A texture-based frameowrk for improving CFD data visualization in a virtual environment

In the field of computational fluid dynamics (CFD) accurate representations of fluid phenomena can be simulated but require large amounts of data to represent the flow domain. Most datasets generated from a CFD simulation can be coarse, {approx} 10,000 nodes or cells, or very fine with node counts on the order of 1,000,000. A typical dataset solution can also contain multiple solutions for each node, pertaining to various properties of the flow at a particular node. Scalar properties such as density, temperature, pressure, and velocity magnitude are properties that are typically calculated and stored in a dataset solution. Solutions are not limited to just scalar properties. Vector quantities, such as velocity, are also often calculated and stored for a CFD simulation. Accessing all of this data efficiently during runtime is a key problem for visualization in an interactive application. Understanding simulation solutions requires a post-processing tool to convert the data into something more meaningful. Ideally, the application would present an interactive visual representation of the numerical data for any dataset that was simulated while maintaining the accuracy of the calculated solution. Most CFD applications currently sacrifice interactivity for accuracy, yielding highly detailed flow descriptions but limiting interaction for investigating the field