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. Dynamic Lot Size Optimization with Reinforcement Learning
  2. The delay vector variance method and the recurrence quantification analysis of energy markets
  3. Dispatching rule selection with Gaussian processes
  4. Analysis of long-term statistical data of cobalt flows in the EU
  5. Computing regression statistics from grouped data
  6. Image compression based on periodic principal components
  7. Gaussian processes for dispatching rule selection in production scheduling
  8. Digging into the roots
  9. Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators
  10. Knowledge Graph Question Answering and Large Language Models
  11. Challenge-oriented policy making and innovation systems theory: reconsidering systemic instruments
  12. Faulty Process Detection Using Machine Learning Techniques
  13. What can conservation strategies learn from the ecosystem services approach?
  14. A Class of Simple Stochastic Online Bin Packing Algorithms
  15. Constraints are the solution, not the problem
  16. Development and evaluation of a training program for dialysis nurses - An intervention study
  17. Overcoming Multi-legacy Application Challenges through Building Dynamic Capabilities for Low-Code Adoption
  18. Positioning Improvement for a Laser Scanning System using cSORPD control
  19. Extending talk on a prescribed discussion topic in a learner-native speaker eTandem learning task
  20. A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods
  21. Handicaps in job assignment
  22. Covert and overt automatic imitation are correlated
  23. Towards an open question answering architecture
  24. Knowledge transfer during the integration of knowledge-intensive acquisitions
  25. Exploring large vegetation databases to detect temporal trends in species occurrences