Many everyday materials do not fit classical definitions of fluid and solid. Instead, rheological materials can have properties of both states. While engineers typically use traditional fluid and solid materials to achieve desired functionality of engineering systems, there is great opportunity for novel performance based on rheological material behavior. The focus of this Grant Opportunity for Academic Liaison with Industry (GOALI) Program research project is to ask the question, given a desired performance, what rheological material behavior is needed, and what material formulations achieve this behavior? The work here will study design and optimization techniques for these complex soft materials. The research involves theory, computation, and experiment. The methodology aims to transform the search for novel rheologically-complex materials and their use in engineering design. The resulting enhanced system performance would impact numerous application domains such as, but are not limited to, soft robotics, vibration control, fire-suppression systems, and prosthetics. The GOALI partnership will strengthen the relevance of the new methods to engineering practice and provide a test bed for the new design approach. The interaction with industry will also enhance the training of students. Associated outreach activities will broaden the general understanding of rheological materials via the development and use of a portal enabling virtual experiments on rheological materials.
The objective of this work is to create a new paradigm for creative and rational design of rheologically-complex materials. This project?s approach directly connects system-level performance optimization to material-level design. A core challenge is that rheological properties are functions, not constants. The work will define and organize design-appropriate mathematical modeling methods that use descriptive material functions (function-valued properties) directly. Rheological complexity derives from time-dependent (viscoelastic) and amplitude-dependent (nonlinear) behavior, and this two-dimensional space will be used to organize the applicability and limitations of different constitutive models for the purpose of design. Optimization methods for the resulting mathematical structures will be established. A key challenge is the optimization of functions, such as kernel functions in convolution integrals. This will be approached with numerical optimal control methods including direct transcription. Once target properties are identified, experiments will be used to demonstrate rational design of rheologically-complex material compositions that best achieve the system performance objectives. This material-level design will leverage known structure-rheology models by considering multiple material strategies including polymeric systems, colloidal systems, and composite combinations. The industry GOALI partner will work closely with the academic team to help translate the work to industry, provide insight on formulation of new material concepts, and provide relevant material formulations. The methodology will be tested numerically and experimentally with case studies of shear-thinning and linear viscoelastic systems. The new paradigm will lay the foundation for additional integrated design approaches for other materials domains with complex function-valued properties.
