The assessment of viscoelastic models for nonlinear soft materials

Rodrigo D. Solis-Ortega, Abbas A. Dehghani-Sanij, Uriel Martinez Hernandez

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

2 Citations (SciVal)
73 Downloads (Pure)


The increasing use of soft materials in robotics applications requires the development of mathematical models to describe their viscoelastic and nonlinear properties. The traditional linear viscoelastic models are unable to describe nonlinear strain-dependent behaviors. This limitation has been addressed by implementing a piecewise linearization (PL) in the simplest viscoelastic model, the Standard Linear Solid (SLS). In this work, we aim to implement the PL in a more complex model, the Wiechert model and compare the stress response of both linearized models. Therefore, the experimental data from the stress relaxation and tensile strength tests of six rubber-based materials is used to approximate the spring and dashpot constants of the SLS and the Wiechert model. Prior to implement the PL into the stress-strain curve of each material, the stress response from the Maxwell branches must be subtracted from this curve. By using the parameters obtained from fitting the Wiechert model into the stress relaxation curve, the response of both linearized models was improved. Due to the selection of constitutive equations evaluated, the linearized SLS model described the stress-strain curve more accurately. Finally, this work describes in details every step of the fitting process and highlights the benefits of using linearization methods to improve known models as an alternative of using highly complex models to describe the mechanical properties of soft materials.

Original languageEnglish
Title of host publicationProceedings of the IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics
Number of pages6
ISBN (Electronic)9781538681831
ISBN (Print)9781538681831
Publication statusPublished - 9 Oct 2018

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering


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