Exploring 4D Flow Data in an Immersive Virtual Environment

Ocean models help us to understand and predict a wide range of intricate physical processes which comprise the atmospheric and oceanic systems of the Earth. Because these models output an abundance of complex time-varying three-dimensional (i.e., 4D) data, effectively conveying the myriad information from a given model poses a significant visualization challenge. The majority of the research effort into this problem has concentrated around synthesizing and examining methods for representing the data itself; by comparison, relatively few studies have looked into the potential merits of various viewing conditions and virtual environments. We seek to improve our understanding of the benefits offered by current consumer-grade virtual reality (VR) systems through an immersive, interactive 4D flow visualization system. Our dataset is a Regional Ocean Modeling System (ROMS) model representing a 12-hour tidal cycle of the currents within New Hampshire's Great Bay estuary. The model data was loaded into a custom VR particle system application using the OpenVR software library and the HTC Vive hardware, which tracks a headset and two six-degree-of-freedom (6DOF) controllers within a 5m-by-5m area. The resulting visualization system allows the user to coexist in the same virtual space as the data, enabling rapid and intuitive analysis of the flow model through natural interactions with the dataset and within the virtual environment. Whereas a traditional computer screen typically requires the user to reposition a virtual camera in the scene to obtain the desired view of the data, in virtual reality the user can simply move their head to the desired viewpoint, completely eliminating the mental context switches from data exploration/analysis to view adjustment and back. The tracked controllers become tools to quickly manipulate (reposition, reorient, and rescale) the dataset and to interrogate it by, e.g., releasing dye particles into the flow field, probing scalar velocities, placing a cutting plane through a region of interest, etc. It is hypothesized that the advantages afforded by head-tracked viewing and 6DOF interaction devices will lead to faster and more efficient examination of 4D flow data. A human factors study is currently being prepared to empirically evaluate this method of visualization and interaction.