Across industries, materials are becoming increasingly advanced, and predicting their complex behavior is one of the hardest challenges in modern day engineering. In the real world, materials are nonlinear, so any material representation or simulation must be capable of producing an accurate description of the corresponding physical behavior across all scales and structures. This is where material modeling comes in.
Material modeling can be described as “the use of test data or mathematical formulas that describe material properties to predict how they will perform in a given environment.” It is required when a material will be exposed to an environment whose effects cannot be fully replicated beforehand with a hardware prototype.
The Abaqus solver has always been a reliable source for nonlinear materials modeling technology. As demand has increased for realistic simulation of complex material behavior over the years, Abaqus has been expanded and become more advanced, with a host of new material modeling capabilities. These make it possible to accurately describe inelastic behavior in metals, and to simulate polymers, elastomers, and foams.
Elastomers, rubber compounds and polymers in general are still a tough challenge for simulation experts. They exhibit rate-dependent behavior, hysteresis, stress softening (also known as the Mullins effect), and permanent set upon removal of load. To handle these complex behaviors, SIMULIA developed a general constitutive modeling framework known as the Parallel Rheological Framework, or PRF.
PRF has the potential to capture a wide variety of behaviors, including nonlinear viscoelasticity, the Mullins effect, and permanent set. The framework’s features include a multiple network setup; different dashpot behaviors in each network; nonlinear elastic springs based on any of the strain energy potentials in Abaqus; flexibility in choosing long- and short-term responses; and the Mullins effect in the plasticity and equilibrium network.
To put these types of complex nonlinear material models to real use, material calibration is critical. Material calibration provides a framework for enabling accurate simulation of the observed behavior, using surrogate mathematical models (also referred to as abstractions).
Effectively, material model calibration is the key that unlocks the door to all SIMULIA material models. In the sense of democratization, material calibration is therefore an enabling technology. To make the material calibration framework more accessible, SIMULIA has developed the material calibration app for the 3DEXPERIENCE platform. It is a fast and efficient tool, which allows a user to input test data and perform the aforementioned calibration, making the material accessible for simulation in a real-time fashion.
Right now is an exciting time for materials, as they become more and more advanced with increased smart capabilities. These new materials will go a long way toward making our world safer and healthier, as well as simply more interesting. Many of these materials have unprecedented properties, which means that it is difficult to know exactly how they will behave in different environments and situations. Material modeling and material calibration will help to ensure that these materials will perform to their best potential from the perspectives of experience, quality, and sustainability.
If you’d like to learn more about material modeling, material calibration, or the 3DEXPERIENCE app, the webinar “Realistic Materials: Modeling and Calibration” is available here. You can also learn more at the SIMULIA Learning Community.