12950881
Principal stream surfaces
The use of stream surfaces and streamlines is well established in vector visualization. However, the proper placement of starting points is critical for these constructs to clearly illustrate the flow topology. In this paper, we present the principal stream surface algorithm, which automatically generates stream surfaces that properly depict the topology of an irrotational flow. For each velocity point in the fluid field, we construct the normal to the principal stream surface through the point. The set of all such normal vectors is used to construct the principal stream function, which is a scalar field describing the direction of velocity in the fluid field. Volume rendering can then be used to visualize the principal stream function, which is directly related to the flow topology. Thus, topology in a fluid field can be easily modeled and rendered.
8939699
Rendering of Surface and Volume Details in Volume Data
Aiming at the detail rendering in volume data, a new volume illumination model, called Composed Scattering Model CSM, is presented. In order to enhance different details in volume data, scattering intensity is decomposed into volume scattering intensity and surface scattering intensity with different weight functions. According to the Gauss probability distribution of gray and gradient of data, we propose an accurate method to detect the materials in a voxel, called composed segmentation. In addition, we discuss the principle of constructing these weight functions based on the operators defined in composed segmentation. CSM can generate images containing more details than most popular volume rendering models. This model has been applied to the direct volume rendering of 3D data sets obtained by CT and MRI. The resultant images show not only rich details but also clear boundary surfaces. CSM is demonstrated as an accurate volume rendering model suited for detail enhancement in volume data sets.
36954376
Data Intermixing and Multi-volume Rendering
The main difference between multi-volume rendering and mono-volume rendering is data intermixing. In this paper, we present three levels of data intermixing and their rendering pipelines in direct multi-volume rendering, which discriminate image level intensity intermixing, accumulation level opacity intermixing, and illumination model level parameter intermixing. In the context of radiotherapy treatment planning, different data intermixing methods are applied to three volumes, including CT volume, Dose volume, and Segmentation volume, to compare the features of different data intermixing methods.
8045003
Scalable Line Dynamics in ParaDiS
We describe an innovative highly parallel application program, ParaDiS, which computes the plastic strength of materials by tracing the evolution of dislocation lines over time. We discuss the issues of scaling the code to tens of thousands of processors, and present early scaling results of the code run on a prototype of the BlueGene/L supercomputer being developed by IBM in partnership with the US DOE’s ASC program.
27164222
Superstructure Searching Algorithm for Generic Reaction Retrieval
Chemical reaction knowledge is usually summarized and retrieved by chemists from references, journals, and reaction databases. To rigorously extract chemical reaction knowledge from large data sets, computer algorithms become much more important. This paper presents a new approach, superstructure searching (SSS) algorithm, for generic reaction retrieval. The algorithm considers all known reaction patterns from the targeted structure and assigns synthetic routes for new chemical compounds. This algorithm consists of screening, atom-by-atom comparison, and computation of R-groups' similarity.
27234285
A load management system for running HLA-based distributed simulations over the grid
Running a large-scale distributed simulation may need a large amount of computing resources at geographically different locations. These resources may be from different organizations. The simulation may run for a long period of time and the availability and amount of computing resources available may change during the course of simulation execution. Therefore, coordinating and managing resources for distributed simulation to complete the simulation efficiently and effectively is a critical issue. This paper describes a load management system for HLA-based distributed simulation. The system is constructed on top of a grid computing environment supported by Globus. The overall structure of the system is presented in the paper and how the system saves and restores a federate is also discussed in detail.