Scientific visualization of large datasets

One of the main goals of scientific visualization is the development of algorithms and appropriate data models which allow interactive visual analysis and direct manipulation of the increasingly large data sets which result from time-dependent 3D simulations running on massive parallel computer systems or from measurements employing fast high-resolution sensors. This task can only be achieved with the optimization of all steps of the visualization pipeline: semantic compression and feature extraction based on the raw data sets, adaptive visualization mappings which allow the user to choose between speed and accuracy, and exploiting new graphics hardware features for fast and high-quality rendering. The paper presents some of the recent advances in those areas of scientific visualization showing examples from computer aided engineering in the automotive industry like Lattice-Boltzmann based flow simulation and pre- and postprocessing in crash-worthiness analysis, as well as volume visualization of chemical and medical datasets. © Oldenbourg Verlag