A GPGPU implementation of the discrete element method applied to modeling the dynamic particulate environment inside a tumbling mill

Includes bibliographical references.Tumbling mills have been an integral part of the comminution circuit for more than a century. With the advent of better computing, discrete element modeling (DEM) has taken on the challenge to model the dynamic particulate environment inside these devices in the search for understanding and hence improving the process of the size reduction of ore. This process represents a large percentage of the energy consumption of a mine. In this work, a discrete element modeling tool was built on a GPU-based platform to perform simulations on a single commodity hardware PC. With a view to elucidating the governing mechanisms inside such devices, the extreme capabilities of the GPU are utilised to provide performance and accurate simulation. The simulation environment offers control that can never be achieved in an experimental setup. Notwithstanding, when agreement with physical experiment is achieved, confidence can be gained in the computational results. In this work the foundations and framework for a large scale GPU based discrete element modeling tool have been built with an emphasis on strict physics requirements, rather than on performance or appearance. In this regard we demonstrate the validity of the GPU implementation of a Hertz-Mindlin-based contact model

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation, and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.Comment: Submitted to 'Systems Medicine' as a book chapte

Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation

In this research, the improved mass spring model is presented to simulate the human liver deformation. The underlying MSM is redesigned where fuzzy knowledge-based approaches are implemented to determine the stiffness values. Results show that fuzzy approaches are in very good agreement to the benchmark model. The novelty of this research is that for liver deformation in particular, no specific contributions in the literature exist reporting on real-time knowledge-based fuzzy MSM for liver deformation

Example Based Caricature Synthesis

The likeness of a caricature to the original face image is an essential and often overlooked part of caricature production. In this paper we present an example based caricature synthesis technique, consisting of shape exaggeration, relationship exaggeration, and optimization for likeness. Rather than relying on a large training set of caricature face pairs, our shape exaggeration step is based on only one or a small number of examples of facial features. The relationship exaggeration step introduces two definitions which facilitate global facial feature synthesis. The first is the T-Shape rule, which describes the relative relationship between the facial elements in an intuitive manner. The second is the so called proportions, which characterizes the facial features in a proportion form. Finally we introduce a similarity metric as the likeness metric based on the Modified Hausdorff Distance (MHD) which allows us to optimize the configuration of facial elements, maximizing likeness while satisfying a number of constraints. The effectiveness of our algorithm is demonstrated with experimental results

Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

A Review on Contact and Collision Methods for Multi-body Hydrodynamic problems in Complex Flows

Modeling and direct numerical simulation of particle-laden flows have a tremendous variety of applications in science and engineering across a vast spectrum of scales from pollution dispersion in the atmosphere, to fluidization in the combustion process, to aerosol deposition in spray medication, along with many others. Due to their strongly nonlinear and multiscale nature, the above complex phenomena still raise a very steep challenge to the most computational methods. In this review, we provide comprehensive coverage of multibody hydrodynamic (MBH) problems focusing on particulate suspensions in complex fluidic systems that have been simulated using hybrid Eulerian-Lagrangian particulate flow models. Among these hybrid models, the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) provides mathematically simple and computationally-efficient algorithms for solid-fluid hydrodynamic interactions in MBH simulations. This paper elaborates on the mathematical framework, applicability, and limitations of various 'simple to complex' representations of close-contact interparticle interactions and collision methods, including short-range inter-particle and particle-wall steric interactions, spring and lubrication forces, normal and oblique collisions, and mesoscale molecular models for deformable particle collisions based on hard-sphere and soft-sphere models in MBH models to simulate settling or flow of nonuniform particles of different geometric shapes and sizes in diverse fluidic systems.Comment: 37 pages, 12 Figure

MODELLING CELL POPULATION GROWTH

The growth of biological matter, e.g., tumor invasion, depends on various factors, mainly the tissue’s mechanical properties, implying elasticity, stiffness, or apparent viscosity. These properties are impacted by the characteristics of the tissue’s extracellular matrix and constituent cells, including, but not limited to, cell membrane stiffness, cell cytoskeleton mechanical properties, and the intensity and distribution of focal adhesions over the cell membrane. To compute and study the mechanical properties of tissues during growth and confluency, a theoretical and computational framework, called CellSim3D, was developed in our group based on a three-dimensional kinetic division model. In this work, CellSim3D is updated with a new set of cell mechanical parameters and force fields such as the asymmetric division rule, shape diversity, apoptosis process, and boundary conditions, e.g., periodic and Lees-Edwards boundary conditions. The package is upgraded to operate on multiple GPUs to further accelerate computations. This enables the inclusion of more complexity in the system. For instance, the simulation of macroscopic scale bicellular tissue growth with precise control over the mechanical properties of cells is now more feasible than before. The effects of cell-cell adhesion strength and intermembrane friction on growth kinetics and interface roughness dynamics of epithelial tissue were studied. It is reported that with fine alterations of the mechanical parameters such as the cell-cell adhesion strength, one could reliably reproduce different interface roughness scaling behaviors such as Kardar–Parisi–Zhang (KPZ)-like and Molecular Beam Epitaxy (MBE)-like scaling. In addition, it was observed that substrate heterogeneity and geometry have significant impacts on the morphology and interface roughness scaling of epithelial tissue. The results suggest that the interface roughness scaling of epithelial tissues cannot be classified by any well-known scaling universality class. Instead, it strongly depends on several other factors, such as the cell-cell adhesion strength. This explains the controversies observed in earlier experimental works over the interface roughness scaling of expanding epithelial tissue

Flexible high performance agent based modelling on graphics card hardware

Agent Based Modelling is a technique for computational simulation of complex interacting systems, through the specification of the behaviour of a number of autonomous individuals acting simultaneously. This is a bottom up approach, in contrast with the top down one of modelling the behaviour of the whole system through dynamic mathematical equations. The focus on individuals is considerably more computationally demanding, but provides a natural and flexible environment for studying systems demonstrating emergent behaviour. Despite the obvious parallelism, traditionally frameworks for Agent Based Modelling fail to exploit this and are often based on highly serialised mobile discrete agents. Such an approach has serious implications, placing stringent limitations on both the scale of models and the speed at which they may be simulated. Serial simulation frameworks are also unable to exploit multiple processor architectures which have become essential in improving overall processing speed. This thesis demonstrates that it is possible to use the parallelism of graphics card hardware as a mechanism for high performance Agent Based Modelling. Such an approach is in contrast with alternative high performance architectures, such as distributed grids and specialist computing clusters, and is considerably more cost effective. The use of consumer hardware makes the techniques described available to a wide range of users, and the use of automatically generated simulation code abstracts the process of mapping algorithms to the specialist hardware. This approach avoids the steep learning curve associated with the graphics card hardware's data parallel architecture, which has previously limited the uptake of this emerging technology. The performance and flexibility of this approach are considered through the use of benchmarking and case studies. The resulting speedup and locality of agent data within the graphics processor also allow real time visualisation of computationally and demanding high population models