Abstract

Today, computational fluid dynamics (CFD) research is almost impossible without computer-generated visualizations of the very large amounts of data resulting from numerical simulations. Although good techniques now exist for analysis of scalar data, most existing techniques for the visualization of vector fields-the predominant data type in CFD-meet only part of what is required. Common techniques such as arrow plots, streamlines, and particles work well for 2D applications, but for 3D data sets they often lead to cluttered displays. For tensors, which are much more complex and abstract entities the problem is even more severe. There is a real need for visualization, but there are no simple solutions. Many researchers have recognized this challenge and developed new techniques. We restrict ourselves to open research issues. We proceed in three ways. First, we propose a classification of existing vector and tensor field visualization techniques based on work by Delmarcelle and Hesselink (1994) and point out research gaps in this classification scheme. Second, we discuss feature-based visualization, which shows higher level descriptions derived from elementary data. Third, we consider the role of visualization in the research process, again revealing gaps in our current know-how concerning visualization of vector and tensor fields. >

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