PARAVIEW HEIGHT ISOVOLUME SKIN

Such events might cause the disconnection of the line, with potentially severe consequences.

Overhead transmission lines are frequently affected by severe climate events such as thunderstorms or heavy snowfalls. Several computing tests are presented in this paper, which verify the stability, efficiency, scalability, and the potential to discover new structure styles of the framework. To realize the combination of distributed memory parallel computing technology and parameterized level set topology optimization using unstructured meshes, several means are taken: (1) the shape functions in finite element analysis are employed to parameterize the level set function (2) the data structure called directed acyclic graph is adopted to represent the unstructured mesh (3) the passive domain and boundary conditions are imposed directly on the geometry entities of the structures (4) a multiple averaging filter is introduced to reduce the tiny structural members in the optimized results for the requirement of manufacturability.

A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes is proposed in this work, in which the full-scale optimization is realized with distributed memory parallel computing technology while the arbitrary geometries and complex boundary conditions are conveniently handled with the usage of unstructured meshes. In addition to the requirements of full-scale optimization, the adaptability to structures with arbitrary geometries and complex boundary conditions is also important to topology optimization in practical engineering applications. ParaView is an open source tool and members of visualization community are invited to add new. In the future, there are number of directions to extend ParaView including the incorporation of data streaming into user interface and rendering support of extremely large datasets for tiled display walls. ParaView provides a graphic user interface for visualizing large datasets using techniques that include data parallelism, level-of-detail and streaming to meet its workflow and large data visualization requirements. This paper presents the design of ParaView, an end-user tool for large data visualization. It is worth noting that climate- specific visualization tools are unable to process datasets of this magnitude. Also a clip plane colored by temperature at a depth of 1140 meters is shown. Isosurfaces and extracted geometry are shown and are used to represent land masses. The 3600x2400x40 structured grid model the earthвЂ™s oceans at 1/10 of a degree resolution. Figure 8 shows the results of a batch script on the results from the Parallel Ocean Program (POP). Both surfaces were colored by mapping the stagnation energy through a default lookup table. Since the actual dataset contains only half the wing due to symmetry, a reflection filter was applied to all surfaces. The delta wing and the contour surface were obtained by extracting sub-grids from the original curvilinear dataset. The streamline filter propagates integration across partition boundaries, and can execute in parallel. This example also shows the 3D line widget used to seed the streamline algorithm. Figure 7 shows streamlines generated by ParaView using a dataset of airflow around a delta wing. ParaView has group and ungroup filters, which simplify processing of multi-block datasets. Since some data sets can have hundreds of blocks, it is important to group these blocks into a single entity that can be filtered in one step.

Each block is configured to get the best resolution sampling for its domain. Many structured data sets divide the domain into blocks. This example also demonstrates ParaView's ability to process multi-block data sets. ParaView was run with 4 server processes in this example.

PARAVIEW HEIGHT ISOVOLUME SKIN

On block of the skin was colored by process id to show the data partitioning. The skin isosurface was clipped in order to reveal the bone isosurface. Two isosurfaces were extracted, one for bone and one for skin. Each section is a uniform rectilinear grid generated by a CT scan. The 512x512x1734 900 MB dataset is composed of seven sections. Figure 6 shows isosurfaces of the visible woman data set.

Paraview height isovolume