Model Validation and Uncertainty Quantification, Vol. 3 : Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics 2024

Roland Platz

ISBN 10: 3031688929 / ISBN 13: 9783031688928

Verlag: Springer International Publishing, Springer Nature Switzerland, 2024

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on:Uncertainty Quantification in DynamicsFusion of Test and AnalysisModel Form Uncertainty: Round Robin Challenge UQVI (Uncertainty Quantification in Vibration Isolation)Recursive Bayesian System IdentificationVirtual Sensing & Realtime MonitoringSurrogate Modeling and Reduced Order Models. Bestandsnummer des Verkäufers 9783031688928

Bibliografische Details

Titel: Model Validation and Uncertainty ...

Verlag: Springer International Publishing, Springer Nature Switzerland

Erscheinungsdatum: 2024

Einband: Buch

Zustand: Neu

Über diesen Titel

Inhaltsangabe:

Model Validation and Uncertainty Quantification, Volume 3:  Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the third volume of ten from the Conference brings together contributions to this important area of research and engineering.  The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on:

• Uncertainty Quantification in Dynamics
• Fusion of Test and Analysis
• Model Form Uncertainty: Round Robin Challenge UQVI (Uncertainty Quantification in Vibration Isolation)
• Recursive Bayesian System Identification
• Virtual Sensing & Realtime Monitoring
• Surrogate Modeling and Reduced Order Models