Modeling wide range of viscoelastic–viscoplastic behavior of Araldite LY 564 epoxy using cooperative viscoplasticity theory based on overstress model

Bakbak O., Çolak Çakır Ö. Ü.

JOURNAL OF APPLIED POLYMER SCIENCE, vol.1, pp.1-13, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 1
  • Publication Date: 2022
  • Doi Number: 10.1002/app.53557
  • Journal Name: JOURNAL OF APPLIED POLYMER SCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Applied Science & Technology Source, Biotechnology Research Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.1-13
  • Keywords: cooperative VBO, epoxy, high strain rate, modeling, relaxation
  • Yıldız Technical University Affiliated: Yes

Abstract

The rate-dependent properties of epoxy (Araldite LY 564) were successfully addressed by dynamic mechanical analysis (DMA), quasi-static compression tests (strain rates: 1.E-3, 1.E-2, and 1.E-1 /s), Split Hopkinson Pressure Bar (SHPB) testing (strain rates: 875 and 770/s) and stress relaxation experiments (strain levels: 3.16 and 7.15%) are simulated by a micromechanically based constitutive model. The used model is Cooperative-Viscoplasticity Theory Based on Overstress (VBO) model. The majority of works about modeling poly- mers are limited to modeling quasi-static tension-compression behaviors and predicting elasticity modulus and yield strength. In this work, the effectiveness of the Cooperative-VBO model is verified and validated by simulating a wide range of material behaviors of Araldite LY 564. Material parameters of the model are determined by using storage modulus obtained from DMA and quasi-static compression test at a strain rate of 1.E-1 /s. High strain rate behaviors and stress relaxation behaviors are predicted. The behaviors from quasi-static to high strain rate, from stress relaxation at different strain levels to storage modulus, respectively, are predicted with a single set of material parameters. Simulation and prediction results revealed the effectiveness of the proposed model.