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High-resolution virtual reactors will enable scientists to simulate and analyze almost every aspect of the performance of existing nuclear reactor designs in unprecedented detail. However, high-quality visualizations of full-core nuclear reactor simulation data with high (pin-by-pin) spatial resolution require both time- and memory-consuming processing of large-scale combinatorial solid geometries...
Recent advances in high-performance computing technologies, applied in climate science, are allowing increases in model complexity, model resolution, and the number of simulations run. The interactive exploration and analysis of these complex, multi-field climate data sets have been identified as one of the major current challenges in scientific visualization. For example, without direct 3D multi-field...
Finding the unknown laws of sciences among data is one of the most essential goals in modern scientific discoveries. Visualization can be a useful tool for domain scientists to understand data if these data can be interactive rendered. But interactive rendering and exploring of these massive, complex data sets has been identified as one of the major challenges in current scientific visualization field...
Due to its interactive and high quality rendering abilities, GPU ray-casting volume rendering method is very popular for the post-processing of scientific and engineering computing appliances. This method however is likely suffered from memory effect, for it will cause the algorithm failure when facing the big data appliances. This problem can be solved through massively parallel approaches. But on...
The visualization of large-scale time-varying data can provide scientists a more in-depth understanding of the inherent physical phenomena behind the massive data. However, because of non-uniform data access speed and memory capacity bottlenecks, the interactive rendering ability for large-scale time-varying data is still a major challenge. Data compression can alleviate these two bottlenecks. But...
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