Award Abstract # 2145512
CAREER: Nonlinear Resonances of Highly Damped, Soft Materials

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: UNIVERSITY OF WASHINGTON
Initial Amendment Date: March 7, 2022
Latest Amendment Date: June 26, 2023
Award Number: 2145512
Award Instrument: Standard Grant
Program Manager: Alena Talkachova
atalkach@nsf.gov
 (703)292-2949
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: June 1, 2022
End Date: May 31, 2027 (Estimated)
Total Intended Award Amount: $671,643.00
Total Awarded Amount to Date: $687,643.00
Funds Obligated to Date: FY 2022 = $671,643.00
FY 2023 = $16,000.00
History of Investigator:
  • Mehmet Kurt (Principal Investigator)
    mkurt@uw.edu
Recipient Sponsored Research Office: University of Washington
4333 BROOKLYN AVE NE
SEATTLE
WA  US  98195-1016
(206)543-4043
Sponsor Congressional District: 07
Primary Place of Performance: University of Washington
Seattle
WA  US  98195-0001
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): HD1WMN6945W6
Parent UEI:
NSF Program(s): CAREER: FACULTY EARLY CAR DEV,
BMMB-Biomech & Mechanobiology,
Dynamics, Control and System D
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 028E, 034E, 1045, 116E, 7479, 9178, 9179, 9231, 9251
Program Element Code(s): 104500, 747900, 756900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Rezayaraghi, Fargol and Abderezaei, Javid and Ozkaya, Efe and Stein, Devlin and Pionteck, Aymeric and Kurt, Mehmet "Modal analysis of computational human brain dynamics during helmeted impacts" Brain Multiphysics , v.5 , 2023 https://doi.org/10.1016/j.brain.2023.100082 Citation Details

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