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Using Nonlinear Dynamic Study for (1) Sine-on-Random and (2) Do Not Allow Penetration

Question asked by David Maxham on May 25, 2012
Latest reply on Nov 13, 2018 by Andre Nuesslein

In an earlier thread regarding random vibration, , we discussed the need to use Nonlinear Dynamic for the situation where the "do not allow penetration" requirement is needed.  Tony Botting also suggested Tom Irvine's site, as a source for synthesizing the random vibration PSD curve as a time-history input.  I've recently subscribed to Irvine's website - the $40 subscription is very reasonable considering all of the information (tutorials, software) that are available for downloading. 


Many of our random vibration analyses involved designs that have panels, brackets, etc., that are attached at defined points. The remaining portions of the mating surfaces are not bonded together - they are free to separate from each other - hence the need for the "do not allow penetration" condition.  Another reason for using Nonlinear Dynamic is the need to include both sine tones and random vibration (sine-on-random) in our analyses.  Looks like the only way to do this is convert the random PSD curve into the time domain and then add in the sine tones.


So, I gave the Nonlinear Dynamic a try, first by using Tom Irvine's software to convert the PSD data into the time domain - I'm working with just the random data now - I'll add the sine tones later.  My main goal is to see how well the "do not allow penetration" contacts work, and compare to the Linear Random Vibration results that I typically use.  Below is the curve of the converted PSD data in the time domain.  Since Nonlinear Dynamic limits the number of points to 5,000, only a portion of the curve is represented.  When I run a very simple model - a beam with a block on the end - the model runs forever - I think I'm using too small of a time step.  What I think I need help on is understanding how to trim down the time data, so my question (finally) is has anyone else worked with converting PSD curves into the time domain using Nonlinear Dynamic and what are the steps to maintaining a reasonably sized model and run time?  Thanks in advance for any help - Dave.



Time curve-1.jpg