Isbn: 9781032508856 - artificial intelligence assisted structural optimization (14 risultati)

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  • Lingua: Inglese

    Editore: CRC Press, 2025

    103250885X / 9781032508856

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    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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  • Lingua: Inglese

    Editore: CRC Press, 2025

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

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  • Lingua: Inglese

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    Hardback. Condizione: New. Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials.Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book.The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning.

  • Lingua: Inglese

    Editore: CRC Pr, 2025

    103250885X / 9781032508856

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    Hardcover. Condizione: Brand New. 248 pages. 9.00x6.00x9.00 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor and Francis Ltd, GB, 2025

    103250885X / 9781032508856

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    Hardback. Condizione: New. Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials.Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book.The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning.

  • Lingua: Inglese

    Editore: CRC Press Feb 2025, 2025

    103250885X / 9781032508856

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials.Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book.The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning. 222 pp. Englisch.

  • Lingua: Inglese

    Editore: CRC Press, 2025

    103250885X / 9781032508856

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 281,33

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    Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials.Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book.The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning.