Run and Review the Material Calibration

Run the calibration job, and then revisit the plot to assess how closely the material's response curve matches the test data. When the calibration is complete, adjust the sensitivity for selected parameters.

A parameter's sensitivity indicates how much influence the parameter has on the calibrated response. For example, parameters with higher sensitivity values have a greater influence on the response. You might want to disable parameters with low sensitivities and rerun the calibration with highly sensitive parameters. When you run a calibration, these parameters iteratively change until the solution satisfies the convergence criteria and the calibration error is smaller.

  1. From the options at the top of the Calibration Setup panel, click Execute .

    This example uses the default best-fit error measure (the coefficient of determination, R2) as a convergence criterion measure. This measure indicates how closely the calibration curve matches the test data points. For R2, the objective function value is a number between 0 and 1; the closer to 1, the better the match. The objective function is a measure of the error between the test data and the predicted material response.

    The Calibration History panel appears and provides a plot of the progress of the calibration, including the value of the objective function for each iteration.
  2. After the calibration completes, review the data in the Sensitivity column in the Material model section of the Calibration Setup panel.

    All of the parameters have low sensitivities except C10 and g5. However, there is little room for improvement because the R2 values are already high.

  3. Review the convergence criterion values at the bottom of the Calibration Setup panel.
    Each material response simulated from the calibration demonstrates R2 values of over 0.99, indicating that the calibration is representative of the material behavior. Review the table below to see the sample results of the calibration.
    Model and Test Data Weight R2
    Strain Rate = 0.01 1 0.997
    Strain Rate = 0.10 1 0.993
    Strain Rate = 1.00 1 0.998
    Strain Rate = 10.0 1 0.999
    Strain Rate = 40 0.5 0.998
  4. Review the updated response curve in the Plot panel.
    The material response curve is closer to the test data, as shown below. In this example, the color of the response curves has been changed to green.

  5. Save your work.