Johnson’s SU distribution using Gray Wolf Optimizer algorithm for fitting gas turbine reliability data

Abstract Controlling failures and degradation of gas turbines is crucial for optimizing efficiency, productivity, and maintaining safe operations in the oil and gas industry. Reliability indices play a vital role in supporting these goals by enabling informed decisions about gas turbine lifespan ext...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Charrak, Naas [verfasserIn]

Djeddi, Ahmed Zohair [verfasserIn]

Hafaifa, Ahmed [verfasserIn]

Elbar, Mohammed [verfasserIn]

Iratni, Abdelhamid [verfasserIn]

Colak, Ilhami [verfasserIn]

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2024

Schlagwörter:

Johnson distributions

SU distribution

Gray Wolf Optimizer

Gas turbine

Reliability data

Data fitting

Weibull distribution

Dependability

Anmerkung:

© The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:

Enthalten in: Life cycle reliability and safety engineering - Springer Nature Singapore, 2017, 13(2024), 3 vom: 12. Juli, Seite 255-275

Übergeordnetes Werk:

volume:13 ; year:2024 ; number:3 ; day:12 ; month:07 ; pages:255-275

Links:

Volltext

DOI / URN:

10.1007/s41872-024-00259-5

Katalog-ID:

SPR057172838

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