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Title Calculation, utilization, and inference of spatial statistics in practical spatio-temporal data
Publication Date
Date Accessioned
Degree PhD
Discipline/Department Computational Science and Engineering
Degree Level doctoral
University/Publisher Georgia Tech
Abstract The direct influence of spatial and structural arrangement in various length scales to the performance characteristics of materials is a core premise of materials science. Spatial correlations in the form of n-point statistics have been shown to be very effective in robustly describing the structural features of a plethora of materials systems, with a high number of cases where the obtained futures were successfully used to establish highly accurate and precise relationships to performance measures and manufacturing parameters. This work addresses issues in calculation, representation, inference and utilization of spatial statistics under practical considerations to the materials researcher. Modifications are presented to the theory and algorithms of the existing convolution based computation framework in order to accommodate deformed, irregular, rotated, missing or degenerate data, with complex or non-probabilistic state definitions. Memory efficient personal computer oriented implementations are discussed for the extended framework. A universal microstructure generation framework with the ability to efficiently address a vast variety of geometric or statistical constraints including those imposed by spatial statistics is assembled while maintaining scalability, and compatibility with structure generators in literature.
Subjects/Keywords Materials; Informatics; Data science; Image processing; Spatial statistics; Texture synthesis; Microstructure generator
Contributors Kalidindi, Surya R. (advisor); Song, Le (committee member); Garmestani, Hamid (committee member); Chau, Duen H. (committee member); Kang, Sung H. (committee member)
Language en
Country of Publication us
Record ID handle:1853/58723
Repository gatech
Date Indexed 2018-01-11
Issued Date 2017-08-02 00:00:00
Note [degree] Ph.D.;

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