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23 records · Page 2

User Directed Tools for Exploiting Expert Knowledge in an Immersive Segmentation and Visualization Environment

Volumetric data sets have become common in medicine and many sciences through technologies such as computed x-ray tomography (CT), magnetic resonance (MR), positron emission tomography (PET), confocal microscopy and 3D ultrasound. When presented with 2D images humans immediately and unconsciously begin a visual analysis of the scene. The viewer surveys the scene identifying significant landmarks and building an internal mental model of presented information. The identification of features is strongly influenced by the viewers expectations based upon their expert knowledge of what the image should contain. While not a conscious activity, the viewer makes a series of choices about how to interpret the scene. These choices occur in parallel with viewing the scene and effectively change the way the viewer sees the image. It is this interaction of viewing and choice which is the basis of many familiar visual illusions. This is especially important in the interpretation of medical images where it is the expert knowledge of the radiologist which interprets the image. For 3D data sets this interaction of view and choice is frustrated because choices must precede the visualization of the data set. It is not possible to visualize the data set with out making some initial choices which determine how the volume of data is presented to the eye. These choices include, view point orientation, region identification, color and opacity assignments. Further compounding the problem is the fact that these visualization choices are defined in terms of computer graphics as opposed to language of the experts knowledge. The long term goal of this project is to develop an environment where the user can interact with volumetric data sets using tools which promote the utilization of expert knowledge by incorporating visualization and choice into a tight computational loop. The tools will support activities involving the segmentation of structures, construction of surface meshes and local filtering of the data set. To conform to this environment tools should have several key attributes. First, they should be only rely on computations over a local neighborhood of the probe position. Second, they should operate iteratively over time converging towards a limit behavior. Third, they should adapt to user input modifying they operational parameters with time.

Senger, Steven O.↗

Adaptive Hybridizable Discontinuous Galerkin discretization of the Grad–Shafranov equation by extension from polygonal subdomains

In this work, we propose a high-order adaptive numerical solver for the semilinear elliptic boundary value problem modeling magnetic plasma equilibrium in axisymmetric confinement devices. In the fixed boundary case, the equation is posed on curved domains with piecewise smooth curved boundaries that may present corners. The solution method we present is based on the hybridizable discontinuous Galerkin method and sidesteps the need for geometry-conforming triangulations thanks to a transfer technique that allows to approximate the solution using only a polygonal subset as computational domain. Moreover, the solver features automatic mesh refinement driven by a residual-based a posteriori error estimator. As the mesh is locally refined, the computational domain is automatically updated in order to always maintain the distance between the actual boundary and the computational boundary of the order of the local mesh diameter. Numerical evidence is presented of the suitability of the estimator as an approximate error measure for physically relevant equilibria with pressure pedestals, internal transport barriers, and current holes on realistic geometries.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A class of hybrid finite element methods for electromagnetics: A review

Integral equation methods have generally been the workhorse for antenna and scattering computations. In the case of antennas, they continue to be the prominent computational approach, but for scattering applications the requirement for large-scale computations has turned researchers' attention to near neighbor methods such as the finite element method, which has low O(N) storage requirements and is readily adaptable in modeling complex geometrical features and material inhomogeneities. In this paper, we review three hybrid finite element methods for simulating composite scatterers, conformal microstrip antennas, and finite periodic arrays. Specifically, we discuss the finite element method and its application to electromagnetic problems when combined with the boundary integral, absorbing boundary conditions, and artificial absorbers for terminating the mesh. Particular attention is given to large-scale simulations, methods, and solvers for achieving low memory requirements and code performance on parallel computing architectures.

Volakis, J. L.↗

MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) [SWR-23-37]

MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) is an open-source computational fluid dynamics package powered by the lattice Boltzmann equations and built on AMReX. In the lattice Boltzmann method, local collisions between meso-scale fictitious particles drive the governing equations which enables MARBLES to easily simulate flow around complex and/or moving geometry without the generation of a body-conforming mesh. Using AMReX data structures and operations ensures a high level of computational performance and parallel scaling on heterogenous architectures while also naturally supporting locally enhanced grid resolution and fidelity through automatic mesh refinement. New domains and problem definitions are easily specified through an input file with examples and guidance on all options and variables provided in the MARBLES documentation.

Henry de Frahan, Marc↗

Uniform Subspace Correction Preconditioners for Discontinuous Galerkin Methods with hp-Refinement

In this paper, we develop subspace correction preconditioners for discontinuous Galerkin (DG) discretizations of elliptic problems with hp-refinement. These preconditioners are based on the decomposition of the DG finite element space into a conforming subspace, and a set of small nonconforming edge spaces. The conforming subspace is preconditioned using a matrix-free low-order refined technique, which in this work, we extend to the hp-refinement context using a variational restriction approach. The condition number of the resulting linear system is independent of the granularity of the mesh h, and the degree of the polynomial approximation p. The method is amenable to use with meshes of any degree of irregularity and arbitrary distribution of polynomial degrees. Furthermore, numerical examples are shown on several test cases involving adaptively and randomly refined meshes, using both the symmetric interior penalty method and the second method of Bassi and Rebay (BR2).

97 MATHEMATICS AND COMPUTING↗