9783031475337 - dynamic image analysis of granular materials: particle granulometry for geotechnical, material, and geological applications di iskander, magued; li, linzhu (13 risultati)
Lingua: Inglese
Editore: Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Lingua: Inglese
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Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 372 | Sprache: Englisch | Produktart: Bücher | This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded… soils, and its limitations. DIA is a modern experimental technique used to analyze and classify particulate materials based on their size, shape, and other morphological properties. This method employs a high-frame-rate camera to capture images of individual sand particles, which have been transported and separated using various techniques. DIA generates both particle size and shape information by analyzing thousands to millions of particles, providing a quantitative statistical description of grain size and shape distribution within the specimen. The manuscript also offers a comprehensive examination of 2D and 3D particle size and shape descriptors. It demonstrates that there is no correlation between size and shape parameters in many sands and that shape descriptors can be reduced to four independent parameters representing sand granulometry at different scales. Additionally, the use of DIA in exploring the depositional history of two complex calcareous sands is presented. The manuscript presents the properties of 30 representative sands, including size and shape parameters, and fits them to statistical distributions. The investigated soils encompass both natural and machine-sorted materials, particles with regular and irregular shapes, as well as siliceous and calcareous sands. Physical granulometry of sand particles is compared using 2D, 3D DIA, and micro-computed tomography (¿CT). The work demonstrates that DIA offers significant advantages in terms of efficiency for 3D shape analysis while providing an adequate representation of particle sizes and shapes of most sands. Finally, the manuscript integrates classical geotechnical engineering with computer vision and artificial intelligence. Size and shape descriptors are utilized for sand classification through machine learning models. This work represents a crucial step toward the automatic machine classification of soils, potentially enabling on-site classification using smartphones equipped with high-resolution cameras.
Lingua: Inglese
Editore: Springer International Publishing AG, Cham, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Hardcover. Condizione: new. Hardcover. This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded soils, and its limitations. DIA is a modern experimental techniqu…e used to analyze and classify particulate materials based on their size, shape, and other morphological properties. This method employs a high-frame-rate camera to capture images of individual sand particles, which have been transported and separated using various techniques. DIA generates both particle size and shape information by analyzing thousands to millions of particles, providing a quantitative statistical description of grain size and shape distribution within the specimen. The manuscript also offers a comprehensive examination of 2D and 3D particle size and shape descriptors. It demonstrates that there is no correlation between size and shape parameters in many sands and that shape descriptors can be reduced to four independent parameters representing sand granulometry at different scales. Additionally, the use of DIA in exploring the depositional history of two complex calcareous sands is presented. The manuscript presents the properties of 30 representative sands, including size and shape parameters, and fits them to statistical distributions. The investigated soils encompass both natural and machine-sorted materials, particles with regular and irregular shapes, as well as siliceous and calcareous sands. Physical granulometry of sand particles is compared using 2D, 3D DIA, and micro-computed tomography (mCT). The work demonstrates that DIA offers significant advantages in terms of efficiency for 3D shape analysis while providing an adequate representation of particle sizes and shapes of most sands. Finally, the manuscript integrates classical geotechnical engineering with computer vision and artificial intelligence. Size and shape descriptors are utilized for sand classification through machine learning models. This work represents a crucial step toward the automatic machine classification of soils, potentially enabling on-site classification using smartphones equipped with high-resolution cameras. This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded soils, and its limitations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Condizione: New. 2024th edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer Nature Switzerland, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded soils, and its limitations.…DIA is a modern experimental technique used to analyze and classify particulate materials based on their size, shape, and other morphological properties. This method employs a high-frame-rate camera to capture images of individual sand particles, which have been transported and separated using various techniques. DIA generates both particle size and shape information by analyzing thousands to millions of particles, providing a quantitative statistical description of grain size and shape distribution within the specimen. The manuscript also offers a comprehensive examination of 2D and 3D particle size and shape descriptors. It demonstrates that there is no correlation between size and shape parameters in many sands and that shape descriptors can be reduced to four independent parameters representing sand granulometry at different scales. Additionally, the use of DIA in exploring the depositional history of two complex calcareous sands is presented. The manuscript presents the properties of 30 representative sands, including size and shape parameters, and fits them to statistical distributions. The investigated soils encompass both natural and machine-sorted materials, particles with regular and irregular shapes, as well as siliceous and calcareous sands. Physical granulometry of sand particles is compared using 2D, 3D DIA, and micro-computed tomography (miCT). The work demonstrates that DIA offers significant advantages in terms of efficiency for 3D shape analysis while providing an adequate representation of particle sizes and shapes of most sands. Finally, the manuscript integrates classical geotechnical engineering with computer vision and artificial intelligence. Size and shape descriptors are utilized for sand classification through machine learning models. This work represents a crucial step toward the automatic machine classification of soils, potentially enabling on-site classification using smartphones equipped with high-resolution cameras.
Lingua: Inglese
Editore: Springer Nature, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Hardcover. Condizione: Brand New. 371 pages. 9.26x6.10x9.49 inches. In Stock.
Lingua: Inglese
Editore: Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Hardcover. Condizione: gut. 2024. Dynamic Image Analysis of Granular Materials In deutscher Sprache. pages.
Lingua: Inglese
Editore: Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Switzerland, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers comprehensive coverage of size and shape parameters used for classification of particle granulometryProvides a comprehensive treatment of Dynamic Image Analysis (DIA) technologyPresents step- by- step tutorial… to help readers learn D.
Lingua: Inglese
Editore: Springer, Berlin, Springer Nature Switzerland, Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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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 -This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded soils, and i…ts limitations. DIA is a modern experimental technique used to analyze and classify particulate materials based on their size, shape, and other morphological properties. This method employs a high-frame-rate camera to capture images of individual sand particles, which have been transported and separated using various techniques. DIA generates both particle size and shape information by analyzing thousands to millions of particles, providing a quantitative statistical description of grain size and shape distribution within the specimen. The manuscript also offers a comprehensive examination of 2D and 3D particle size and shape descriptors. It demonstrates that there is no correlation between size and shape parameters in many sands and that shape descriptors can be reduced to four independent parameters representing sand granulometry at different scales. Additionally, the use of DIA in exploring the depositional history of two complex calcareous sands is presented. The manuscript presents the properties of 30 representative sands, including size and shape parameters, and fits them to statistical distributions. The investigated soils encompass both natural and machine-sorted materials, particles with regular and irregular shapes, as well as siliceous and calcareous sands. Physical granulometry of sand particles is compared using 2D, 3D DIA, and micro-computed tomography (miCT). The work demonstrates that DIA offers significant advantages in terms of efficiency for 3D shape analysis while providing an adequate representation of particle sizes and shapes of most sands. Finally, the manuscript integrates classical geotechnical engineering with computer vision and artificial intelligence. Size and shape descriptors are utilized for sand classification through machine learning models. This work represents a crucial step toward the automatic machine classification of soils, potentially enabling on-site classification using smartphones equipped with high-resolution cameras. 345 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Mai 2024, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book explores the effectiveness of Dynamic Image Analysis (DIA) in granulometry studies of sand, and presents criteria for soil characterization using DIA, including test parameters, specimen size, efficacy in gap-graded soils, and its l…imitations. DIA is a modern experimental technique used to analyze and classify particulate materials based on their size, shape, and other morphological properties. This method employs a high-frame-rate camera to capture images of individual sand particles, which have been transported and separated using various techniques.DIA generates both particle size and shape information by analyzing thousands to millions of particles, providing a quantitative statistical description of grain size and shape distribution within the specimen. The manuscript also offers a comprehensive examination of 2D and 3D particle size and shape descriptors. It demonstrates that there is no correlation between size and shape parameters in many sands and that shape descriptors can be reduced to four independent parameters representing sand granulometry at different scales. Additionally, the use of DIA in exploring the depositional history of two complex calcareous sands is presented.The manuscript presents the properties of 30 representative sands, including size and shape parameters, and fits them to statistical distributions. The investigated soils encompass both natural and machine-sorted materials, particles with regular and irregular shapes, as well as siliceous and calcareous sands.Physical granulometry of sand particles is compared using 2D, 3D DIA, and micro-computed tomography (¿CT). The work demonstrates that DIA offers significant advantages in terms of efficiency for 3D shape analysis while providing an adequate representation of particle sizes and shapes of most sands.Finally, the manuscript integrates classical geotechnical engineering with computer vision and artificial intelligence. Size and shape descriptors are utilized for sand classification through machine learning models. This work represents a crucial step toward the automatic machine classification of soils, potentially enabling on-site classification using smartphones equipped with high-resolution cameras.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2024
Serie: Libro 37 di 38 - Springer Series in Geomechanics and Geoengineering
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