(115d) Three-dimensional shape descriptors and tomographic reconstruction techniques for granular materials | AIChE

(115d) Three-dimensional shape descriptors and tomographic reconstruction techniques for granular materials

Authors 

Barrot, D. - Presenter, Rowan University
Corriveau, J. - Presenter, Rowan University
Giordano, P. - Presenter, Rowan University
Mandayam, S. - Presenter, Rowan University
Sukumaran, B. - Presenter, Rowan University


Shear behavior and flow behavior of granular materials have been determined to be dependent on particle morphology. However, quantification of this dependence is a challenging task owing to a dearth of quantitative models for describing particle shape and the difficulty of modeling angular particle assemblies. The situation becomes more complex when discrete element analyses of realistic 3-D particle shapes are required. The paper describes a method whereby shape descriptors for granular particles in three-dimensions can be obtained from two-dimensional images. In addition, the paper also describes a tomographic reconstruction technique for regenerating particles in three-dimensions using two-dimensional shape descriptors. This proves useful for generating realistic shapes for discrete element applications for hopper flow analysis or in obtaining more fundamental understanding of the micromechanics of granular solids. The paper will describe the development and validation of automated image processing algorithms that can estimate three-dimensional shape-descriptors for particle aggregates. It will also demonstrate that a single set of numbers representing a composite three-dimensional shape can be used to characterize all the varying three-dimensional shapes of similar particles in a granular particle mix. The composite shape is obtained by subdividing the problem into a judicious combination of simple techniques ? two-dimensional shape description using Fourier and/or invariant moment descriptors, feature extraction using principal component analysis, statistical modeling and projective reconstruction. Results demonstrating the consistency, separability and uniqueness of the three-dimensional shape descriptor algorithms will be presented. This paper also 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 and synthesize 3-D particle shapes from this database. The particle synthesis algorithm is a powerful technique to regenerate realistic three-dimensional shapes for DEM purposes.

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