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A Class of Rate-Independent Lower-Order Gradient Plasticity Theories: Implementation and Application to Disc Torsion
Emin Semih Perdahcıoğlu1, Celal Soyarslan2, Emin Erkan Aşık3
1Chair of Nonlinear Solid Mechanics, Faculty of Engineering Technology, University of Twente, 7500AE Enschede, The Netherlands. e.s.perdahcioglu@utwente.nl.
This study investigates plasticity deviations at smaller scales using gradient-enhanced models. It compares phenomenological and crystal plasticity approaches, highlighting how dislocation density and gradient types influence material behavior.
Area of Science:
- Materials Science
- Mechanical Engineering
- Continuum Mechanics
Background:
- Plasticity phenomena diverge at micro/nanoscales compared to macroscales.
- Understanding these deviations is crucial for advanced material design and manufacturing.
- Existing models may not fully capture scale-dependent plasticity effects.
Purpose of the Study:
- To investigate the gap in understanding plasticity at decreasing scales.
- To compare phenomenological and crystal plasticity models using a gradient-enhanced approach.
- To analyze the influence of different dislocation types and gradient origins on material behavior.
Main Methods:
- Employed a lower-order gradient enhanced approach.
- Utilized phenomenological continuum and crystal plasticity models.
- Incorporated statistically stored dislocations (SSDs) and geometrically necessary dislocations (GNDs) into hardening models.
- Used a rate-independent formulation to avoid artificial hardening.
Main Results:
- Both models successfully incorporated GNDs into hardening mechanisms.
- Simulations revealed distinct behaviors based on structurally imposed vs. inherent gradients.
- The study quantified the impact of gradient types on plasticity at smaller scales.
Conclusions:
- Gradient-enhanced models provide valuable insights into scale-dependent plasticity.
- The distinction between imposed and inherent gradients is critical for accurate micro/nanoscale plasticity prediction.
- Further research can refine these models for predicting the behavior of materials at reduced characteristic scales.
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