Adithya challapalli (26 resultados)
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 87,41
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 100,02
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 100,57
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Paperback. Condición: Brand New. 208 pages. 6.00x0.47x9.00 inches. In Stock.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 77,86
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Condición: New. Adithya Challapalli earned an MS at the University of North Texas (UNT) in mechanical and energy engineering and a PhD at Louisiana State University (LSU) in materials engineering, engineering science. Concurrently, he is a project engin.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 104,00
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Taschenbuch. Condición: Neu. 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 machi…ne 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.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 179,00
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 179,73
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Condición: As New. Unread book in perfect condition.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 182,73
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 168,99
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 196,42
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 188,94
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 180,10
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Condición: As New. Unread book in perfect condition.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 185,68
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Condición: New. In.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 193,61
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 206,74
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 215,90
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Condición: New.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 237,80
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Hardcover. Condición: Brand New. 248 pages. 9.00x6.00x9.00 inches. In Stock.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 49,17
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Paperback. Condición: new. Paperback. 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 machin…e 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 48,66
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Paperback. Condición: new. Paperback. 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 machin…e 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 83,33
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Paperback. Condición: new. Paperback. 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 machin…e 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. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 134,45
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Condición: Brand New. New. Delivery takes 20-25 days. Print on Demand.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 148,90
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Buch. Condición: 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 we…ll 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.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 164,81
Envío por EUR 62,40Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: 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.
