Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/5282
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dc.contributor.authorPriyadarshini, S.-
dc.contributor.authorBehera, S.K.-
dc.date.accessioned2025-08-14T12:25:55Z-
dc.date.available2025-08-14T12:25:55Z-
dc.date.issued2025-07-
dc.identifier.citationApplied Materials & Interfaces Conference (AMIC), NTU Singapore, 3-5 July 2025en_US
dc.identifier.urihttp://hdl.handle.net/2080/5282-
dc.descriptionCopyright belongs to the proceeding publisher.en_US
dc.description.abstractGas Foil Bearings (GFBs) have emerged as essential components in modern high-speed, oil-free rotating machinery, driven by demands for higher efficiency, lower maintenance, and environmental sustainability. However, their dynamic performance is highly sensitive to wear, thermal loading, and transient events such as rotor imbalances and high-speed start-ups. To address these challenges, the integration of AI into GFBs represents a promising advancement in industries. This paper presents a conceptual and technological review of smart Gas Foil Bearings incorporating AI. The potential benefits of smart GFBs—performance optimization—are useful for critical applications such as aerospace propulsion, microturbines. Key technological challenges, ….with future research directions to enable the next generation foil bearing systems.en_US
dc.subjectGas Foil Bearings (GFBs)en_US
dc.subjectFoil bearing systemsen_US
dc.subjectAerospace propulsionen_US
dc.subjectMicroturbinesen_US
dc.titleTowards Smart Tribological Systems: AI-Based Analysis of Gas Foil Bearings in Turbomachineryen_US
dc.typePresentationen_US
Appears in Collections:Conference Papers

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