Publications

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Sandia's Continuous Reliability Enhancement for Wind (CREW) Program is a follow on project to the Wind Plant Reliability Database and Analysis Program. The goal of CREW is to characterize the reliability performance of the US fleet to serve as a basis for improved reliability and increased availability of turbines. This document states the objectives of CREW and describes how data collected for CREW will be used in analysis. A critical aspect to the success of the CREW project is data input from participating owner/operators. The level of detail and the quality of input data provided dictates the type of analysis that can be accomplished. Options for analysis range from high level availability summaries to detailed analysis of failure modes for individual equipment items. Specific types of input data are identified followed by samples of the type of output that can be expected along with a discussion of benefits to the user community.

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Calculating operational availability (Ao) for a system of systems (SoS) presents unique challenges to reliability, availability, and maintainability (RAM) assessment, modeling, and analysis. System interdependencies and complex interrelated sustainment operations that exist in a SoS present complexities that must be accounted for in calculating or estimating Ao for the SoS. These system interdependencies affect the operating, operable, and down times of the individual systems. Both system-level and SoS-level Ao performance must be assessed within the SoS context for logistics and planning purposes. However, metrics calculated for the individual systems as part of the SoS may not be appropriate for assessing the individual system performance against their individual system requirements. In most cases, simulation modeling is required to capture the complex operating, operable, and down time hours of a SoS and the systems in the SoS, and to accurately aggregate the individual system availabilities to higher SoS levels. This paper explores some of the complexities involved in SoS Ao modeling and presents So S simulation results from a modeled SoS application.

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