ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S SECTION 10 MODELING ISSUES

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S10 - 2

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S COURSE OBJECTIVES What’s in this section: –Discontinuities –Motion Inputs –Spline Functions –Units –Good Modeling Practices –Bad Modeling Practices –Converging Solutions

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: DISCONTINUITIES Avoid discontinuities!!! –Discontinuities do not exist in nature –Discontinuities are the root cause of almost all simulation problems Examples of discontinuous functions –Min, Max, Int, Dim, Mod, IF Discontinuous displacements and velocities cause corrector and integrator failures Discontinuous accelerations cause integration failures (requires infinite force) Discontinuous forces cause corrector failures

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: MOTION INPUTS Motions should be such that they impose continuous accelerations Inputting measured data –Specify Motion as a velocity –Function = CUBSPL(id, expression, 0) User subroutines –Be very careful with IF logic –Avoid discontinuous intrinsic functions like MIN, MAX, MOD etc –Avoid AKISPL in MOTIONS Example Displacement Function: Acceleration is discontinuous! if (t<t 0 ) then value=0 else value=(t-t 0 ) 2 endif t0t0 t

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: SPLINE FUNCTIONS AKIMA Spline –Does not have smooth derivatives –Use only in forces –Do not use in any type of Motion CUBIC Spline –Has two continuous derivatives –Likely smoother than AKIMA

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: UNITS Widely separated numbers in a matrix can cause numeric difficulties (conditioning problems) Be careful when using inconsistent units. Make sure units consistency factors are correct Choose units so that model states (displacements, velocities) are reasonable values –Length units of millimeters may not be appropriate if you are modeling an aircraft landing on a runway Choose units so that stiffness values are not very big Choose time units appropriate to phenomena being studied

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: GOOD MODELING PRACTICES Do… –Always use DEBUG/EPRINT early in the validation phase of your model/simulation –Try hard to eliminate any source of discontinuities in the simulation –Always perform an initial static first, when applicable –Approximate forces with smooth, continuous functions –Extend the range of spline data beyond the range of need –Add damping so frequencies can die off –Use velocity-based motions if possible (see KB ) –Filter experimental data so high frequencies are removed –Eliminate the causes for all warnings during a simulation, from the model. A good model will generate no warnings during a simulation. –Make sure your results have converged before accepting them as the truth

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: BAD MODELING PRACTICES Avoid... –Redundant constraints –Very high damping coefficients –Using dummy parts –Connecting dummy parts with compliant connections (BEAMs, BUSHINGs, etc.) –User-subroutines (if possible) –Translational spring-dampers with spring length=0 (coincident I-J markers)

ADM703b, Section 10, February 2013 Copyright© 2013 MSC.Software Corporation S MODELING ISSUES: CONVERGING SOLUTIONS Assuming that you have set the output step size (DTOUT) appropriately to capture the required phenomena in your model, the following procedure is recommended to tune the ERROR tolerance: 1.Run your model with, for example, ERROR=1e-3 2.Plot a displacement result for a typical output of interest 3.Re-run your model with ERROR new = 0.1*ERROR old 4.Plot the same displacement signal and compare with previous run 5.If the signals differs too much, go to step 3 and repeat until you see converged results And then tune HMAX in a similar fashion: 6.Run your model with, for example, HMAX=1e-2 7.Plot an acceleration result for a typical output of interest 8.Re-run your model with HMAX new = 0.5*HMAX old 9.Plot the same acceleration signal and compare with previous run 10.If the signals differs too much, go to step 8 and repeat until you see converged results