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Synopsis
Local and integral (corrective, correcting Abramovich-Sekundov and Spalart-Allmaras models) neural network models of turbulent viscosity are proposed, showing intermediate accuracy results between one-parameter and two-parameter models. A new algorithm for controlling the numerical calculation error in some typical problems of aerodynamics has been proposed. Its effectiveness on a number of problems is shown. The algorithm is based on the application of particle indicators and uses the particle-in-cell method. The principles of data compression, representing physical quantities varying depending on some parameter, by constructing cluster-neural network descriptions, are proposed.
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- PublisherOur Knowledge Publishing
- Publication date2022
- ISBN 10 6205434717
- ISBN 13 9786205434710
- BindingPaperback
- LanguageEnglish
- Number of pages52
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Neural networks in air turbulence modelling: Correction models
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Our Knowledge Publishing, 2022
ISBN 10: 6205434717
ISBN 13: 9786205434710
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Neural networks in air turbulence modelling
Published by
Our Knowledge Publishing Dez 2022, 2022
ISBN 10: 6205434717
ISBN 13: 9786205434710
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Local and integral (corrective, correcting Abramovich-Sekundov and Spalart-Allmaras models) neural network models of turbulent viscosity are proposed, showing intermediate accuracy results between one-parameter and two-parameter models. A new algorithm for controlling the numerical calculation error in some typical problems of aerodynamics has been proposed. Its effectiveness on a number of problems is shown. The algorithm is based on the application of particle indicators and uses the particle-in-cell method. The principles of data compression, representing physical quantities varying depending on some parameter, by constructing cluster-neural network descriptions, are proposed. 52 pp. Englisch. Seller Inventory # 9786205434710
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Neural networks in air turbulence modelling: Correction models
Published by
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ISBN 10: 6205434717
ISBN 13: 9786205434710
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Neural networks in air turbulence modelling: Correction models
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ISBN 10: 6205434717
ISBN 13: 9786205434710
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Neural networks in air turbulence modelling : Correction models
Published by
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ISBN 10: 6205434717
ISBN 13: 9786205434710
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Local and integral (corrective, correcting Abramovich-Sekundov and Spalart-Allmaras models) neural network models of turbulent viscosity are proposed, showing intermediate accuracy results between one-parameter and two-parameter models. A new algorithm for controlling the numerical calculation error in some typical problems of aerodynamics has been proposed. Its effectiveness on a number of problems is shown. The algorithm is based on the application of particle indicators and uses the particle-in-cell method. The principles of data compression, representing physical quantities varying depending on some parameter, by constructing cluster-neural network descriptions, are proposed. Seller Inventory # 9786205434710
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Neural networks in air turbulence modelling
Published by
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ISBN 10: 6205434717
ISBN 13: 9786205434710
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Pekunov VladimirVladimir Viktorovich Pekunov was born on 21 January 1977 in Zapolyarny. Graduated from Ivanovo State Power Engineering University. Doctor of Technical Sciences, author of more than 85 scientific works. Main research i. Seller Inventory # 774154273
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Neural networks in air turbulence modelling
Published by
Our Knowledge Publishing Dez 2022, 2022
ISBN 10: 6205434717
ISBN 13: 9786205434710
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Taschenbuch
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Taschenbuch. Condition: Neu. Neuware -Local and integral (corrective, correcting Abramovich-Sekundov and Spalart-Allmaras models) neural network models of turbulent viscosity are proposed, showing intermediate accuracy results between one-parameter and two-parameter models. A new algorithm for controlling the numerical calculation error in some typical problems of aerodynamics has been proposed. Its effectiveness on a number of problems is shown. The algorithm is based on the application of particle indicators and uses the particle-in-cell method. The principles of data compression, representing physical quantities varying depending on some parameter, by constructing cluster-neural network descriptions, are proposed.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. Seller Inventory # 9786205434710
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