Publicação:
Probabilistic prognostics and health management of energy systems

dc.contributor.authorEkwaro-Osire, Stephen
dc.contributor.authorCarlos Gonçalves, Aparecido [UNESP]
dc.contributor.authorAlemayehu, Fisseha M.
dc.contributor.institutionTexas Tech University
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionWest Texas A and M University
dc.date.accessioned2018-12-11T16:48:51Z
dc.date.available2018-12-11T16:48:51Z
dc.date.issued2017-04-25
dc.description.abstractThis book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters. It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.en
dc.description.affiliationDepartment of Mechanical Engineering Texas Tech University
dc.description.affiliationDepartment of Mechanical Engineering São Paulo State University (UNESP)
dc.description.affiliationSchool of Engineering Computer Science and Mathematics West Texas A and M University
dc.description.affiliationUnespDepartment of Mechanical Engineering São Paulo State University (UNESP)
dc.format.extent1-277
dc.identifierhttp://dx.doi.org/10.1007/978-3-319-55852-3
dc.identifier.citationProbabilistic Prognostics and Health Management of Energy Systems, p. 1-277.
dc.identifier.doi10.1007/978-3-319-55852-3
dc.identifier.scopus2-s2.0-85027839037
dc.identifier.urihttp://hdl.handle.net/11449/170039
dc.language.isoeng
dc.relation.ispartofProbabilistic Prognostics and Health Management of Energy Systems
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.titleProbabilistic prognostics and health management of energy systemsen
dc.typeLivro
dspace.entity.typePublication
unesp.author.lattes7516385196117516[2]
unesp.author.orcid0000-0001-5376-3392[2]

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