Calibrate a Material Model using DMA Data

Introduction to Calibrate Material Model using DMA Data

It is really easy to calibrate a material model using DMA data using MCalibration. It is also equally easy to calibrate a material to experimental data from multiple different test types. The following video shows how.

Introduction

This article shows how to use MCalibration to calibrate any material model to a dataset that consists of both stress-strain and Dynamic Mechanical Analysis (DMA) data. More specifically, it will show how to use cyclic uniaxial tension tests with built-in stress relaxation  segments (which is consistent with my definition of a “smart” test), and some DMA data (storage and loss modulus). The following two figures show the  stress-strain data.

The material was also tested using DMA frequency sweeps at a mean strain of 0.10 and a strain amplitude of 0.01, as shown in the following table and figures.

The material model calibration can be performed in 3 easy steps:

Define load cases: tension fast, tension slow, DMA

Select a  material model.

Click Run Calibration in MCalibration

Start by defining the fast uniaxial time-strain-stress data. Call the load case “Uniaxial-Cyclic fast”.

Then define the slow uniaxial time-stress-strain  data. Call the load case “Uniaxial-Cylic slow”.

Finally, read in the DMA data from the frequency sweep test. Any combination of mean strain, strain amplitude, frequency, or temperature sweeps can be used.

Select any of the supported material models. In this example we will use the PolyUMod TNV model. After the material model has been selected, start the material model calibration.

The figures below show that the calibrated material model accurately captures the stress relaxation and cyclic response.

 

 

Summary

This document shows how MCalibration can be used to calibrate a material model to any combination of traditional stress-strain data, and dynamic E’ and E” data. The ability to use results from any combination of different experimental tests is a significant advantage of MCalibration over other material model calibration approaches.

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