Computational modeling of amorphous polymers: A Lagrangian logarithmic strain space formulation of a glass–rubber constitutive model

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

We present a reformulation of the finite strain, rate dependent inelastic glass–rubber material model suggested by Buckley and Jones (1995) and extended by Adams et al. (2000) for modeling the deformation of amorphous polymers in the Lagrangian logarithmic strain space. This not only warrants a hyperelastic characterization in the bonding part which remedies problems associated with hypoelastic approaches devising objective stress rates selected on ad hoc basis, see, e.g., Dooling et al. (2001) and Li and Buckley (2009), but also allows a transparent and naturally objective implementation analogous to the geometrically linear theory. A numerical implementation into ABAQUS is pursued where algorithms for stress update and tangent moduli computations are reported. It is shown that significant reduction in nonlinear equation system size is possible in the computation of both bonding and conformational part. The characterization tests include constant-width tension, equi-biaxial tension, and simple shear. To demonstrate the robustness of the developed framework, two hypothetical problems of extreme deformation under tensile and combined tensile and torsion loading are considered. Finally, simulation of an injection stretch-blow molding process is presented as an application problem.

Original languageEnglish
JournalComputer Methods in Applied Mechanics and Engineering
Volume344
Pages (from-to)887-909
Number of pages23
ISSN0045-7825
DOIs
Publication statusPublished - 01.02.2019

    Research areas

  • Glass–rubber constitutive model, Lagrangian logarithmic strains, Return mapping
  • Engineering

Recently viewed

Publications

  1. Early Detection of Faillure in Conveyor Chain Systems by Wireless Sensor Node
  2. Formative Perspectives on the Relation Between CSR Communication and CSR Practices
  3. TARGET SETTING FOR OPERATIONAL PERFORMANCE IMPROVEMENTS - STUDY CASE -
  4. From Knowledge to Application
  5. Neural correlates of the enactment effect in the brain
  6. Machine Learning and Knowledge Discovery in Databases
  7. Competing Vegetation Structure Indices for Estimating Spatial Constrains in Carabid Abundance Patterns in Chinese Grasslands Reveal Complex Scale and Habitat Patterns
  8. Spaces for challenging experiences, indeterminacy, and experimentation
  9. Mapping Khulan habitats - a GIS based approach.
  10. Commitment to grand challenges in fluid forms of organizing
  11. Soft Optimal Computing Methods to Identify Surface Roughness in Manufacturing Using a Monotonic Regressor
  12. A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics
  13. Determination of 10 particle-associated multiclass polar and semi-polar pesticides from small streams using accelerated solvent extraction
  14. Training effects of two different unstable shoe constructions on postural control in static and dynamic testing situations
  15. Intraspecific trait variation patterns along a precipitation gradient in Mongolian rangelands
  16. Artificial Intelligence in Foreign Language Learning and Teaching
  17. Unraveling Privacy Concerns in Complex Data Ecosystems with Architectural Thinking
  18. A survey of empirical studies using transaction level data on exports and imports
  19. Governing Objects from a Distance
  20. An Outcome-Oriented, Social-Ecological Framework for Assessing Protected Area Effectiveness
  21. Aspect-oriented software development
  22. Web-Based Drills in Maths Using a Computer Algebra System
  23. Effectiveness of a Web-Based Cognitive Behavioural Intervention for Subthreshold Depression
  24. Machine Learning and Data Mining for Sports Analytics
  25. E-stability and stability of adaptive learning in models with private information
  26. Action rate models for predicting actions in soccer
  27. Time Use Research and Time Use Data
  28. Failing and the perception of failure in student-driven transdisciplinary projects
  29. Computational history of knowledge