11629 - 11640 of 20114 Results
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Motion of disc-shaped colloids and pairs of colloidal discs in a nematic liquid crystal
Alena Antipova Western University
PIRSA:14050057Polycrystalline On-Lattice Kinetic Monte Carlo Simulations of Electrodeposition
Nasser Mohiedden Abukhdeir University of Waterloo
PIRSA:14050055Testing Discontinuous Galerkin Methods in the Einstein Toolkit for Numerical Relativity
Jonah Miller Los Alamos National Laboratory
PIRSA:14050045
Tree-Based Cosmological Radiative Transfer
PIRSA:14050052One of the most challenging problems in computational galaxy formation is modeling distant heating and ionization by locally produced radiation. Most Radiative Transfer (RT) techniques are very computationally expensive and limit users to poor resolution or post-processing thus decoupling the radiation from the dynamics of the simulation. We present a new efficient method for RT implemented in the SPH code GASOLINE aimed at full cosmological simulations. The method is tree-based (similar to a gravity solver) scaling as N$_sinklogN_source$ in the optically thin case and as N$_sinklogN_sourcelogN_tot$ in the optically thick case. Applications range from the reionization of the Universe to H$_2$ formation and destruction. First applications focus on FUV and EUV emission from Milky Way-type galaxies and how these affect satellites galaxies.Motion of disc-shaped colloids and pairs of colloidal discs in a nematic liquid crystal
Alena Antipova Western University
PIRSA:14050057In the present work the motion of disc-shaped particles in a nematic liquid crystal was simulated via a Lattice Boltzmann algorithm. Under the action of a rotating magnetic field the colloidal disc with perpendicular surface anchoring immersed in a nematic liquid crystal experiences a torque and continues turning following the field. However when the disc reaches some critical position when the director field around it is highly distorted the disc suddenly flips to minimize the free energy. Analyzing this motion and consequently the behaviour of two discs placed close together we examine the possible uses of this peculiar flip behaviour.A Fourth-Order Solution-Adaptive CENO Scheme for Space-Physics Flows on Three-Dimensional Multi-Block Cubed-Sphere Grids
PIRSA:14050051Accurate efficient and scalable computational methods are highly desirable for large-scale scientific computing applications especially for problems exhibiting spatial and temporal multi-resolution scales non-trivial geometries and complex boundary conditions (BSc). For global magnetohydrodynamics (MHD) modelling of space-physics problemshigh-performance approaches could significantly reduce the grid requirements to achieve targeted solution accuracies thereby enabling more affordable yet accurate predictions of space-plasma flows. Key challenges encountered relate to providing solenoidal magnetic fields accurate discretizations on spherical domains capturing of MHD shocks and implementing accurate BCs. This talk gives an overview of a fourth-order finite-volume discretization procedure in combination with a parallel solution-adaptive algorithm for the computation of MHD space plasmas on cubed-sphere grids. Numerical results to demonstrate the accuracy and capability of the multidimensional high-order solution-adaptive cubed-sphere computational framework are presented.Uses of HPC in radar data processing and analysis
PIRSA:14050056A low troposphere MST type radar located in Costa Rica was used to gather information up to 6 km. With the digital radar technique used thousands of sweeps can be recorded every second. Challenges in processing spectral analysis and radar imaging were addressed with tools provided by HPC.Polycrystalline On-Lattice Kinetic Monte Carlo Simulations of Electrodeposition
Nasser Mohiedden Abukhdeir University of Waterloo
PIRSA:14050055The effects of the microstructure of metal films on device performance and longevity have become increasingly important with the recent advances in nanotechnology. Depending on the application of the metal films and interconnects certain microscopic structures and properties are preferred over others. A common method to produce these films and interconnects is through electrodeposition. As with every process the ability to control the end product requires a detailed understanding of the system and the effect of operating conditions on the resulting product. To address this problem a three-dimensional on-lattice kinetic Monte Carlo (KMC) method is developed to conduct atomistic simulations of polycrystalline metal electrodeposition. The method utilizes the highly descriptive embedded-atom method (EAM) potential to accurately describe the interatomic interaction energy. The EAM potential is a semi-empirical multi-body potential that accounts for the cohesive forces in a metallic system. Its parameters are determined from known experimental data.In the presented study kinetically controlled copper electrodeposition onto polycrystalline copper under potentiostatic conditions is modeled using the aforementioned KMC method. Two plating modes are considered: direct current and pulsed-plating. Three surface processes are considered during electrodeposition: deposition dissolution and surface diffusion. In addition to the surface processes diffusion along grain boundaries is also considered. The KMC method presented in this study is capable of simulating the copper electrodeposition process at the atomic level over long time scales on the order of seconds. The computational requirement of these serial KMC simulations are a fraction (hours versus days) of that required by the parallel molecular dynamics (MD) approach to simulate the same process over the much shorter time scales on the order of nanoseconds. Consequently this KMC method allows for the simulation of electrodeposition processes over time scales that are experimentally-relevant and not feasible using MD.Fast calculation of electro thermo static and elasticity fields in 3D-medium with isolated inclusions using application of Gaussian approximating functions
PIRSA:14050050The problem of calculation of electro and thermo static fields in an infinite homogeneous medium with a heterogeneous isolated inclusion (Kanaun et al) has shown to be reduced to the solution of integral equations for the fields inside the inclusion using Gaussian functions (V. Mazya) for the approximation of the unknown fields. Using this approach coefficients of the matrix of the discretized system will be obtained in closed analytical forms. Only information necessary to carry out the method is the coordinates of the centers of the Gaussian functions (nodes) in the region occupied by the inclusion ie. a mesh-free method. Using a regular grid of nodes the matrix of the discretized problem will have a Teoplitzs structure. Hence Fast Fourier Transform (FFT) technique can be used for the calculation of the matrix-vector products within an iterative solution of the system of linear algebraic equations of the discretized problem. The proposed algorithm is simple fast and does not require much computer memory. In practice this has led to over ten folds reduction in the required computational time and the allocated memory space and enabling consideration of very fine grids not possible with other tried solution methods. Comparisons of the numerical and exact solutions for electrostatic fields inside spherical inclusions with step changing properties are presented here. Second boundary value problem of elasticity for 3D-bodies with cracks is another problem where this approach has been applied successfully. References:S. Kanaun and S. Babaii A numerical method for the solution of thermo and electro static problems for a medium with isolated inclusions Journal of Computational Physics 192 471-493 (2003).V. Mazya Approximate approximation in The Mathematics of Finite Elements and Applications. highlights 1993 edited by J.R. Whitman 77 Wiley Chichester (1994).S. Kanaun A. Markov and S. Babaii An efficient numerical method for the solution of the second boundary value problem of elasticity for 3D- bodies with cracks Int J Fract DOI 10.1007/s10704-013-9885-5Testing Discontinuous Galerkin Methods in the Einstein Toolkit for Numerical Relativity
Jonah Miller Los Alamos National Laboratory
PIRSA:14050045Discontinuous Galerkin finite element (DGFE) methods combine advantages of both finite differences and finite elements approaches. These methods scale extremely well and they have been very successful in computational fluid dynamics. As such we would like to transpose them to the domain of relativistic astrophysics. Recently we have implemented DGFE methods in the Einstein Toolkit a large numerical relativity codebase used by hundreds of scientists around the world. However before DGFE methods can be used in production simulations we must ensure that our implementation is up to the efficiency and accuracy standards of a production codebase. Here we detail our efforts to test our implementation using the Apples with Apples tests (c.f. arXiv:gr-qc/0305023 and arXiv:0709.3559). We briefly introduce DGFE methods explain the Apples with Apples tests and our rationale for using them and discuss results.Predicting New Graphene - Boron Nitride 2D Nano-Materials: Structure Electron Bands Optical Response and Vibrations
PIRSA:14050048The goal of this research is to investigate theoretically the possibility of creating graphene-based semiconducting 2D heterosystems that allow tailoring of the band gap and creating states inside the gap by demand. Such systems are created in our computational experiment by depositing graphene on a layer of hexagonal boron nitride and adding hydrogen on top and bottom of the systems to passivate the dangling bonds and create covalent bonding between the layers of the system of interest. Apart from the atomic structure the thermal stability of the heterosystems their optical and vibrational properties were also studied. In this research four dierent bilayers and their properties are presented.Designing Electroencephalographic (EEG) analysis software with HPC in mind: Focus on a modular submission interface and flexible data annotation
PIRSA:14050044Electroencephalography (EEG) is a method for measuring brain activity by recording electrical fields at the scalp surface. Although it has the highest temporal resolution among brain imaging techniques it has low spatial resolution and is very sensitive to various forms of noise (e.g. movement artifacts electrical sources in the environment impedance artifacts and various biological artifacts typically generated from muscle activation). Substantial progress in the implementation of new signal processing and statistical strategies for EEG data analysis is currently changing the specificity with which EEG researchers can interpret their data. Because EEG studies can produce large data sets (e.g. 100 participants each contributing an EEG recording that consists of 130+ recording channels for 1 hour at a common sampling rate of 500 Hz or 1000 Hz) and the new processing strategies are computationally intensive (e.g. Independen Components Analysis (ICA) and bootstrapping) the computation time involved is not feasible for many research situations. Thus often these advanced methods are not used due to computation limitations even though there is no information based downside to their outcome. In this talk I present two software extensions being developed at the Brock University Lifespan Research Center for integration with the leading open source EEG analysis software platform EEGLab (developed at the Swartz Center for Computational Neuroscience UCSD). The first is a modular interface for submitting unsupervised procedures to a compute cluster and the second is a flexible off line visualization tool that allows for the interactive annotation of extensive unsupervised processing. These software extensions together with resources such as SHARCNet can remove the computation constraints of advanced data processing from EEG research labs.HPC in Quantum Gravity
Sebastian Steinhaus Friedrich Schiller University Jena
PIRSA:14050037Application of numerical simulations to quantum gravity are so far largely neglected yet they possess remarkable potential to learn more about the theory. For approaches that attempt to construct quantum spacetime from fundamental microscopical building blocks e.g. spin foam models the collective behaviour involving many building blocks is unexplored.Therefore we numerically simulate the collective dynamics of many of these building blocks using coarse graining techniques i.e. tensor network renormalization and uncover a rich structure of fixed points with extended phases and phase transitions. Ref.: arXiv:1312.0905 [gr-qc]Biological graph dissimilarity characterization using graph theory
PIRSA:14050043Many biological data sets and relationships can be modeled as graphs. Understanding how structure of these graphs relates to biological function is essential for understanding underlining mechanisms of disease and for aiding drug discoveries. Vertices of biological graphs represent individual entities such as genes and proteins. Edges represent the relationship between two cellular components such as physical and functional interactions. A challenging problem in the post-genomic era is graph comparisons as they are large typed complex and evolving. Comparing graph structures helps to gain insights into the underlying signaling mechanisms and treatments for complex diseases. With technological advancement biological data will continue to grow and so will the size and complexity of graphs.Large graph comparisons are computationally intensive as they involve the subgraph isomorphism problem which is NP-complete. Therefore graph comparison algorithms need to be efficient scalable and be able to systematically capture biologically meaningful graph structure differences. Efficient graph comparison algorithms are necessary for many types of biological graphs e.g. protein-protein interaction drug-target microRNA-gene gene-regulatory and co-expression graphs. Furthermore graph comparison algorithms are extremely useful for many applications such as comparing graphs characterizing different diseases representing different cancer subtypes or different drug treatment responses. There are two main categories of graph properties used for comparing biological graphs global graph properties and local graph properties. Global graph properties study the overall graph while local graph properties focus on local structures of the graph. Our objective is to develop an efficient scalable graph comparison algorithm such that graph structure differences between any two states can be obtained systematically. We achieve the objective in two steps. First we propose an algorithm such that graph structure differences are systematically obtained and verified that the differences are biologically meaningful. Then we develop a heuristic to improve upon the proposed algorithm in the first step in terms of efficiency and scalability. While our approaches are generic we apply it on non-small cell lung cancer data sets. The non-small cell lung cancer datasets are used to construct normal and tumor co-expression graphs. Global graphs properties do not contain the detail needed to capture the structural characteristics of biological graphs thus we used a local property graphlets. Graphlets are all non-isomorphic connected induced graphs on a specific number of vertices. By definition graphlets have the ability to capture all the local structures on a certain number of vertices. Results showed that our graphlet approach returns graph structure differences between normal and tumor conditions that correspond to biological knowledge. We then introduce a heuristic to identify areas that are likely to be different between the normal and tumor graph and perform graph comparisons on the identified areas only. The heuristic was able to achieve interesting results that were successfully validated in vitro.