Model Order Reduction and Applications

Michael Hinze

ISBN 10: 3031295625 / ISBN 13: 9783031295621

Editore: Springer Nature Switzerland Jun 2023, 2023

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This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses the state of the art of reduced order methods for modelling and computational reduction of complex parametrised systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in various fields.Consisting offour contributions presented at the CIME summer school,the bookpresentsseveral pointsof view and techniques to solve demanding problems of increasing complexity. The focus ison theoretical investigation and applicative algorithm development for reduction inthe complexity - the dimension, the degrees of freedom, the data - arising in these models.The book is addressed to graduate students, young researchers and people interested in the field. It is a good companion for graduate/doctoral classes. 244 pp. Englisch.

Codice articolo 9783031295621

Dati bibliografici

• Titolo: Model Order Reduction and Applications
• Editore: Springer Nature Switzerland Jun 2023
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 3031295625
• ISBN 13: 9783031295621
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 13 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 13 millimetri di profondità
• Peso: 421 grammi

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Riassunto

This book addresses the state of the art of reduced order methods for modelling and computational reduction of complex parametrised systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in various fields.

Consisting of  four contributions presented at the CIME summer school, the book presents several points of view and techniques to solve demanding problems of increasing complexity. The focus is on theoretical investigation and applicative algorithm development for reduction in the complexity – the dimension, the degrees of freedom, the data – arising in these models.

The book is addressed to graduate students, young researchers and people interested in the field. It is a good companion for graduate/doctoral classes.