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Verlag: Springer International Publishing, 2021
ISBN 10: 3030447200 ISBN 13: 9783030447205
Sprache: Englisch
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ISBN 10: 3030447170 ISBN 13: 9783030447175
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Verlag: Springer Nature Switzerland, 2021
ISBN 10: 3030447200 ISBN 13: 9783030447205
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Data Analysis for Direct Numerical Simulations of Turbulent Combustion | From Equation-Based Analysis to Machine Learning | Antonio Attili (u. a.) | Taschenbuch | ix | Englisch | 2021 | Springer Nature Switzerland | EAN 9783030447205 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Verlag: Springer International Publishing, Springer Nature Switzerland Mai 2021, 2021
ISBN 10: 3030447200 ISBN 13: 9783030447205
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Neuware -This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones.The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 304 pp. Englisch.
Verlag: Springer International Publishing, Springer International Publishing Mai 2020, 2020
ISBN 10: 3030447170 ISBN 13: 9783030447175
Sprache: Englisch
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Buch. Zustand: Neu. Neuware -This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones.The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 304 pp. Englisch.
Verlag: Springer International Publishing, 2021
ISBN 10: 3030447200 ISBN 13: 9783030447205
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences.
Verlag: Springer International Publishing, 2020
ISBN 10: 3030447170 ISBN 13: 9783030447175
Sprache: Englisch
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences.
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Verlag: Springer International Publishing Mai 2021, 2021
ISBN 10: 3030447200 ISBN 13: 9783030447205
Sprache: Englisch
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences. 304 pp. Englisch.
Verlag: Springer International Publishing Mai 2020, 2020
ISBN 10: 3030447170 ISBN 13: 9783030447175
Sprache: Englisch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data.The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics,applied mathematics, and the environmental and atmospheric sciences. 304 pp. Englisch.
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