Qingya Shu

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In this paper, we present a novel scalable approach for visualizing multivariate unsteady flow data with Lagrangian-based Attribute Space Projection (LASP). The distances between spatiotemporal samples are evaluated by their attribute values along the advection directions in the flow field. The massive samples are then projected into 2D screen space for(More)
We describe a two-dimensional shallow water model whose initial implementation simulates flows in the San Francisco Bay and Sacramento-San Joaquin Delta. This model, called REALM, is based on a Cartesian grid, embedded boundary discretization of the shallow water equations. We employ parallel computation and adaptive mesh refinement for rapid computation.(More)
This paper presents a novel visual analysis tool, EnsembleGraph, which aims at helping scientists understand spatiotemporal similarities across runs in time-varying ensemble simulation data. We abstract the input data into a graph, where each node represents a region with similar behaviors across runs and nodes in adjacent time frames are linked if their(More)
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