Material characterization is the foundation of any reliable FEA model. Yet in most workflows, there's a significant gap between what's measured in a test and what goes into the simulation: stress-strain curves from a handful of gauges, averaged over large regions, fitted to a constitutive law that may not capture the actual local behavior of the material.
FAQ
- What material types is EikoTwin DIC suited for?
EikoTwin DIC has been applied to metals, composites, polymers, elastomers, and foams. Any material that can be speckle-coated and tested under controlled loading is a valid candidate. For very small specimens, EikoSim can advise on speckle pattern sizing and camera setup. - Can EikoTwin DIC support inverse identification of material parameters?
Yes — this is a core use case for EikoTwin Digital Twin. The module allows engineers to set up a feedback loop between experimental full-field data and FEA model parameters, minimizing the gap between simulation and measurement iteratively. - How many tests do I need to characterize a material with this approach?
Full-field DIC provides much richer information per test than gauge-based methods, which typically reduces the number of tests required. The exact protocol depends on the material and the constitutive model, but EikoSim can help design an efficient test plan. - What output formats are supported for integration with my FEA solver?
If you need to use inverse methods, EikoTwin Digital Twin (inverse identification) supports Abaqus. Material parameters identified through inverse methods can be directly imported into your solver's material card.