What's New

This section describes the new and enhanced functionality in Material Calibration.

R2022x FD01 (FP.2205)

Regularizing a Test Data Set

You can now regularize a set of test data, which means that you can resample a range of the test data to add or remove data points.
Regularization resamples the test data to be a user-defined number of intervals uniformly spaced with respect to time or frequency. This enhancement lets you increase or decrease the number of test data points in the test data set.
Benefits: This enhancement allows you to modify a test data set to provide a consistent time or frequency interval.
For more information, see Regularizing a Test Data Set

Generating a Time History from a Frequency Domain Test Data Set

You can now generate a time response from a frequency domain test data set using the conversion parameters.
Benefits: This functionality allows you to evaluate whether the current set of conversion parameters is adequate to yield a steady-state response for calibration in Numerical Mode.
For more information, see Generating a Time History from a Set of Frequency Domain Test Data

Critical Points in a Test Data Set

You can now flag one or more points in a test data set as "critical points." These critical points remain unchanged when you perform test data processing operations like smoothing, decimation, or regularization.
Critical points can identify points in the test data that represent important discontinuities, such as load reversals or sudden changes in material response that you usually want to preserve. When you perform preprocessing operations on a test data set with critical points, the app operates on the test data between the critical points and leaves the critical points unchanged. You can define critical points automatically and you can flag individual critical points manually.
Benefits: Defining critical points lets you perform other test data processing operations more easily while keeping the critical points unchanged.
For more information, see Specifying Critical Points in a Test Data Set

Enhancements to Plot Display

You can now define a minimum and maximum value for the X- and Y-axes of a plot. You can also hide the data probe that appears when you hover over data points.
Setting minimum and maximum bounds along either axis lets you create plots that focus on the areas of interest in the plot.
Benefits: These enhancements provide improved usability and customization for plots.
For more information, see Plotting Calibration Data

Support for Hosford-Coulomb Damage

You can now specify Hosford-Coulomb damage as the material model for an FE-based calibration.
Benefits: This enhancement provides a general capability for calibrating materials that experience ductile failure, including sheet metals, extrusion metals, cast metals, and other nonmetal materials.
For more information, see Supported Built-In Material Models

Support for Orthotropic and Anisotropic Elasticity

You can now specify orthotropic and anisotropic elastic material behavior for numerical and FE-based calibrations.
Benefits: This enhancement provides a general capability for calibrating materials that experience nonisotropic response to external loadings.
For more information, see Supported Built-In Material Models

Extended Support for Quadratic Anisotropic Yield

You can now specify quadratic anisotropic yield for Drucker Prager, creep, crushable foam, and Two-Layer Viscoplasticity for numerical and FE-based calibrations.
Benefits: This enhancement provides a general capability for calibrating materials that experience different yield or creep behavior in different directions.
For more information, see Supported Built-In Material Models

Support for Common Empirical Hardening Laws

You can now choose from a larger set of plastic hardening laws for numerical and FE-based calibrations. The newly available hardening formulas include Ludwik, Swift, Voce, and Swift-Voce.
Benefits: This enhancement provides a greater flexibility in calibrating materials that undergo plastic yielding.
For more information, see Supported Built-In Material Models

Support for Linear Extrapolation for Tabular Plasticity

You can now specify linear extrapolation of the yield stress outside the specified range of the equivalent plastic strains for tabular plasticity for numerical and FE-based calibrations.
Benefits: This enhancement provides a greater flexibility in calibrating materials that undergo plastic yielding.
For more information, see Supported Built-In Material Models

Support for User-defined Hardening

You can now define your own hardening laws for use in numerical and FE-based calibrations.
Benefits: This enhancement provides a greater flexibility in calibrating materials that undergo plastic yielding.
For more information, see About User Subroutines

Support for User-defined Nonlinear Viscoelastic Networks

You can now define your own hardening laws for use in numerical and FE-based calibrations.
Benefits: This enhancement provides a greater flexibility in calibrating materials models with nonlinear viscoelastic networks defined using the parallel rheological frame.
For more information, see About User Subroutines

Support for Importing a Material Model

You can now import a previously defined material model.
Benefits: This enhancement allows you to start a calibration with a previously defined material model, an approach that can provide a good starting point for your calibration.
For more information, see Importing Existing Material Data for Use as the Initial Parameter Values in a Calibration

New Simulation Example: Hyperelastic-Viscoelastic Material Calibration for Butyl Rubber

A new simulation example is available that teaches you how to use stress-strain test data and the Material Calibration app to calibrate a material response for a sample of butyl rubber.
Because butyl rubber is viscoelastic, calibrating the material's response requires you to perform the following steps:
  • Load multiple stress-strain data sets of varying strain rates.
  • Define a hyperelastic-viscoelastic material model with a 5-term Prony Series to calibrate the rate-dependent material response.
  • Place more emphasis on the test data recorded at low strain rates than test data recorded at high strain rates.
  • Select an optimization algorithm that is suited for the test data.
Benefits: This example introduces features in the Material Calibration app that the previous example, Elastic and Plastic Material Calibration of Aluminum, did not include.
For more information, see Hyperelastic-Viscoelastic Material Calibration of Butyl Rubber