT: RTOP 505-66-21
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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