Robust Optimization Scheme for Inverse Method for Crystal Plasticity Model Parametrization.

Area of Science:

• Materials Science
• Computational Mechanics
• Solid Mechanics

Background:

• Bottom-up material modeling using nonlocal crystal plasticity requires numerous physical and phenomenological parameters.
• Identifying these parameters for nonlocal crystal plasticity models is inherently difficult due to their large number.

Purpose of the Study:

• To propose a robust method for parameterizing the nonlocal crystal plasticity model of body-centered cubic (BCC) materials.
• To combine experimental nanoindentation tests with inverse analysis for accurate material parameter identification.

Main Methods:

• Nanoindentation tests were performed to obtain load-displacement curves and surface imprint data.
• An inverse analysis was developed using a trust-region-reflective algorithm to minimize discrepancies between numerical and experimental results.
• A discrepancy function was defined to simultaneously match load-displacement curves and surface topologies.

Main Results:

• Numerical models using identified material properties demonstrated good agreement with experimental nanoindentation data.
• Sensitivity analysis indicated that the geometrical factor significantly influences both load-displacement curves and surface imprint parameters.
• The proposed method successfully parameterized the nonlocal crystal plasticity model for BCC materials.

Conclusions:

• The combined nanoindentation and inverse analysis approach provides a robust method for parameterizing nonlocal crystal plasticity models.
• Accurate identification of material parameters is crucial for reliable bottom-up material modeling.
• Geometrical factors play a critical role in the mechanical response of BCC materials under indentation.