Atmospheric nucleation is a process of phase transformation like liquid water transforming into solid or gas phase water, which serves as a significant impact on many atmospheric and technological processes. During the process of the atmospheric nucleation, certain 3D molecular models for atmospheric nucleation will be generated, which are main mixtures of water molecules and hexanol molecules. Analyzing these 3D molecular models can promote the understanding for the nucleation and growth of the particles and phases in a multi-component mixture, as well as for the changes in climate and weather. Therefore, the research for atmospheric nucleation can be transformed into the research for the 3D molecular visualizations and comparisons, which are the similarity calculations. Unfortunately, the research on understanding atmospheric nucleation processes is restricted due to the lack of efficient visual data exploration tools. In this paper, the issue of lacking efficient data visualization tools is tackled by implementing our own application to visualize the atmospheric nucleation. The similarity
calculation for these 3D molecules is implemented in order to analyze and compare the atmospheric nucleation processes and molecular models. Admittedly, there are various 3D molecular similarity calculation algorithms, such as clique-detection algorithms and point matching, etc; however, these algorithms are specifically utilized in the fields of protein amino-acids and pharmacophore. Due to the large scale of the atmospheric nucleation data, GPU (Graphical Processing Units) is employed in order to significantly reduce the computation times. This is achieved by utilizing CUDA (Compute Uniform Device Architecture) technology which allows us to execute our algorithm in a parallel method.
Furthermore, in this research, the knowledge of hypertree visualization is intended to be utilized to enhance the previously developed web-based visualization and analysis tool that allows remote users to effectively mine the wealth of particle-based nucleation simulation data. The research goal is to speed up knowledge discovery and improve users' productivity through effective data visualization technique and more friendly user interface design. Meanwhile, a feasible parallel computing solution is developed to overcome the slow response due to expensive large data pre-processing. The core research of my thesis is to calculate the similarity between the distinct 3D molecules.
| Identifer | oai:union.ndltd.org:pacific.edu/oai:scholarlycommons.pacific.edu:uop_etds-1839 |
| Date | 01 January 2012 |
| Creators | Zhu, Kai |
| Publisher | Scholarly Commons |
| Source Sets | University of the Pacific |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of the Pacific Theses and Dissertations |
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