Model Validation and Uncertainty Quantification, Volume 3

Zhu Mao

ISBN 10: 3030773477 / ISBN 13: 9783030773472

Editore: Springer International Publishing, Springer Nature Switzerland Jan 2022, 2022

Riguardo questo articolo

Neuware -Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the third volume of nine 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:Inverse Problems and Uncertainty QuantificationControlling UncertaintyValidation of Models for Operating EnvironmentsModel Validation & Uncertainty Quantification: Decision MakingUncertainty Quantification in Structural DynamicsUncertainty in Early Stage DesignComputational and Uncertainty Quantification ToolsSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.

Codice articolo 9783030773472

Dati bibliografici

• Titolo: Model Validation and Uncertainty Quantification, Volume 3
• Editore: Springer International Publishing, Springer Nature Switzerland Jan 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 3030773477
• ISBN 13: 9783030773472
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 285 L x 215 A x 17 P (millimetri) 285 millimetri di larghezza per 215 millimetri di altezza per 17 millimetri di profondità
• Peso: 745 grammi

Descrizione articolo

Riassunto

Model Validation and Uncertainty Quantification, Volume 3:  Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the third volume of nine 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:

• Inverse Problems and Uncertainty Quantification
• Controlling Uncertainty
• Validation of Models for Operating Environments
• Model Validation & Uncertainty Quantification: Decision Making
• Uncertainty Quantification in Structural Dynamics
• Uncertainty in Early Stage Design
• Computational and Uncertainty Quantification Tools

Informazioni sull?autore

Zhu Mao, University of Massachusetts Lowell, MA, USA