CAREER: Nonlinear Resonances of Highly Damped, Soft Materials

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This Faculty Early Career Development Program (CAREER) grant promotes the progress of science and advances the national health through research that enables an improved understanding of impact and vibration-induced damage in highly damped, soft materials, for example, human brain tissue, thereby paving the way for improved diagnosis of pathologies and design of protective devices. Soft materials are found across a variety of engineering domains, ranging from elastomeric dampers in aerospace applications to compliant robotic devices designed for wearability. Traditional techniques for characterizing the response of material structures to dynamic loading fail for soft materials due to the combined effects of large deformations and complex material behaviors. In contrast, the experimental and theoretical framework developed in this project will focus precisely on resonant conditions that produce significant material deformations and activate the strongest dissipative and nonlinear forces. This framework will generate new insights into the occurrence of localized damage in soft materials, for example during transient loading events such as sudden impacts. These insights will be particularly transformative for structural health monitoring of soft structures, including biological systems such as human organs. Project outcomes have the potential to inform research in the biomechanics of traumatic brain injury, one of the leading causes of death and disability among children and adolescents in the US. A closely integrated research and education plan will excite student engagement in STEM through curriculum development, outreach workshops on helmet design, and digital arts exhibits. A dedicated effort to increase participation from the LGBTQ+ community, where a STEM visibility and underrepresentation problem currently exists, includes annual events, workshops, and mentoring networks. This research aims to make fundamental contributions to a modeling and system identification framework for characterizing the deformation response of highly damped, soft materials to steady-state and transient loading, with particular emphasis on deformation localization and damage in heterogeneous, membranous material systems. It achieves this aim by analyzing amplitude resonance backbones in models of highly damped, soft material systems with complex, distributed internal forces, studying the correspondence between such amplitude resonances and the transient impact response, and validating these predictions using magnetic resonance imaging of silicone phantoms representing biological tissue. An efficient computational framework will be developed to enable parameter continuation of amplitude resonance backbones for large-scale models using an innovative combination of the method of harmonic balance, finite-element simulations, and a novel Bayesian Fourier Neural Operator-based machine learning technique. Computational modeling of real-world head impacts will be used to determine the relationship between amplitude resonance backbones and impact-induced strain localization patterns in the human brain.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.