KEYWORDS: Sensors, Visualization, Earthquakes, Data modeling, Data acquisition, 3D modeling, Solid modeling, Visual process modeling, 3D image processing, Buildings
We present a system that visualizes displacement, acceleration, and strain that were measured during an earthquake simulation experiment in a geotechnical centrifuge. Our visualization tool starts by reading the data describing experiment set-up and displaying this data along with icons for the sensors used during data acquisition. Different sensor types (measuring acceleration, displacement and strain) are indicated by different icons. One general experiment set-up is used in a sequence of simulated earthquake events. Once a user has selected a particular event, measured data can be displayed as a two-dimensional (2D) graph/plot by clicking the corresponding sensors. Multiple sensors can be animated to obtain a three-dimensional (3D) visualization of measured data.
The complexity of physical phenomena often varies substantially over space and time. There can be regions where a physical phenomenon/quantity varies very little over a large extent. At the same time, there can be small regions where the same quantity exhibits highly complex variations. Adaptive mesh refinement (AMR) is a technique used in computational fluid dynamics to simulate phenomena with drastically varying scales concerning the complexity of the simulated variables. Using multiple nested grids of different resolutions, AMR combines the topological simplicity of structured-rectilinear grids, permitting efficient computational and storage, with the possibility to adapt grid resolutions in regions of complex behavior. We present methods for direct volume rendering of AMR data. Our methods utilize AMR grids directly for efficiency of the visualization process. We apply a hardware-accelerated rendering method to AMR data supporting interactive manipulation of color-transfer functions and viewing parameters. We also present a cell-projection-based rendering technique for AMR data.
Conference Committee Involvement (1)
Visualization and Data Analysis 2013
4 February 2013 | Burlingame, California, United States
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