The research goal of this award is to enable a more effective multi-scale and multivariate modeling process for the design of components comprised of cellular, mesostructured materials by advancing our understanding of how uncertainties at different scales affect product realization. This research will explore fundamental theories and computational tools to cascade uncertainties among meso- and macro-scales, manufacturing processes, and operating environments. Specifically, the new method will resolve the imperative issue of the need of accurate stochastic modeling across multiple length scales while ensuring the link between stochastic models and physical realities. Deliverables include, 1) the implementation of reliability-based synthesis methods to realize robust systems by incorporating the effects of stochastic dependencies in material, manufacturing, and various scales, 2) the experimental characterization and model building of the cellular structures via additive manufacturing technologies, and 3) the demonstration of the integrated design synthesis method on aerospace components comprised of risk mitigated mesostructured materials.
The results of the research will have a broad impact on the mechanical and materials engineering community, as well as other research, education, and industrial programs by developing new computational models and tools that can be used to design robust meso-structured materials for aerospace or automobile components. A significant benefit to society is expected by providing examples of parts that utilize material much more efficiently than currently possible, leading to improved fuel economy for cars and planes, among other benefits. The research experience for the graduate and undergraduate programs will foster creative and statistical thinking among an interdisciplinary group of faculty and students. Incorporating reliability-based design and hands-on experience into the existing mechanical engineering courses will help better education and train a new generation of engineers who are better prepared to address the challenges in the future.
