NASA Technical Reports Server (NTRS) 19970012795: Visualization Of Unsteady Computational Fluid Dynamics - Info and Reading Options
By NASA Technical Reports Server (NTRS)
"NASA Technical Reports Server (NTRS) 19970012795: Visualization Of Unsteady Computational Fluid Dynamics" and the language of the book is English.
“NASA Technical Reports Server (NTRS) 19970012795: Visualization Of Unsteady Computational Fluid Dynamics” Metadata:
- Title: ➤ NASA Technical Reports Server (NTRS) 19970012795: Visualization Of Unsteady Computational Fluid Dynamics
- Author: ➤ NASA Technical Reports Server (NTRS)
- Language: English
Edition Identifiers:
- Internet Archive ID: NASA_NTRS_Archive_19970012795
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"NASA Technical Reports Server (NTRS) 19970012795: Visualization Of Unsteady Computational Fluid Dynamics" Description:
The Internet Archive:
The current compute environment that most researchers are using for the calculation of 3D unsteady Computational Fluid Dynamic (CFD) results is a super-computer class machine. The Massively Parallel Processors (MPP's) such as the 160 node IBM SP2 at NAS and clusters of workstations acting as a single MPP (like NAS's SGI Power-Challenge array and the J90 cluster) provide the required computation bandwidth for CFD calculations of transient problems. If we follow the traditional computational analysis steps for CFD (and we wish to construct an interactive visualizer) we need to be aware of the following: (1) Disk space requirements. A single snap-shot must contain at least the values (primitive variables) stored at the appropriate locations within the mesh. For most simple 3D Euler solvers that means 5 floating point words. Navier-Stokes solutions with turbulence models may contain 7 state-variables. (2) Disk speed vs. Computational speeds. The time required to read the complete solution of a saved time frame from disk is now longer than the compute time for a set number of iterations from an explicit solver. Depending, on the hardware and solver an iteration of an implicit code may also take less time than reading the solution from disk. If one examines the performance improvements in the last decade or two, it is easy to see that depending on disk performance (vs. CPU improvement) may not be the best method for enhancing interactivity. (3) Cluster and Parallel Machine I/O problems. Disk access time is much worse within current parallel machines and cluster of workstations that are acting in concert to solve a single problem. In this case we are not trying to read the volume of data, but are running the solver and the solver outputs the solution. These traditional network interfaces must be used for the file system. (4) Numerics of particle traces. Most visualization tools can work upon a single snap shot of the data but some visualization tools for transient problems require dealing with time.
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