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The past few years have seen a rapid growth in the development and exploitation of X-ray diffraction on ultrafast time-scales. One area of physics which has benefited particularly from these advances is the the field of shock-waves. Whilst it has been known for many years that crystalline matter, subjected to uniaxial shock compression, can undergo plastic deformation and, for certain materials, polymorphic phase transformations, it has hitherto not been possible to observe the rearrangement of the atoms on the pertinent timescales. We have used laser-plasma generated X-rays to study how single crystals of metals (copper and iron) react to uniaxial shock compression, and observed rapid plastic flow (in the case of copper), and directly observed the famous alpha-epsilon transition in Iron. These studies have been complemented by large-scale multi-million atom molecular dynamics simulations, yielding significant information on the underlying physics.© (2006) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The key to perfect radiation endurance is perfect recovery. Since surfaces are perfect sinks for defects, a porous material with a high surface to volume ratio has the potential to be extremely radiation tolerant, provided it is morphologically stable in a radiation environment. Experiments and computer simulations on nanoscale gold foams reported here show the existence of a window in the parameter space where foams are radiation tolerant. We analyze these results in terms of a model for the irradiation response that quantitatively locates such window that appears to be the consequence of the combined effect of two length scales dependent on the irradiation conditions: (i) foams with ligament diameters below a minimum value display ligament melting and breaking, together with compaction increasing with dose (this value is typically ∼5 nm for primary knock on atoms (PKA) of ∼15 keV in Au), while (ii) foams with ligament diameters above a maximum value show bulk behavior, that is, damage accumulation (few hundred nanometers for the PKA's energy and dose rate used in this study). In between these dimensions, (i.e., ∼100 nm in Au), defect migration to the ligament surface happens faster than the time between cascades, ensuring radiation resistance for a given dose-rate. We conclude that foams can be tailored to become radiation tolerant. Fil: Bringa, Eduardo Marcial. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina Fil: Monk, J. D.. Louisiana State University. Cain Department of Chemical Engineering; Estados Unidos Fil: Caro, A.. Los Alamos National Laboratory; Estados Unidos Fil: Misra, A.. Los Alamos National Laboratory; Estados Unidos Fil: Zepada Ruiz, L.. Lawrence Livermore National Laboratory; Estados Unidos Fil: Duchaineau, M.. Lawrence Livermore National Laboratory; Estados Unidos Fil: Abraham, F.. Lawrence Livermore National Laboratory; Estados Unidos Fil: Nastasi, M.. Los Alamos National Laboratory; Estados Unidos Fil: Picraux, S.T.. Los Alamos National Laboratory; Estados Unidos Fil: Wang, Y.Q.. Los Alamos National Laboratory; Estados Unidos Fil: Farkas, D.. Virginia Tech. Department of Materials Sciences; Estados Unidos

We present a dimension reduction and feature extraction method for the visualization and analysis of function field data. Function fields are a class of high-dimensional, multi-variate data in which data samples are onedimensional scalar functions. Our approach focuses upon the creation of high-dimensional range-space segmentations, from which we can generate meaningful visualizations and extract separating surfaces between features. We demonstrate our approach on high-dimensional spectral imagery, and particulate pollution data from air quality simulations.

Material interface reconstruction (MIR) is the task of constructing boundary interfaces between regions of homogeneous material, while satisfying volume constraints, over a structured or unstructured spatial domain. In this paper, we present a discrete approach to MIR based upon optimizing the labeling of fractional volume elements within a discretization of the problem's original domain. We detail how to construct and initially label a discretization, and introduce a volume conservative swap move for optimization. Furthermore, we discuss methods for extracting and visualizing material interfaces from the discretization. Our technique has significant advantages over previous methods: we produce interfaces between multiple materials that are continuous across cell boundaries for time-varying and static data in arbitrary dimension with bounded error.

This paper presents a new, automated image- and feature-based pipeline of analysis algorithms to elucidate and quantify a discovery regarding supersonic cracks made using large-scale molecular dynamics computations. The first computational confirmation of supersonic cracks was made in recent years, along with the discovery of a two-step, discrete process of increasing crack velocity through the nucleation of a transonic daughter crack and the later nucleation of a supersonic granddaughter crack. This discovery was facilitated by the work presented here. The algorithm pipeline includes modeling, recognition and motion analysis of both the front most crack tips and the more subtle secondary wavefronts from the slower ancestor cracks. The algorithms employed include line extraction from Canny edge maps, feature modeling based on physical properties, and subsequent tracking of primary and secondary wavefronts. The model embeds anticipated propagation properties (physics-based framework) and adapts to changes in the data for unexpected aspects (data-driven modeling). This process is completely automated; it runs in real time on three different 834-frame sequences using 40 250MHz processors. Results supporting the discovery of the two-step transition to supersonic crack propagation in bilayer materials are presented in terms of both feature tracking and velocity analysis.

The real-time display of huge geometry and imagery databases involves view-dependent approximations, typically through the use of precomputed hierarchies that are selectively refined at runtime. A classic motivating problem is terrain visualization in which planetary databases involving billions of elevation and color values are displayed on PC graphics hardware at high frame rates. This paper introduces a new diamond data structure for the basic selective-refinement processing, which is a streamlined method of representing the well-known hierarchies of right triangles that have enjoyed much success in real-time, view-dependent terrain display. Regular-grid tiles are proposed as the payload data per diamond for both geometry and texture. The use of 4-8 grid refinement and coarsening schemes allows level-of-detail transitions that are twice as gradual as traditional quadtree-based hierarchies, as well as very high-quality low-pass filtering compared to subsampling-based hierarchies. An out-of-core storage organization is introduced based on Sierpinski indices per diamond, along with a tile preprocessing framework based on fine-to-coarse, same-level, and coarse-to-fine gathering operations. To attain optimal frame-to-frame coherence and processing-order priorities, dual split and merge queues are developed similar to the Realtime Optimally Adapting Meshes (ROAM) Algorithm, as well as an adaptation of the ROAM frustum culling technique. Example applications of lake-detection and procedural terrain generation demonstrate the flexibility of the tile processing framework.

We analyze a large-scale molecular dynamics simulation of work hardening in a model system of a ductile solid. With tensile loading, we observe emission of thousands of dislocations from two sharp cracks. The dislocations interact in a complex way, revealing three fundamental mechanisms of work-hardening in this ductile material. These are (1) dislocation cutting processes, jog formation and generation of trails of point defects; (2) activation of secondary slip systems by Frank-Read and cross-slip mechanisms; and (3) formation of sessile dislocations such as Lomer-Cottrell locks. We report the discovery of a new class of point defects referred to as trail of partial point defects, which could play an important role in situations when partial dislocations dominate plasticity. Another important result of the present work is the rediscovery of the Fleischer-mechanism of cross-slip of partial dislocations that was theoretically proposed more than 50 years ago, and is now, for the first time, confirmed by atomistic simulation. On the typical time scale of molecular dynamics simulations, the dislocations self-organize into a complex sessile defect topology. Our analysis illustrates numerous mechanisms formerly only conjectured in textbooks and observed indirectly in experiments. It is the first time that such a rich set of fundamental phenomena have been revealed in a single computer simulation, and its dynamical evolution has been studied. The present study exemplifies the simulation and analysis of the complex nonlinear dynamics of a many-particle system during failure using ultra-large scale computing.

Large scale atomic simulations are becoming an increasingly important tool in modeling deformation and failure mechanisms of materials. Here we describe and analyze a recent one-billion-atom simulation of ductile materials failure [PNAS 99 (9) (2002) 5783] where the complexity of creation and collective behavior of thousands of dislocations are revealed, for the first time, from atomic to submicron length scales. The amount of information that can be extracted from such large-scale simulations is truly overwhelming, and graphic visualization of dynamic dislocation motion and interactions are breathtaking. We present some of our preliminary analysis of the one-billion-atom simulation which indicates several interesting and unique features characterizing interactions among a large number of dislocations. A sessile defect structure is observed to develop on the time scale of several picoseconds, effectively locking further dislocation motion and causing the material to work harden. We make analysis of the activated slip systems, the dislocation reactions leading to rigid junctions and the formation of sessile defect structure. In order to render the present study more comprehensive to the readers from a continuum plasticity background and stimulate further interests in this area of research, we also include some brief reviews of some of the previous studies as well as commonly used simulation, visualization and analysis techniques on atomistic modeling of dislocation plasticity. Finally, we discuss possible ways to link continuum mechanics theories of plasticity with atomistic simulation results via the dislocation density tensor.

Multiresolution methods are a common technique used for dealing with large-scale data and representing it at multiple levels of detail. We present a multiresolution hierarchy construction based on n√2 subdivision, which has all the advantages of a regular data organization scheme while reducing the drawback of coarse granularity. The n√2-subdivision scheme only doubles the number of vertices in each subdivision step regardless of dimension n. We describe the construction of 2D, 3D, and 4D hierarchies representing surfaces, volume data, and time-varying volume data, respectively. The 4D approach supports spatial and temporal scalability. For high-quality data approximation on each level of detail, we use downsampling filters based on n-variate B-spline wavelets. We present a B-spline wavelet lifting scheme for n√2-subdivision steps to obtain small or narrow filters. Narrow filters support adaptive refinement and out-of-core data exploration techniques.

This paper presents an algorithm for material interface reconstruction for data sets where fractional material information is given as a percentage for each element of the underlying grid. The reconstruction problem is transformed to a problem that analyzes a dual grid, where each vertex in the dual grid has an associated barycentric coordinate tuple that represents the fraction of each material present. Material boundaries are constructed by analyzing the barycentric coordinate tuples of a tetrahedron in material space and calculating intersections with Voronoi cells that represent the regions where one material dominates. These intersections are used to calculate intersections in the Euclidean coordinates of the tetrahedron. By triangulating these intersection points one creates the material boundary. The algorithm can treat data sets containing any number of materials. The algorithm can also create non-manifold boundary surfaces if necessary. By clipping the generated material boundaries against the original cells, one can examine the error in the algorithm. Error analysis shows that the algorithm preserves volume fractions within an error range of 0.5% per material.

Author(s): Pinskiy, Dimitriy V.; Meyer, Joerg; Hamann, Bernd; Joy, Ken; Brugger, Eric S.; Duchaineau, Mark A. | Abstract: We present an octree-based approach supporting multiresolution visualization of large three-dimenstional scientific data sets. Given an irregular gridded data set, we initially impose an octree data structure of relatively low resolution, i.e., consisting of a relatively small number of cells. The construction of this initial octree structure is controlled by the original data resolution and cell-specific error value. It is thus possible to use the octree to visualize either the field function value or the local error value. The octreee data structure can be refined further in areas that are specified by a user of a visualization system: A user would identify a region in space, i.e., an octree cell, where the field is of greater interest or where octree cells carry relatively large error values. This usage of our data sturcture ensures that we use the highest resolution to render only regions of interest in a large-scale scientific data set.

In this paper we present a method for interactive high-quality visualization of large and time-varying 3D unstructured data from particle simulations.

This paper presents a novel method for multi-view sequential scene reconstruction scenarios such as in aerial video, that exploits the constraints imposed by the path of a moving camera to allow for a new way of detecting and correcting inaccuracies in the feature tracking and structure computation processes. The main contribution of this paper is to show that for short, planar segments of a continuous camera trajectory, parallax movement corresponding to a viewed scene point should ideally form a scaled and translated version of this trajectory when projected onto a parallel plane. This creates two constraints, which differ from those of standard factorization, that allow for the detection and correction of inaccurate feature tracks and to improve scene structure. Results are shown for real and synthetic aerial video and turntable sequences, where the proposed method was shown to correct outlier tracks, detect and correct tracking drift, and allow for a novel improvement of scene structure, additionally resulting in an improved convergence for bundle adjustment optimization.

Blossoming has proven to be a useful technique for understanding and generalizing polynomial curves through the use of the polar form. This paper shows that general polar values may be used to control polynomial curves when a related matrix is invertible. The inverse matrix provides a useful translation from these general blossom control points to well known ones such as those of Bezier. The special case in which the polar form can be evaluated through pairwise affine combinations is characterized, allowing the arguments of the blossom control points to be chosen in a manner akin to choosing the knot vector of a B-spline segment. The number of free parameters for specifying the blossom control points of polynomial curves is increased significantly over the B-spline case.

Recent work on multi-object tracking has shown the promise of tracklet-based methods. In this work we present a method which infers tracklets then groups them into tracks. It overcomes some of the disadvantages of existing methods, such as the use of heuristics or non-realistic constraints. The main idea is to formulate the data association problem as inference in a set of Bayesian networks. This avoids exhaustive evaluation of data association hypotheses, provides a confidence estimate of the solution, and handles split-merge observations. Consistency of motion and appearance is the driving force behind finding the MAP data association estimate. The computed tracklets are then used in a complete multi-object tracking algorithm, which is evaluated on a vehicle tracking task in an aerial surveillance context. Very good performance is achieved on challenging video sequences. Track fragmentation is nearly non-existent, and false alarm rates are low.

An algorithm that shows how ray divergence in multi-view stereo scene reconstruction can be used towards improving bundle adjustment weighting and conditioning is presented. Starting with a set of feature tracks, ray divergence when attempting to compute scene structure for each track is first obtained. Assuming accurate feature matching, ray divergence reveals mainly camera parameter estimation inaccuracies. Due to its smooth variation across neighboring feature tracks, from its histogram a set of weights can be computed that can be used in bundle adjustment to improve its convergence properties. It is proven that this novel weighting scheme results in lower reprojection errors and faster processing times than others such as image feature covariances, making it very suitable in general for applications involving multi-view pose and structure estimation.

This paper introduces a non-parametric sequential frame decimation algorithm for image sequences in low-memory streaming environments. Frame decimation reduces the number of input frames to increase pose and structure robustness in Structure and Motion (SaM) applications. The main contribution of this paper is the introduction of a sequential low-memory work-flow for frame decimation in embedded systems where memory and memory traffic come at a premium. This approach acts as an online preprocessing filter by removing frames that are ill-posed for reconstruction before streaming. The introduced sequential approach reduces the number of needed frames in memory to three in contrast to global frame decimation approaches that use at least ten frames in memory and is therefore suitable for low-memory streaming environments. This is moreover important in emerging systems with large format cameras which acquire data over several hours and therefore render global approaches impossible. In this paper a new decimation metric is designed which facilitates sequential keyframe extraction fit for reconstruction purposes, based on factors such as a correspondence-to-feature ratio and residual error relationships between epipolar geometry and homography estimation. The specific design of the error metric allows a local sequential decimation metric evaluation and can therefore be used on the fly. The approach has been tested with various types of input sequences and results in reliable low-memory frame decimation robust to different frame sampling frequencies and independent of any thresholds, scene assumptions or global frame analysis.

A new material interface reconstruction method for volume fraction data is presented. Our method is comprised of two components: first, we generate initial interface topology; then, using a combination of smoothing and volumetric forces within an active interface model, we iteratively transform the initial material interfaces into high-quality surfaces that accurately approximate the problem's volume fractions. Unlike all previous work, our new method produces material interfaces that are smooth, continuous across cell boundaries, and segment cells into regions with proper volume. These properties are critical during visualization and analysis. Generating high-quality mesh representations of material interfaces is required for accurate calculations of interface statistics, and dramatically increases the utility of material boundary visualizations.