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Polyurethane/Elastomer modelling in LS DYNA

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Joined: 11 years ago

Hello there,

Im a 4th year Aero-Mechanical Engineering student doing my thesis on valve dynamics. I need to model the elastomer as hyperelastic material as opposed to assuming linear elastic which is a poor approximation. Im using LS-DYNA 14.0 and I need to know how I can enter the Mooney-Rivlin Constants. I have the Excel Sheet from Experiments only. A uniaxial Tension/ Biaxial Tension and a PLANER tension(pure shear). I have only those data the strain values and the stress values for each of the tests. I do not have any other information regarding the experiment as a PhD student carried this out and I was only given the stress/strain values on excel to put into ls-dyna as hyperelastic modelling. I have looked numerous times into online and cant find how to enter the constants or a method of means to modelling the polyurethane. If someone could help me that would be great it would be really appreciated as this thesis is due a month today.


Ahmet Erik

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Joined: 12 years ago

Hi Ahmet,

To model an elastomer you need to reproduce the experimental sress-strain curve trough a numerical approach, this is often doing by different hyperelastic models that give you the necessary parameters (constants) for such purposes. Fortunately therere several software that read your data and do it automatically, like Abaqus and Ansys. Actually, the owners of this forum developed a very good one: MC Calibration. Check this link [url] [/url]

On the other hand, you could send me your data trough PM and Ill give the constants from Mooney-Rivlin.


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You can use MCalibration as Alejandro said.

You can also find the constants by hand. This may not produce the BEST fit but will be decent if you look at the extreme stress-strain pairs from your material test data.

This process is shown here:
[url] [/url]

On that webpage, look at examples 1 and 2.
Your uniaxial test data gives you \sigma_{11} and \lambda_1.
Your shear test would give you \sigma_{12} and &#8220,k.&#8221,
There are then two equations in \sigma_{11}, \sigma_{12} and you can solve for the two unknowns: \mu and \beta.