Ultra-High-Performance Concretes (UHPCs) are a promising class of cementitious materials possessing mechanical properties superior to those of Normal Strength Concretes (NSCs). However, UHPCs have been slow to transition from laboratory testing to insertion in new applications, partly due to an intuitive trial-and-error materials development process. This research seeks to addresses this problem by implementing a materials design process for the design of UHPC materials and structures subject to blast loads with specific impulses between 1.25- and 1.5-MPa-ms and impact loads resulting from the impact of a 0.50-caliber bullet travelling between 900 and 1,000 m/s. The implemented materials design process consists of simultaneous bottom-up deductive mappings and top-down inductive decision paths through a set of process-structure-property-performance (PSPP) relations identified for this purpose. The bottom-up deductive mappings are constructed from a combination of analytical models adopted from the literature and two hierarchical multiscale models developed to simulate the blast performance of a 1,626-mm tall by 864-mm wide UHPC panel and the impact performance of a 305-mm tall by 305-mm wide UHPC panel. Both multiscale models employ models at three length scales – single fiber, multiple fiber, and structural – to quantify deductive relations in terms of fiber pitch (6-36 mm/revolution), fiber volume fraction (0-2%), uniaxial tensile strength of matrix (5-12 MPa), quasi-static tensile strength of fiber-reinforced matrix (10-20 MPa), and dissipated energy density (20-100 kJ/m²). The inductive decision path is formulated within the Inductive Design Exploration Method (IDEM), which determines robust combinations of properties, structures, and processing steps that satisfy the performance requirements. Subsequently, the preferred material and structural designs are determined by rank order of results of objective functions, defined in terms of mass and costs of the UHPC panel.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50216 |
| Date | 13 January 2014 |
| Creators | Ellis, Brett D. |
| Contributors | McDowell, David L. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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