Critical comparison of two user friendly tools to study Piecewise Deterministic Markov Processes (PDMP): Season 2

Zitrou, Athena; Bedford, Tim; Walls, Lesley; Wilson, Kevin H.; Bell, Keith

doi:10.1201/b15938-176

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The uncertainties in windfarms, and other energy projects, fall into two classes: aleatory uncertainties associated with hard-to-predict scenarios such as catastrophic weather events which can severely damage turbines and epistemic uncertainties such as the expected lifetimes of key turbine components and the availability of repair equipment. An approach to investigating these uncertainties is to build a stochastic computer model (a stochastic simulator ), such as the Athena simulator (Zitrou et al 2013(Zitrou et al , 2016, which motivates this article. The Athena simulator is a stochastic simulation of an offshore windfarm, with a focus on the early life of a windfarm.…”

Section: Introductionmentioning

confidence: 99%

Multilevel Emulation for Stochastic Computer Models with Application to Large Offshore Wind farms

Kennedy¹,

Henderson²,

Wilson³

2020

Preprint

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Increasingly, stochastic computer models are being used in science and engineering to predict and understand complex phenomena. Despite the power of modern computing, these simulators are often too computationally costly to be of practical use due to their complexity. Hence the emulation of stochastic computer models is a problem of increasing interest. Many stochastic computer models can be run at different levels of complexity, which incurs a trade-off with simulation accuracy. More complex simulations are more expensive to run, but will often be correlated with less complex but cheaper to run versions. We present a heteroscedastic Gaussian process approach to emulation of stochastic simulators which utilises cheap approximations to a stochastic simulator, motivated by a stochastic reliability and maintenance model of a large offshore windfarm. The performance of our proposed methodology is demonstrated on two synthetic examples (a simple, tractable example and a predator-prey model) before being applied to the stochastic windfarm simulator.

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Section: Introductionmentioning

confidence: 99%

Multilevel Emulation for Stochastic Computer Models with Application to Large Offshore Wind farms

Kennedy¹,

Henderson²,

Wilson³

2020

Preprint

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“…The turbines will be subject to both corrective and preventive maintenance, and the effect of maintenance is expected to vary from perfect to imperfect, depending on the type of failure and maintenance action. The maintenance strategy setting is similar to the one considered in [Zitrou et al, 2013].…”

Section: Example Modelling Of Epistemic Uncertainty On Farm Availabilitymentioning

confidence: 99%

Expert methods in system safety and reliability Aeronautics and Aerospace Development of a new algorithm for optimal multi-level redundancy allocation

Zitrou¹,

Bedford²,

Walls³

2014

Safety and Reliability: Methodology and Applications

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This version is available at https://strathprints.strath.ac.uk/52115/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. ABSTRACTUnderstanding the level of control one has over risk is important in the context of financial decisionmaking associated with new offshore wind farm projects. Effective risk management requires a new model to adequately address systemic risk, which is important for two reasons. First, if systemic risk, which impacts across all turbines, is ignored then overall farm performance will be over-estimated. Second, the epistemic uncertainty associated with systemic risk reduces as we learn from relevant data and information gathered from, for example, relevant testing.We have developed a novel availability growth model that takes into account the sources of systemic risk to provide a more accurate estimation of farm performance over early life. Our model focuses on early operating life because the impact of systemic risk is more prevalent when teething problems arise and are resolved through remedial actions at the price of additional investment. Our model can be used to understand the scale of uncertainties involved in wind farm development and, thus, inform decisions to grow availability and buy-down risk. The model captures the specific effect of epistemic issues on the wind farm subassemblies, as well as their aggregated effect on overall farm performance. Our model has a general structure that can be adjusted to reflect a particular application. This paper explains how we have designed and implemented a structured expert judgment elicitation process to identify key uncertainties for a particular offshore wind farm context and to quantify model parameters associated with epistemic uncertainties.We overview our contextual model to set the scene before describing the mathematical approach to modelling the epistemic uncertainties. We explain our general protocol of expert judgment elicitation, which involves a qu...

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Accelerated reliability testing of articulated cable bend restrictor for offshore wind applications

Thies

Johanning

Bashir

et al. 2016

International Journal of Marine Energy

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Power cable failures for offshore marine energy applications are a growing concern since experience from offshore wind has shown repeated failures of interarray and export cables. These failures may be mitigated by dedicated cable protection systems, such as bend restrictors. This paper presents the rationale and the results for accelerated reliability tests of an articulated bend restrictor.The tests are a collaborative effort between the University of Exeter, CPNL Engineering and NSW, supported by the EU MARINET programme.The tests have been carried out at full-scale and exposed the static submarine power cable -bend restrictor specimen to mechanical load regimes exceeding the allowable design loads in order to provoke accelerated wear and component failures. The tested load cases combined cyclic bending motions with oscillating * corresponding author, Tel.: +44 (0) The test demonstrated the integrity of the cable protection system with quantified wear rates obtained through 3D scanning of the individual shells.The static power cable also maintained its integrity throughout the accelerated test regime. None of the failure modes, mainly fatigue cracks and fretting of individual wires, identified by cable dissection would have caused a direct loss of service. The observed failure modes could also be predicted through numerical load analysis, giving confidence in the utilised mechanical modelling and crosssectional analysis for dynamic applications.

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Critical comparison of two user friendly tools to study Piecewise Deterministic Markov Processes (PDMP): Season 2

Cited by 3 publications

References 2 publications

Multilevel Emulation for Stochastic Computer Models with Application to Large Offshore Wind farms

Multilevel Emulation for Stochastic Computer Models with Application to Large Offshore Wind farms

Expert methods in system safety and reliability Aeronautics and Aerospace Development of a new algorithm for optimal multi-level redundancy allocation

Accelerated reliability testing of articulated cable bend restrictor for offshore wind applications

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