Search results for Fluid dynamics and solid mechanics

Mechanics of Ice Failure

An Engineering Analysis
Ian Jordaan
Published online:

10 February 2023

Print publication:

02 March 2023
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Featuring real-world examples and practical methodology, this rigorous text explores time dependence in the mechanics of ice. Emphasizing use of full scale data, and implementing risk-based design methods, mechanical theory is combined with design and modelling. Readers will gain understanding of fundamental concepts and modern advances of ice mechanics and ice failure processes, analysis of field data, and use of probabilistic design methods, with applications to the interaction of ships and offshore structures with thick ice features or icebergs. The book highlights the use of viscoelastic theory, including nonlinearity with stress and the effects of microstructural change, in the mechanics of ice failure and fracture. The methods of design focus on risk analysis, with emphasis on rational limit-state principles and safety. Full discussion of historical discoveries and modern advances – including Hans Island, Molikpak, and others – support up-to-date methods and models to make this an ideal resource for designers and researchers.

17 - Machine Learning for Turbulence Control
from Part V - Applications
- By B. R. Noack, G. Y. Cornejo Maceda, F. Lusseyran
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 350-367
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12 - Methods for System Identification
from Part IV - Dynamical Systems
- By S. Brunton
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 232-254
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8 - Generalized and Multiscale Modal Analysis
from Part III - Data-Driven Decompositions
- By M.A. Mendez
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 153-181
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13 - Modern Tools for the Stability Analysis of Fluid Flows
from Part IV - Dynamical Systems
- By P. J. Schmid
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 255-284
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15 - Advancing Reacting Flow Simulations with Data-Driven Models
from Part V - Applications
- By K. Zdybal, G. D’Alessio, G. Aversano, M. R. Malik, A. Coussement, J. C. Sutherland, A. Parente
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 304-329
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Preface
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp xiii-xviii
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A Note on the Notation
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

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12 January 2023

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02 February 2023, pp xix-xx
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Part VI - Perspectives
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 391-392
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7 - The Dynamic Mode Decomposition: From Koopman Theory to Applications
from Part III - Data-Driven Decompositions
- By P. J. Schmid
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 133-152
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1 - Analysis, Modeling, and Control of the Cylinder Wake
from Part I - Motivation
- By B. R. Noack, A. Ehlert, C. N. Nayeri, M. Morzynski
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 3-19
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16 - Reduced-Order Modeling for Aerodynamic Applications and Multidisciplinary Design Optimization
from Part V - Applications
- By S. Görtz, P. Bekemeyer, M. Abu-Zurayk, T. Franz, M. Ripepi
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 330-349
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Contributors
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp x-xii
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6 - The Proper Orthogonal Decomposition
from Part III - Data-Driven Decompositions
- By S. Dawson
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 117-132
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Part II - Methods from Signal Processing
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 59-60
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9 - Good Practice and Applications of Data-Driven Modal Analysis
from Part III - Data-Driven Decompositions
- By A. Ianiro
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 182-200
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References
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 409-448
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Contents
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp v-ix
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18 - Deep Reinforcement Learning Applied to Active Flow Control
from Part V - Applications
- By J. Rabault, A. Kuhnle
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 368-390
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Part III - Data-Driven Decompositions
Edited by Miguel A. Mendez, Von Karman Institute for Fluid Dynamics, Belgium, Andrea Ianiro, Universidad Carlos III de Madrid, Bernd R. Noack, Harbin Institute of Technology, China, Steven L. Brunton, University of Washington
Book:

Data-Driven Fluid Mechanics

Published online:

12 January 2023

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02 February 2023, pp 115-116
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Fluid dynamics and solid mechanics

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7932 results in Fluid dynamics and solid mechanics

Mechanics of Ice Failure

17 - Machine Learning for Turbulence Control

12 - Methods for System Identification

8 - Generalized and Multiscale Modal Analysis

13 - Modern Tools for the Stability Analysis of Fluid Flows

15 - Advancing Reacting Flow Simulations with Data-Driven Models

Preface

A Note on the Notation

Part VI - Perspectives

7 - The Dynamic Mode Decomposition: From Koopman Theory to Applications

1 - Analysis, Modeling, and Control of the Cylinder Wake

16 - Reduced-Order Modeling for Aerodynamic Applications and Multidisciplinary Design Optimization

Contributors

6 - The Proper Orthogonal Decomposition

Part II - Methods from Signal Processing

9 - Good Practice and Applications of Data-Driven Modal Analysis

References

Contents

18 - Deep Reinforcement Learning Applied to Active Flow Control

Part III - Data-Driven Decompositions

Fluid dynamics and solid mechanics

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7932 results in Fluid dynamics and solid mechanics

Mechanics of Ice Failure