Turboelectric uncertainty quantification and error estimation in numerical modelling

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dc.contributor.authorAlrashed, Mosab
dc.contributor.authorNikolaidis, Theoklis
dc.contributor.authorPilidis, Pericles
dc.contributor.authorJafari, Soheil
dc.date.accessioned2020-03-06T16:31:31Z
dc.date.available2020-03-06T16:31:31Z
dc.date.issued2020-03-06
dc.description.abstractTurboelectric systems can be considered complex systems that may comprise errors and uncertainty. Uncertainty quantification and error estimation processes can, therefore, be useful in achieving accurate system parameters. Uncertainty quantification and error estimation processes, however, entail some stages that provide results that are more positive. Since accurate approximation and power optimisation are crucial processes, it is essential to focus on higher accuracy levels. Integrating computational models with reliable algorithms into the computation processes leads to a higher accuracy level. Some of the current models, like Monte Carlo and Latin hypercube sampling, are reliable. This paper focuses on uncertainty quantification and error estimation processes in turboelectric numerical modelling. The current study integrates the current evidence with scholarly sources to ensure the incorporation of the most reliable evidence into the conclusions. It is evident that studies on the current subject began a long time ago, and there is sufficient scholarly evidence for analysis. The case study used to obtain this evidence is NASA N3-X, with three aircraft conditions: rolling to take off, cruising, and taking off. The results show that the electrical elements in turboelectric systems can have decent outcomes in statistical analysis. Moreover, the risk of having overload branches is up to 2% of the total aircraft operation lifecycle, and the enhancement of the turboelectric system through electrical power optimisation management could lead to higher performance.en_UK
dc.identifier.citationAlrashed M, Nikolaidis T, Pilidis P, Jafari S. (2020) Turboelectric uncertainty quantification and error estimation in numerical modelling. Applied Sciences, Volume 10, Issue 5, March 2020, Article number 1805en_UK
dc.identifier.issn2076-3417
dc.identifier.urihttps://doi.org/10.3390/app10051805
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15248
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectturboelectric poweren_UK
dc.subjectuncertainty quantificationen_UK
dc.subjecterror estimationen_UK
dc.subjectnumerical modelling turboelectricen_UK
dc.subjectdistributed propulsionen_UK
dc.subjectapplied modellingen_UK
dc.titleTurboelectric uncertainty quantification and error estimation in numerical modellingen_UK
dc.typeArticleen_UK

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