Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter

The calibration of discrete element method (DEM) simulations is typically accomplished in a trial-and-error manner. It generally lacks objectivity and is filled with uncertainties. To deal with these issues, the sequential quasi-Monte Carlo (SQMC) filter is employed as a novel approach to calibrating the DEM models of granular materials. Within the sequential Bayesian framework, the posterior probability density functions (PDFs) of micromechanical parameters, conditioned to the experimentally obtained stress–strain behavior of granular soils, are approximated by independent model trajectories. In this work, two different contact laws are employed in DEM simulations and a granular soil specimen is modeled as polydisperse packing using various numbers of spherical grains. Knowing the evolution of physical states of the material, the proposed probabilistic calibration method can recursively update the posterior PDFs in a five-dimensional parameter space based on the Bayes’ rule. Both the identified parameters and posterior PDFs are analyzed to understand the effect of grain configuration and loading conditions. Numerical predictions using parameter sets with the highest posterior probabilities agree well with the experimental results. The advantage of the SQMC filter lies in the estimation of posterior PDFs, from which the robustness of the selected contact laws, the uncertainties of the micromechanical parameters and their interactions are all analyzed. The micro–macro correlations, which are byproducts of the probabilistic calibration, are extracted to provide insights into the multiscale mechanics of dense granular materials.     

Discrete modeling of sand–tire mixture considering grain-scale deformability

Mixing sand or soil with small pieces of tire is common practice in civil engineering applications. Although the properties of the soil are changed, it is environmentally friendly and sometimes economical. Nevertheless, the mechanical behavior of such mixtures is still not fully understood and more numerical investigations are required. This paper presents a novel approach for the modeling of sand–tire mixtures based on the discrete element method. The sand grains are represented by rigid agglomerates whereas the tire grains are represented by deformable agglomerates. The approach considers both grain shape and deformability. The micromechanical parameters of the contact law are calibrated based on experimental results from the literature. The effects of tire content and confining pressure on the stress–strain response are investigated in detail by performing numerical triaxial compression tests. The main results indicate that both strength and stiffness of the samples decrease with increasing tire content. A tire contact of 40% is identified as the boundary between rubber-like and sand-like behavior.     

Enterprise networks: The re-engineering of complex software systems

Today technology design can no longer be understood as a design process on a green site. Design and implementation of new technology are always dependent on existing technology and the way it is used by people. In this respect Software-Engineering has also changed to the characteristics of normal technology design taking into account existing computer systems. Experiences show that the conditions and needs of such Software-Reengineering projects are highly complex and differ in their special characteristics ranging from aspects of quality of existing system documentation to organizational structures of the computer departments concerned. The Task-Artifact Cycle presented here gives a suitable reengineering approach emphasizing both analysis and design in Software-Reengineering.     

Mixtures of (N2)1−x : (O2) x at High Pressures and Low Temperatures

We performed Raman measurements at 18 K and pressures up to 25 GPa in order to construct a tentative phase diagram of the (N ₂)_1–x :(O ₂)_x –system at low temperatures. We varied the composition of the mixed system over the whole concentration range. Here we focused on the systems with high nitrogen concentration and pressures above 2 GPa. It is known that at room temperature oxygen is highly solvable in the –phase of N ₂. The experimental results show that oxygen suppresses the disorder–order transition –N ₂.     

A new Fortran 90 program to compute regular and irregular associated Legendre functions

We present a modern Fortran 90 code to compute the regular and irregular associated Legendre functions for all x∈(−1,+1) (on the cut) and |x|>1 and integer degree (l) and order (m). The code applies either forward or backward recursion in (l) and (m) in the stable direction, starting with analytically known values for forward recursion and considering both a Wronskian based and a modified Miller's method for backward recursion. While some Fortran 77 codes existed for computing the functions off the cut, no Fortran 90 code was available for accurately computing the functions for all real values of x different from x=±1 where the irregular functions are not defined.

Program summary

Program title: Associated Legendre FunctionsCatalogue identifier: AEHE_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHE_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 6722No. of bytes in distributed program, including test data, etc.: 310 210Distribution format: tar.gzProgramming language: Fortran 90Computer: Linux systemsOperating system: LinuxRAM: bytesClassification: 4.7Nature of problem: Compute the regular and irregular associated Legendre functions for integer values of the degree and order and for all real arguments. The computation of the interaction of two electrons, 1/|r₁−r₂|, in prolate spheroidal coordinates is used as one example where these functions are required for all values of the argument and we are able to easily compare the series expansion in associated Legendre functions and the exact value.Solution method: The code evaluates the regular and irregular associated Legendre functions using forward recursion when |x|<1 starting the recursion with the analytically known values of the first two members of the sequence. For values of the argument |x|<1, the upward recursion over the degree for the regular functions is numerically stable. For the irregular functions, backward recursion must be applied and a suitable method of starting the recursion is required. The program has two options; a modified version of Miller's algorithm and the use of the Wronskian relation between the regular and irregular functions, which was the method considered in [1]. Both approaches require the computation of a continued fraction to begin the recursion. The Wronskian method (which can also be described as a modified Miller's method) is a convenient method of computations when both the regular and irregular functions are needed.Running time: The example tests provided take a few seconds to run.References:

• [1] 

  A. Gil, J. Segura, A code to evaluate prolate and oblate spheroidal harmonics, Comput. Phys. Commun. 108 (1998) 267–278.

     

Hierarchical vibrations for part-based recognition of complex objects

We propose a technique for the recognition and segmentation of complex shapes in 2D images using a hierarchy of finite element vibration modes in an evolutionary shape search. The different levels of the shape hierarchy can influence each other, which can be exploited in top-down part-based image analysis. Our method overcomes drawbacks of existing structural approaches, which cannot uniformly encode shape variation and co-variation, or rely on training. We present results demonstrating that by utilizing a quality-of-fit function the model explicitly recognizes missing parts of a complex shape, thus allowing for categorization between shape classes.     

iView: a feature clustering framework for suggesting informative views in volume visualization

The unguided visual exploration of volumetric data can be both a challenging and a time-consuming undertaking. Identifying a set of favorable vantage points at which to start exploratory expeditions can greatly reduce this effort and can also ensure that no important structures are being missed. Recent research efforts have focused on entropy-based viewpoint selection criteria that depend on scalar values describing the structures of interest. In contrast, we propose a viewpoint suggestion pipeline that is based on feature-clustering in high-dimensional space. We use gradient/normal variation as a metric to identify interesting local events and then cluster these via k-means to detect important salient composite features. Next, we compute the maximum possible exposure of these composite feature for different viewpoints and calculate a 2D entropy map parameterized in longitude and latitude to point out promising view orientations. Superimposed onto an interactive track-ball interface, users can then directly use this entropy map to quickly navigate to potentially interesting viewpoints where visibility-based transfer functions can be employed to generate volume renderings that minimize occlusions. To give full exploration freedom to the user, the entropy map is updated on the fly whenever a view has been selected, pointing to new and promising but so far unseen view directions. Alternatively, our system can also use a set-cover optimization algorithm to provide a minimal set of views needed to observe all features. The views so generated could then be saved into a list for further inspection or into a gallery for a summary presentation.     

Natural perspective projections for head-mounted displays

The display units integrated in today's head-mounted displays (HMDs) provide only a limited field of view (FOV) to the virtual world. In order to present an undistorted view to the virtual environment (VE), the perspective projection used to render the VE has to be adjusted to the limitations caused by the HMD characteristics. In particular, the geometric field of view (GFOV), which defines the virtual aperture angle used for rendering of the 3D scene, is set up according to the display field of view (DFOV). A discrepancy between these two fields of view distorts the geometry of the VE in a way that either minifies or magnifies the imagery displayed to the user. It has been shown that this distortion has the potential to affect a user's perception of the virtual space, sense of presence, and performance on visual search tasks. In this paper, we analyze the user's perception of a VE displayed in a HMD, which is rendered with different GFOVs. We introduce a psychophysical calibration method to determine the HMD's actual field of view, which may vary from the nominal values specified by the manufacturer. Furthermore, we conducted two experiments to identify perspective projections for HMDs, which are identified as natural by subjects--even if these perspectives deviate from the perspectives that are inherently defined by the DFOV. In the first experiment, subjects had to adjust the GFOV for a rendered virtual laboratory such that their perception of the virtual replica matched the perception of the real laboratory, which they saw before the virtual one. In the second experiment, we displayed the same virtual laboratory, but restricted the viewing condition in the real world to simulate the limited viewing condition in a HMD environment. We found that subjects evaluate a GFOV as natural when it is larger than the actual DFOV of the HMD--in some cases up to 50 percent--even when subjects viewed the real space with a limited field of view.