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Updated: Jul 13, 2026

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography
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图像处理和神经网络技术用于石颗粒的大小表征

Rana Hassan1, Kennedy C Onyelowe2,3, Amr A Zamel4

  • 1Structural Engineering Department, Faculty of Engineering - Zagazig University, Zagazig, 44519, Egypt. rar.hassan@zu.edu.eg.

Scientific reports
|September 30, 2024
PubMed
概括

本研究介绍了一种高效的图像处理和人工神经网络 (IPNN) 方法,用于估计石颗粒大小分布. IPNN技术为地质技术实践和材料质量控制提供了传统分析的有希望的替代方案.

关键词:
人工智能的人工智能是人工智能.石灰石灰石是什么意思 石灰石图像处理 图像处理神经网络的神经网络颗粒大小 颗粒大小

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Aggregates Classification01:29

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Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...