The Experts below are selected from a list of 1803675 Experts worldwide ranked by ideXlab platform
Claudio Bittencourt Ferreira - One of the best experts on this subject based on the ideXlab platform.
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probabilistic failure Rate Model of a tidal turbine pitch system
Renewable Energy, 2020Co-Authors: Fraser J Ewing, Philipp R Thies, Jonathan Shek, Claudio Bittencourt FerreiraAbstract:Abstract AccuRate reliability prediction for tidal turbines is challenging due to scarce reliability data. To achieve commercialization, it is widely acknowledged that reductions in maintenance costs are vital and robust component reliability assessments can help drive this. For established technologies, reliability prediction either involves a statistical assessment of historical failure data, or a physics of failure approach based on dedicated acceleRated testing. However, for low/mid Technology Readiness Level tidal developers these common approaches are difficult. Thus, developers require a method of making reliability predictions for components in the absence of tidal turbine specific failure data and physical testing results. This paper presents a failure Rate Model for a tidal turbine pitch system using empirical Physics of Failure equations, with associated uncertainties. Critical component design parameters are determined and their effects on the failure Rate investigated via a sensitivity analysis. The Modelled failure Rate is then compared with wind turbine failure data from a series of turbines. The tidal turbine failure Rate is approximately 50% lower, however high reliability requirements mean this is unlikely to be acceptable. The developed Model can assist turbine developers in estimating failure Rates and determining reliability critical design parameters for the failure critical pitch system.
Fraser J Ewing - One of the best experts on this subject based on the ideXlab platform.
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probabilistic failure Rate Model of a tidal turbine pitch system
Renewable Energy, 2020Co-Authors: Fraser J Ewing, Philipp R Thies, Jonathan Shek, Claudio Bittencourt FerreiraAbstract:Abstract AccuRate reliability prediction for tidal turbines is challenging due to scarce reliability data. To achieve commercialization, it is widely acknowledged that reductions in maintenance costs are vital and robust component reliability assessments can help drive this. For established technologies, reliability prediction either involves a statistical assessment of historical failure data, or a physics of failure approach based on dedicated acceleRated testing. However, for low/mid Technology Readiness Level tidal developers these common approaches are difficult. Thus, developers require a method of making reliability predictions for components in the absence of tidal turbine specific failure data and physical testing results. This paper presents a failure Rate Model for a tidal turbine pitch system using empirical Physics of Failure equations, with associated uncertainties. Critical component design parameters are determined and their effects on the failure Rate investigated via a sensitivity analysis. The Modelled failure Rate is then compared with wind turbine failure data from a series of turbines. The tidal turbine failure Rate is approximately 50% lower, however high reliability requirements mean this is unlikely to be acceptable. The developed Model can assist turbine developers in estimating failure Rates and determining reliability critical design parameters for the failure critical pitch system.
Alessandro Gnoatto - One of the best experts on this subject based on the ideXlab platform.
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The Wishart short Rate Model
International Journal of Theoretical and Applied Finance, 2012Co-Authors: Alessandro GnoattoAbstract:We consider a short Rate Model, driven by a stochastic process on the cone of positive semidefinite matrices. We derive sufficient conditions ensuring that the Model replicates normal, inverse or humped yield curves.
Jonathan Shek - One of the best experts on this subject based on the ideXlab platform.
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probabilistic failure Rate Model of a tidal turbine pitch system
Renewable Energy, 2020Co-Authors: Fraser J Ewing, Philipp R Thies, Jonathan Shek, Claudio Bittencourt FerreiraAbstract:Abstract AccuRate reliability prediction for tidal turbines is challenging due to scarce reliability data. To achieve commercialization, it is widely acknowledged that reductions in maintenance costs are vital and robust component reliability assessments can help drive this. For established technologies, reliability prediction either involves a statistical assessment of historical failure data, or a physics of failure approach based on dedicated acceleRated testing. However, for low/mid Technology Readiness Level tidal developers these common approaches are difficult. Thus, developers require a method of making reliability predictions for components in the absence of tidal turbine specific failure data and physical testing results. This paper presents a failure Rate Model for a tidal turbine pitch system using empirical Physics of Failure equations, with associated uncertainties. Critical component design parameters are determined and their effects on the failure Rate investigated via a sensitivity analysis. The Modelled failure Rate is then compared with wind turbine failure data from a series of turbines. The tidal turbine failure Rate is approximately 50% lower, however high reliability requirements mean this is unlikely to be acceptable. The developed Model can assist turbine developers in estimating failure Rates and determining reliability critical design parameters for the failure critical pitch system.
Philipp R Thies - One of the best experts on this subject based on the ideXlab platform.
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probabilistic failure Rate Model of a tidal turbine pitch system
Renewable Energy, 2020Co-Authors: Fraser J Ewing, Philipp R Thies, Jonathan Shek, Claudio Bittencourt FerreiraAbstract:Abstract AccuRate reliability prediction for tidal turbines is challenging due to scarce reliability data. To achieve commercialization, it is widely acknowledged that reductions in maintenance costs are vital and robust component reliability assessments can help drive this. For established technologies, reliability prediction either involves a statistical assessment of historical failure data, or a physics of failure approach based on dedicated acceleRated testing. However, for low/mid Technology Readiness Level tidal developers these common approaches are difficult. Thus, developers require a method of making reliability predictions for components in the absence of tidal turbine specific failure data and physical testing results. This paper presents a failure Rate Model for a tidal turbine pitch system using empirical Physics of Failure equations, with associated uncertainties. Critical component design parameters are determined and their effects on the failure Rate investigated via a sensitivity analysis. The Modelled failure Rate is then compared with wind turbine failure data from a series of turbines. The tidal turbine failure Rate is approximately 50% lower, however high reliability requirements mean this is unlikely to be acceptable. The developed Model can assist turbine developers in estimating failure Rates and determining reliability critical design parameters for the failure critical pitch system.