nattsr/srbdrp_grainsizedistribution

Codes to measure the grain size distribution from thin sections or µXCT images. The distribution can be calculated based on the sieve method (volume-based), the laser diffraction (frequency-based) method, or the point-count method. The code outputs are (1) grain centroid - a matrix of Cartesian coordinates for each grain, (2) grain radius – a matrix of the radii measured from the grain centroid for each grain, (3) grain azimuth, - a matrix of the azimuth of all principal axes, (4) grain inclination – a matrix of the inclination of all principal axes, (5) grain volume – a vector of the volume in voxels for each grain, and (6) the number of contacts - a vector of the number of adjacent grains in contact.

SRBDRP_GrainSizeDistribution

Codes to measure the grain size distribution from thin sections or µXCT images.

Overview

Grain Size Distribution is one of the basic measurements for sediment classification. The conventional methods for grain size distribution include the sieve method, the laser diffraction method, and the point-count method. We aimed to develop a robust computer code that simulates these conventional methods. The code can measure grain size distribution on 2-D and 3-D binary images using a watershed algorithm to extract out individual grains, and using principal component algorithms to find the principal axes. The outputs include grain radius for different principal axes, grain volume, grain surface area, principal axes inclinations and azimuths, and the number of contacts for each grain. The calculated distribution can be volume-based, frequency-based, or grid-based.

Requirements

MATLAB is required to run the program.

Getting Started

The main function computeGSD.m takes an (nx,ny) or (nx,ny,nz) uint8 matrix, 2-D or 3-D binary image of porespace (1 = grain, 0 = pore). The code outputs are grainCentroid, grainRadius, grainAzimuth, grainInclination, grainVolume, nContact, grainSurfaceArea.

After computing grain properties. The distribution can be computed using computeHistFB.m, computeHistPC.m, or computeHistVB.m. The inputs should be matrix of diameter which is the result from computeGrainDiameter.m.

Published Research Studies using computeGSD.m

The publication is in submission. In the meantime, please make a citation to

Srisutthiyakorn, N. (2018). Computational Analysis of Fluid Flow in 2D&3D Pore Geometry. Ph.D Dissertation. Stanford University. https://searchworks.stanford.edu/view/12684954

srbdrp_grainsizedistribution's Issues

The code do not work

There is no result after calculation.