Description:
OBJECTIVE: The objective of this project is to design and develop a modeling tool for materials designers, which uses as input on the microstructure quantitative statistical measures of structure variations and features, and provides efficiently information on materials behavior with robust quantitative measures of performance variations and their correlations with microstructure features. This project supports the goals of the Materials Genome Initiative (MGI) in the area of Integrated Computational Materials Engineering (ICME). DESCRIPTION: The behavior of individual crystalline grains in a material is well modeled and understood. For the behavior of polycrystalline media, however, we revert to relatively simple bulk constitutive models that often only roughly approximate our observations of macroscopic behavior. Local misorientations result in deviations in local responses, which can be much larger than any other deviations seen in analysis. Aggravating this is that these field problems are non-linear in the materials properties, which limits the applicability of many perturbation and spectral approaches. Finally, the exact grain positions and orientations are usually random, which makes single examinations of example microstructures limited in overall applicability for a materials design problem. More important to the designer is a measure of the mean behavior with quantitative predictions of the likely deviations, the correlations of these deviations, and the sensitivities of these deviations to the microstructure features. These allow the designer to make predictions of the reliability of the material. The objectives of this research area are to design and develop a stochastic analysis code (for example, finite element analysis, boundary element analysis, peridynamics), using as inputs the statistical properties of the microstructure of the material, and outputting the performance characteristics, including variations, fluctuations, and correlations in materials behavior. The code should allow the design and development of random-field constitutive behavior models based on adaptations of homogenization of crystal plasticity models, or other similar mechanism-based models, that provide statistical information on material behavior at the polycrystalline length scale, and are suitable for insertion into stochastic analysis models. Objective outcomes should include the design and development of visualization tools that use robust archival data formats, and display mean-field, uncertainty, and sensitivity parameters, in a manner suitable to a materials designer. The research should also develop and design a suite of test and evaluation methods to determine experimentally the materials properties parameters necessary to populate the constitutive models (such methods might be reentrant). This work will utilize the construct of integrated computational materials engineering, supporting the development of the materials innovation infrastructure within the Materials Genome Initiative. PHASE I: The successful phase 1 effort will demonstrate successfully the concept and mathematical basis for the code and its use in materials and product design to meet the objectives stated above. The effort shall also produce a roadmap/timeline for the code development and testing. PHASE II: The Phase II project will develop and demonstrate the code the concept from Phase I. The investigators will demonstrate the uses of the code in the design of a hypothetical component of interest. The investigators will also outline a market for the tool, and a plan for a second iteration of development to meet that market. PHASE III: The design of critical components requires careful consideration of the reliability of the components in the likely service environments. The designer, having a means of dealing directly with the randomness of the material and the environment, can consider the reliability issues as part of the design process, and not as an a posteriori process. This will speed the design process and result in systems optimized for superior reliability. PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: Computational design of materials and materials systems for specific applications has been associated with both commercial and military materials processing and design programs and product development activities. The computational design of metal alloy microstructure or hybrid and composite material meso-structure and, therefore, properties appropriate for specific applications has broad application in both military platforms and civil transportation for air, sea, and ground vehicles and in dual-use specialty applications such as spacecraft and missiles. The potential to tailor specific metal alloy properties has the potential for more efficient use of materials and processing energy in both the defense and commercial sectors.
