About the Computational Science and Engineering Book Series Cover

 

Cover images from left to right:


This image is one of a series of images that depict a complete end-to-end simulation run by the University of Utah's Center for the Simulation of Accidental Fires and Explosions (C-SAFE). Visualized is a sectional view of the rupturing of a steel container that is filled with a plastic bonded explosive and heated by a fire. The structural response of the container and the solid explosive is modeled using the Material Point Method (MPM). The fire and products of reaction of the explosive are modeled using a multi-material version of the Implicit Compressible Eulerian (ICE) CFD algorithm. This highly coupled multi- physics integrated simulation consists of three phases, all run by a single program. The first phase is the simulation of the fire, which runs for a period of time sufficient to compute a spatially resolved, time-averaged rate of heat transfer to the container.

Using this heat transfer rate, the simulation switches to the second phase (the heat-up phase). During the heat-up phase, the heat generated by the fire is absorbed by the container and transferred to the explosive. This phase of the simulation lasts on the order of tens of minutes. When the explosive temperature reaches approximately 450 degrees Kelvin, it begins to react, rapidly pressurizing the container. At this point, the simulation switches to the third phase (the explosion phase). The explosion phase lasts several milliseconds. The simulation terminates when fragments of the cylinder escape the computational domain. The final result of the simulation, as depicted here, was calculated using 146 hours of computation time on 600 processors utilizing both the ALC and Thunder computers at Lawrence Livermore National Laboratory. The data from 200 time steps of this simulation, including the 2.8 million particles per time step, was visualized interactively using the Real Time Ray Tracer (RTRT) on 60 processors of an SGI Origin 3800. The particles are colored based on temperature; particle size corresponds to particle mass.

Visualization created by the Scientific Computing and Imaging (SCI) Institute, University of Utah.


The image is an illustration of the intricate topology of a vortex breakdown bubble in a delta wing simulation. High-quality stream surfaces with adaptive resolution are shown in red and green, corresponding to the separation surfaces of two saddle points that determine the boundary of the bubble. This is demonstrated by an additional closed stream surface surrounding the vortex core and integrated from the tip of the wing that wraps the whole structure.

Visualization created by the Scientific Computing and Imaging (SCI) Institute, University of Utah.

 

This is a multi-field visualization of the Argon bubble dataset. Two scalar fields are visualized using volume rendering and the horizontal cut plane, as well as two vector fields visualized using stream tubes and arrow glyphs in the vertical cut plane. Dataset provided courtesy of J. Bell and V. Beckner, Center for Computational Sciences and Engineering, Lawrence Berkeley National Laboratory.

Visualization created by the Scientific Computing and Imaging (SCI) Institute, University of Utah.

 

This is a volume visualization from a weather simulation. The reverse image is used on the cover. The images were created from a condensed water field 1008 km x 1008 km x 300 km. The data is courtesy of David E. Stevens (LLNL), Andrew S. Ackerman (NASA AMES), and Christopher S. Bretherton (UW, Seattle), DOE-OSTI Report No. UCRL-JC-145931, “Effects of Domain Size and Numerical Resolution on the Simulation of Shallow Cumulus Convection.”

Visualization created by the Scientific Computing and Imaging (SCI) Institute, University of Utah.

 

The image is a snapshot of seismic wave intensity from a simulation of the 1994 Northridge earthquake in the Los Angeles Basin.

Researchers involved in creating the image: J. Bielak, D. O'Hallaron, L. Ramirez-Guzman, and T. Tu, Carnegie Mellon University; O. Ghattas, University of Texas at Austin; K. Ma and H. Yu, University of California, Davis.

 

The image is a visualization of areas of neural activation from an inverse magnetoencelphalography (MEG) source localization simulation. A cut-away of the patient's head is shown along with cutting planes of the MRI of the patient's brain showing the recovered areas of activation volume rendered in yellow. The blue triangles represent the locations of the MEG sensors.

Visualization created by the Scientific Computing and Imaging (SCI) Institute, University of Utah.

 



The image on the book’s spine is one in a series of images that show animations of two vortices merging. The colors show vorticity; red is high positive vorticity and blue is zero vorticity. If two vortices of the same sign are near each other, they will rotate around each other. Close vortices, like those shown, will merge into one.

The animations were produced by a pseudo-spectral model of the
quasi-geostrophic potential vorticity equation (QG). QG, first derived by Charney in 1948, is a reduced model for stratified, rotating flows which is often employed in atmospheric and ocean dynamics. QG has been successful in analytic models of Rossby waves, cyclogenesis, and ocean basin circulation, as well as fundamental numerical models. This model was used to study a "Slanted QG" regime, which is pertinent to low-latitude dynamics.

These images show 2D slices of the full 3D model. For a single 2D layer, QG is identical to the 2D vorticity equation.

A portion of the series of images also appears on the front of the Computational Science and Engineering book series brochure.

Visualization created by Mark R. Petersen, Los Alamos National Laboratory.

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