University of Illinois Urbana-Champaign

Oscillatory shear in strain and stress: reduced metrics, first measurements, and linearity limits

Ramlawi, Nabil

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RAMLAWI-DISSERTATION-2023.pdf

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https://hdl.handle.net/2142/121966

Description

Title
Oscillatory shear in strain and stress: reduced metrics, first measurements, and linearity limits
Author(s)
Ramlawi, Nabil
Issue Date
2023-11-02
Director of Research (if dissertation) or Advisor (if thesis)
Ewoldt, Randy H
Doctoral Committee Chair(s)
  • Ewoldt, Randy H
  • Hilgenfeldt, Sascha
Committee Member(s)
  • Schweizer, Kenneth S
  • Evans, Christopher M
  • Rogers, Simon A
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Complex Fluids
  • Rheology
  • Nonlinear viscoelasticity
  • Weakly nonlinear oscillations
  • Constitutive models
Abstract
Complex materials, such as polymers, colloids, and emulsions, with nonlinear viscoelastic behavior, play a crucial role in various industries, including food, agriscience, chemical manufacturing, additive manufacturing, and more. Understanding and characterizing their nonlinear behavior is essential for their design and application. However, this behavior is high-dimensional depending on both the amplitude and timescale of applied deformation. Large-amplitude oscillatory shear (LAOS) is a great way to probe nonlinear viscoelasticity, allowing for independent amplitude and frequency control. A key challenge in analyzing LAOS experiments is the plethora of material functions required to describe the material response. Medium-amplitude oscillatory shear (MAOS) is a protocol that reduces the complexity of LAOS by only quantifying the material functions required to capture the frequency-dependent weakly-nonlinear response of viscoelastic materials. In this dissertation, we explore how LAOS and MAOS can be used to effectively characterize the nonlinear viscoelastic behavior and address fundamental questions regarding the origin of nonlinearity in complex materials. MAOS provides rich information about the nonlinear viscoelastic response while maintaining low dimensionality and accessibility to analytical model solutions. Since this method is recent, not all models have solutions in this limit, which limits the model selection process. Here, we derive MAOS solutions and non-affine visualization of the widely used Johnson-Segalman/Gordon-Schowalter model, showing that it can outperform existing MAOS models for certain materials. Even though, in theory, MAOS can be conducted in stress or strain control modes, no previous MAOStress measurements have been reported. This unexplored protocol provides increased accessibility to MAOS, which is otherwise restricted to strain-controlled instruments. Moreover, MAOStress can answer a paradox regarding the mechanical origin of nonlinearity in viscoelastic material: Is the nonlinearity caused by strain, strain rate, or stress? We show that stress is a more universal measure of nonlinearity across the range of frequency. Motivated by the experimental observations, we explore numerically the dependence of linearity limits on polydispersity in the distribution of relaxation times. While weakly nonlinear protocols like MAOS are great for model fitting and rigorous physical exploration, they don't capture information about the fully nonlinear regime needed to understand how a complex material performs in an industrial application. We explore how we can reduce Large-amplitude Oscillatory Shear Stress (LAOStress) measurements into meaningful metrics that can be connected to the performance of these materials and allow for comparison between different materials. By addressing these research gaps, this thesis contributes to the understanding and design of complex materials with nonlinear viscoelastic behavior, paving the way for advancements in various industries and applications.
Graduation Semester
2023-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/121966
Copyright and License Information
Copyright 2023 Nabil Ramlawi

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