Detection of Precursors of Thermoacoustic Instability in a Swirled Combustor Using Chaotic Analysis and Deep Learning Models

This paper investigates the role of chaotic analysis and deep learning models in combustion instability predictions. To detect the precursors of impending thermoacoustic instability (TAI) in a swirled combustor with various fuel injection strategies, a data-driven framework is proposed in this study...

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Autori principali:	Boqi Xu, Zhiyu Wang, Hongwu Zhou, Wei Cao, Zhan Zhong, Weidong Huang, Wansheng Nie
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2024-06-01
Serie:	Aerospace
Soggetti:	combustion instability thermoacoustic instability chaotic analysis deep learning instability precursors
Accesso online:	https://www.mdpi.com/2226-4310/11/6/455
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