A study on the influence of the particle packing fraction on the performance of a multilevel contact detection algorithm

We investigate the influence of the packing fraction of highly polydisperse particle systems on the performance of a high-performance multilevel contact detection algorithm as applied for molecular dynamics type simulations. For best performance, this algorithm requires two or more hierarchy levels in order to cope with the strongly different particle size classes. In order to predict the optimal number of levels, an empirical parameter corresponding to the “overhead” is identified. For homogeneous systems, the density is not much affecting the performance of the algorithm, however, the optimal number of levels slightly increases with density as well as the speed-up as compared to a single-level method

Structure characterization of hard sphere packings in amorphous and crystalline states

The channel size distribution in hard sphere systems, based on the local neighbor correlation of four particle positions, is investigated for all volume fractions up to jamming. For each particle, all three particle combinations of neighbors define channels, which are relevant for the concept of caging. The analysis of the channel size distribution is shown to be very useful in distinguishing between gaseous, liquid, partially and fully crystallized, and glassy (random) jammed states. A common microstructural feature of four coplanar particles is observed in crystalline and glassy jammed states, suggesting the presence of "hidden" two-dimensional order in three-dimensional random close packings.Comment: 5 pages, 5 figure

Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization

We introduce a workflow integrating geological modelling uncertainty information to constrain gravity inversions. We test and apply this approach to the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their inferred accuracy as inputs. The uncertainty information is utilized to locally adjust the weights of a minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models reveals that the recovered greenstone belts may be shallower and thinner than previously thought.</p

A review of recent work on the discrete particle method at the University of Twente: an introduction to the open-source package MercuryDPM

In this paper we review some recent advances in DEM (DPM) modelling undertaken at the University of Twente. We introduce the new open-source package MercuryDPM that we have been developing over the last few years.\ud MercuryDPM is an object-oriented program with a simple C++ implementation and includes: support for moving and complex walls, such as polyhedra or screw-threads; state-of-the-art granular contact models; multi-species support; specialised classes, allowing the easy implementation of common geometries like chutes, hoppers, etc.; common handler interfaces for particles, walls and boundaries (so all type of objects are changed using the same interfaces); restarting; large self-test suite and numerous simple demos; and, visualisation support, both internal and using Visual Molecular Dynamics.\ud Additionally to these features, MercuryDPM has two major components that, to the best of our knowledge, cannot be found in other DPM packages. Firstly, it uses a novel advanced contact detection method that is able of dealing with multiple distinct granular components with sizes ranging over many orders of magnitude: the hierarchical grid. We explain how this algorithm works and demonstrate the speedup gained over the traditional linked cell approach. This algorithm has lower complexity for poly-dispersed ows which means for the first time large simulations with extremely wide size distributions are feasible.\ud Secondly, we present a novel way to extract continuum fields from discrete particle systems that is applicable to mixtures as well as boundaries and interfaces. The particle data is coarse grained in a way that is by construction compatible with the continuum equations of mass-, momentum-, and energy balance. Boundary interaction forces are taken into account in a self-consistent way and thus allow the construction of a continuous stress field even within one particle radius of the boundaries. The method does not require temporal averaging and thus can be used to investigate time-dependent flows as well as static and steady situations. This coarse-graining method is available from MercuryDPM either as a post-processing tool or it can be run in real time. In real-time mode, it not only reduces the data which has to be stored but also allows boundary conditions etc. to be updated depending on the current macroscopic state of the system, e.g. allowing the creation of a pressure-release wall.\ud Finally, we illustrate these tools and a selection of other features of MercuryDPM via various problems including size-driven segregation in chute flow, rotating drums, and screw-conveyer

Utilisation of probabilistic magnetotelluric modelling to constrain magnetic data inversion: proof-of-concept and field application

We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterisation of the cover–basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover–basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine these domains with petrophysical information to apply spatially varying, disjoint interval bound constraints (DIBC) to least-squares magnetic data inversion using the alternating direction method of multipliers (or ADMM). We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover–basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement.</p

A study on the influence of the particle packing fraction on the performance of a multilevel contact detection algorithm

We investigate the influence of the packing fraction of highly polydisperse particle systems on the performance of a high-performance multilevel contact detection algorithm as applied for molecular dynamics type simulations. For best performance, this algorithm requires two or more hierarchy levels in order to cope with the strongly different particle size classes. In order to predict the optimal number of levels, an empirical parameter corresponding to the “overhead” is identified. For homogeneous systems, the density is not much affecting the performance of the algorithm, however, the optimal number of levels slightly increases with density as well as the speed-up as compared to a single-level method

A fast multilevel algorithm for contact detection of arbitrarily polydisperse objects

An efficient algorithm for contact detection among many arbitrarily sized objects is developed. Objects are allocated to cells based on their location and size within a nested hierarchical cell space. The choice of optimal cell sizes and the number of hierarchies for best performance is not trivial in most cases. To overcome this challenge, a novel analytical method to determine the optimal hierarchical cell space for a given object size distribution is presented. With this, a decision can be made between using the classical Linked-Cell method and the contact detection algorithm presented. For polydisperse systems with size ratios up to 50, we achieved 220 times speed-up compared to the classical Linked-Cell method. For larger size ratios, even better speed-up is expected. The complexity of the algorithm is linear with the number of objects when the optimal hierarchical cell space is chosen. So that the problem of contact detection in polydisperse systems essentially is solved

Equation of state and jamming density for equivalent bi- and polydisperse, smooth, hard sphere systems.

We study bi- and polydisperse mixtures of hard sphere fluids with extreme size ratios up to 100. Simulation results are compared with previously found analytical equations of state by looking at the compressibility factor, Z, and agreement is found with much better than 1% deviation in the fluid regime. A slightly improved empirical correction to Z is proposed. When the density is further increased, excluded volume becomes important, but there is still a close relationship between many-component mixtures and their binary, two-component equivalents (which are defined on basis of the first three moments of the size distribution). Furthermore, we determine the size ratios for which the liquid-solid transition exhibits crystalline, amorphous or mixed system structure. Near the jamming density, Z is independent of the size distribution and follows a −1 power law as function of the difference from the jamming density (Z → ∞). In this limit, Z depends only on one free parameter, the jamming density itself, as reported for several different size distributions with a wide range of widths