Shear behavior and liquefaction susceptibility of geomaterial aggregates have been determined to be dependent on particle shape and angularity. However, quantification of this dependence is a challenging task owing to a dearth of quantitative models for particle shape and the difficulty of modeling angular particle assemblies. The situation becomes more complex when the quantitative models are required to synthesize arbitrary 3-D particle shapes that are representative of specific sand mixtures. The authors have recently described a method for quantitative identification of 3-D particle morphology estimated from projective two-dimensional representations. This paper extends prior work and describes the design and development of an automated three-dimensional particle synthesis algorithm using tomographic reconstruction techniques. A database of 2-D and 3-D images has been generated by optical and X-ray scans of the following sands: #1 Dry Sand, Daytona Beach, Standard Melt, Rhode Island, Hawaii Kahala Beach, Michigan Dune and Hawaii Ala Wai Surfer's Beach. The algebraic reconstruction technique (ART) has been used to characterize 3-D particle shapes from this database. This paper demonstrates the consistency, separability, and uniqueness of the 3-D shape descriptor algorithm as well as its ability to synthesize 3-D particle shapes representative of the respective aggregate mixtures. Copyright ASCE 2006.
|Original language||English (US)|
|Title of host publication||GeoCongress 2006|
|Subtitle of host publication||Geotechnical Engineering in the Information Technology Age|
|Number of pages||1|
|State||Published - Dec 28 2006|
|Event||GeoCongress 2006 - Atlanta, GA, United States|
Duration: Feb 26 2006 → Mar 1 2006
|Name||GeoCongress 2006: Geotechnical Engineering in the Information Technology Age|
|Period||2/26/06 → 3/1/06|
All Science Journal Classification (ASJC) codes
FingerprintDive into the research topics of 'Synthesis of sand particles from 3D shape descriptors using tomographic reconstruction techniques'. Together they form a unique fingerprint.
Shreekanth Mandayam (Manager) & George D. Lecakes (Manager)