Monday  |  Salon 10  |  10:00 AM–10:20 AM

#15666, Considerations for the Identification of Elasto-Plastic Material Model Parameters

Accurate computer modeling and simulation is necessary for the design of advanced engineered components. The reliability of these computer models depends on the accuracy of the user-defined material model parameters and their ability to capture the physical phenomena in the simulation. However, the experimental data used to calibrate these models are often prone to biases due to systematic limitations of the measurement technique, or experimental anomalies. Therefore, these biases must be considered when attempting to inversely identify material properties from an experiment. This work focuses on reducing the bias in the final-calibrated material model by careful intervention in the inversion process.
SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. SAND2022 13476 A

Samuel Fayad   University of Illinois, Urbana-Champaign
Elizabeth Jones   Sandia National Laboratories
D. Thomas Seidl   Sandia National Laboratories
Phillip Reu   Sandia National Laboratories
John Lambros   University of Illinois, Urbana-Champaign