Structural Engineering and Mechanics

Techno-Press (테크노프레스)
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Characterization of a carbon black rubber Poisson's ratio based on optimization technique applied in FEA data fit

  • Lalo, Debora Francisco (Graduate Program in Structural Engineering, Department of Structural Engineering, School of Engineering, Universidade Federal de Minas Gerais) ;
  • Greco, Marcelo (Graduate Program in Structural Engineering, Department of Structural Engineering, School of Engineering, Universidade Federal de Minas Gerais) ;
  • Meroniuc, Matias (Fluid Mechanics Laboratory, Railway Engineering, National Technological University)
  • Received : 2019.07.11
  • Accepted : 2020.08.13
  • Published : 2020.12.10
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Abstract

The paper presents a study regarding rubber compressibility behavior. The objective is to analyze the effect of compression degree of rubber on its mechanical properties and propose a new methodology based on reverse engineering to predict compressibility degree based on uniaxial stretching test and Finite Element Analysis (FEA). In general, rubbers are considered to be almost incompressible and Poisson's ratio is close to 0.5. Since this property is intimately related to the rubber packing density, little changes in Poisson's ratio can lead to significant changes regarding mechanical behavior. The deviatory hyperelastic constants were obtained through experimental data fitting by least squares method for the most relevant constitutive models implemented in commercial software Abaqus, such as: Neo-Hooke, Mooney-Rivlin, Ogden, Yeoh and Arruda-Boyce, whereas the hydrostatic part was determined through an optimization algorithm implemented in the Abaqus environment by Python scripting. The simulation results presented great influence of the Poisson's ratio in the rubber specimen mechanical behavior mainly for high strain levels. A conventional pure volumetric compression test was also carried out in order to compare the results obtained by the proposed methodology.

Keywords

Acknowledgement

The authors are grateful for the financial support granted by Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Programa de Pós-Graduação em Engenharia de Estruturas (PROPEEs-UFMG) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), under grant numbers TEC-PPM-00444-18, 302597/2019-0 and 405183/2018-6. The authors also acknowledge UFMG (Universidade Federal de Minas Gerais) and University Center of FEI supports. Authors also acknowledge the valuable contributions of the reviewers that considerably improve the paper.

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