Shane Latham

The Lattice Solid Model (LSMearth) is a particle based model similar to the Discrete Element Model (DEM). The current LSMerath includes only radial interaction between two linked particles, involving only translational motions of particles. In this study, we extend the LSM by introducing full rigidity interactions between particles and full degrees of freedom for a single particle. In the new model, for each particle we introduce six degrees of freedom: 3 for translational motion, and 3 for orientation. Six kinds of relative motions are permitted, and six interactions are transferred, i.e., radial, two shearing forces, twisting and two bending torques. Particle motion is decomposed into translational motion of the center of mass and rotation about the center. The former is solved using conventional Molecular Dynamics algorithms. The latter is integrated using Fincham's leap-frog algorithm using quaternion representation of orientations. The relative rotation between two particles is decomposed into two sequence-independent rotations. Using such decomposition, all interactions due to the relative translational and rotational motions between interactive rigid bodies can be uniquely determined. We carried out several tests on 3-D rock failure under uni-axial compression and frictional instability between two blocks. Compared with the simulations without the single particle rotational mechanism, the new simulation results match more closely with experimental results

SUMMARY Public domain total magnetic intensity (TMT) airborne data covcring thc Australian contincnt havc bccn collated into a new database of grids. The cell resolution of each grid is optimal with regard to the original survey flight-linc spacing. Data for all the grids havc bccn matched in one inverse operation by using the statistics of data ditferences in the grid

ABSTRACT We present a simple, robust, and versatile solution to the problem of blurred tomographic images as a result of imperfect geometric hardware alignment. The necessary precision for the alignment between the various components of a tomographic instrument is in many cases technologically difficult to implement, or requires impractical stability. Misaligned projection sets are not self-consistent and give blurred tomographic reconstructions. We have developed an off-line software method that utilises a geometric model to parameterise the alignment, and an algorithm for determining the alignment parameter set that gives the sharpest tomogram. It is an adaptation of passive auto-focus methods that have been used to obtain sharp images in optical instruments for decades. To minimise computation time, the auto-focus strategy is a multi-scale iterative technique implemented on a selection of 2D cross-sections of the tomogram. For each cross-section, the sharpness is evaluated while scanning over various combinations of alignment parameters. The parameter set that maximises sharpness is used to reconstruct the 3D tomogram. To apply the corrections, the projection data are re-mapped, or the reconstruction algorithm is modified. The entire alignment process takes less time than that of a full-scale 3D reconstruction. It can in principle be applied to any cone or parallel beam CT with circular, helical, or more general trajectories. It can also be applied retrospectively to archived projection data without any additional information. This concept is fully tested and implemented for routine use in the ANU micro-CT reconstruction software suite and has made the entire reconstruction pipeline robust and autonomous.

ABSTRACT We present a description of our departments work flow that utilises X-ray micro-tomography in the observation and prediction of physical properties of porous rock. These properties include fluid flow, dissolution/deposition, fracture mapping, and mechanical processes, as well as measurement of three-dimensional (3D) morphological attributes such as pore/grain size and shape distributions, and pore/grain connectivity. To support all these areas there is a need for well integrated and parallel research programs in hardware development, structural description and physical property modelling. Since we have the ability to validate simulation with physical measurement, (and vice versa), an important part of the integration of all these techniques is calibration at every stage of the work flow. For example, we can use high-resolution scanning electron microscopy (SEM) images to verify or improve our sophisticated segmentation algorithm based on image grey-levels and gradients. The SEM can also be used to obtain sub-resolution porosity information estimated from tomographic grey-levels and texture. Comparing experimental and simulated mercury intrusion porosimetry can quantify the effective resolution of tomograms and the accuracy of segmentation. The foundation of our calibration techniques is a robust and highly optimised 3D to 3D image-based registration method. This enables us to compare the tomograms of successively disturbed (e.g., dissolved, fractured, cleaned, ...) specimens with an original undisturbed state. A two-dimensional (2D) to 3D version of this algorithm allows us to register microscope images (both SEM and quantitative electron microscopy) of prepared 2D sections of each specimen. This can assist in giving a multimodal assessment of the specimen.

The contribution of the paper is two-fold: firstly, a review of the point set registration literature is given, and secondly a novel weighted least squares formulation of the point set registration problem is presented. Numerical registration results, produced by registering 3D point correspondence data sets using the weighted least squares approach show improved accuracy over those produced by an unweighted