Dynamic Image Analysis of Granular Materials Particle Granulometry for Geotechnical, Material, and Geological Applications /
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...
Salvato in:
| Autori principali: | , |
|---|---|
| Ente Autore: | |
| Natura: | Elettronico eBook |
| Lingua: | inglese |
| Pubblicazione: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
|
| Edizione: | 1st ed. 2024. |
| Serie: | Springer Series in Geomechanics and Geoengineering,
|
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-3-031-47534-4 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-47534-4 | ||
| 003 | DE-He213 | ||
| 005 | 20251113180557.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240518s2024 sz | s |||| 0|eng d | ||
| 020 | |a 9783031475344 |9 978-3-031-47534-4 | ||
| 024 | 7 | |a 10.1007/978-3-031-47534-4 |2 doi | |
| 050 | 4 | |a TA703-705.4 | |
| 072 | 7 | |a TNC |2 bicssc | |
| 072 | 7 | |a TEC009150 |2 bisacsh | |
| 072 | 7 | |a TNC |2 thema | |
| 082 | 0 | 4 | |a 624.15 |2 23 |
| 100 | 1 | |a Iskander, Magued. |e author. |0 (orcid)0000-0001-8245-1451 |1 https://orcid.org/0000-0001-8245-1451 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Dynamic Image Analysis of Granular Materials |h [electronic resource] : |b Particle Granulometry for Geotechnical, Material, and Geological Applications / |c by Magued Iskander, Linzhu Li. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a XVIII, 353 p. 287 illus., 258 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Springer Series in Geomechanics and Geoengineering, |x 1866-8763 | |
| 505 | 0 | |a Introduction -- Methods for Determining Particle Granulometry -- Particle Size and Shape Descriptors -- Compendium of Size and Shape Statics of Sand -- Best Practices for Conducting 2D DIA -- Comparison of 2D and 3D DIA -- Comparison of 2D/3D DIA and µCT -- Use of DIA for Tracing the Geologic Origin of Two Marine Calcareous Sands -- DIA for Classification of Soils using Machine Learning and Computer Vision -- Conclusions and Recommendations. | |
| 520 | |a 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 (μCT). 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 650 | 0 | |a Engineering geology. | |
| 650 | 0 | |a Geotechnical engineering. | |
| 650 | 0 | |a Soft condensed matter. | |
| 650 | 0 | |a Signal processing. | |
| 650 | 1 | 4 | |a Geoengineering. |
| 650 | 2 | 4 | |a Geotechnical Engineering and Applied Earth Sciences. |
| 650 | 2 | 4 | |a Soft and Granular Matter. |
| 650 | 2 | 4 | |a Digital and Analog Signal Processing. |
| 700 | 1 | |a Li, Linzhu. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031475337 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031475351 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031475368 |
| 830 | 0 | |a Springer Series in Geomechanics and Geoengineering, |x 1866-8763 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-47534-4 |
| 912 | |a ZDB-2-ENG | ||
| 912 | |a ZDB-2-SXE | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||