Paper Number
AR25 

Session
Applied Rheology and Rheology Methods

Title
Pseudo-linear large-amplitude oscillatory shear stress (LAOStress): A delicious gift from Afuega’l Pitu Spanish cheese

Presentation Date and Time
October 12, 2021 (Tuesday) 4:10

Track / Room
Track 2 / Ballroom 7

Authors (Click on name to view author profile)

  1. Ramlawi, Nabil (University of Illinois at Urbana-Champaign)
  2. Piñeiro-Lago, Lorena (University of Vigo, Food Technology Area, Faculty of Sciences)
  3. Franco, Inmaculada (University of Vigo, Food Technology Area, Faculty of Sciences)
  4. Tovar, Clara A. (University of Vigo, Department of Applied Physics, Faculty of Sciences)
  5. Campo-Deaño, Laura (Universidade do Porto, Departamento de Engenharia Mecânica, Faculdade de Engenharia)
  6. Ewoldt, Randy H. (University of Illinois at Urbana-Champaign, Department of Mechanical Science and Engineering)

Author and Affiliation Lines (in printed abstract book)
Nabil Ramlawi1, Lorena Piñeiro-Lago2, Inmaculada Franco2, Clara A. Tovar2, Laura Campo-Deaño3 and Randy H. Ewoldt1
1University of Illinois at Urbana-Champaign, Urbana-Champaign, IL 61801; 2Food Technology Area, Faculty of Sciences, University of Vigo, Ourense, Spain; 3Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto 4200-465, Portugal

Speaker / Presenter 
Ramlawi, Nabil

Keywords
experimental methods; applied rheology; rheology methods

Text of Abstract
We describe dimensionality reduction and feature selection from nonlinear rheology for the purpose of human cognition and sample comparison. Specifically, we consider stress-controlled amplitude sweeps in large-amplitude oscillatory shear (LAOStress) for the Spanish acid-coagulated cheese Afuega’l Pitu. Being a food product enables routes of human perception unavailable with inedible materials, and this in part guides our feature selection hypotheses. The dataset consists of two variations (Blancu and Roxu) each from nine different manufacturers, totaling 18 different samples each tested at three different temperatures (25, 50, 75 °C) each at three different frequencies. These 162 different conditions each experience a LAOStress amplitude sweep that generates a nonlinear strain waveform at each stress amplitude covering a range of 10 – 10,000 Pa. We developed data processing software to analyze this large dataset which allowed us to test different summarizing metrics (low-dimensional descriptions) that highlight the similarities and differences between the cheeses. Key features include the linear viscoelastic compliance (modulus) and the critical stress for significant nonlinearity (either 15% or 100% increase in compliance). The data reduction was simple because the material revealed a distinct response that we call “pseudo-linear” LAOS, wherein some metrics of nonlinearity are small, while others are dramatic. This is geometrically interpreted with Lissajous curve rotation and distortion. For these samples, we generally observe significant rotation (change of first-harmonic compliance) with minimal distortion (as captured by local LAOS measures within a Lissajous curve and higher harmonics). We introduce a map for quantitatively assessing pseudo-linear signatures which can be used across a wide range of soft matter microstructures and constitutive models to help identify and assess low-dimensional features of LAOS datasets.