Q: I tried to compare RICSAC tests' total energy loss values with CRASH 3 algorithm and planar impact mechanics. I used NHTSA's stiffness coefficient values for wheelbase category and crush measurements in the papers you sent me. I found total energy loss values so different between 2 methods. Sometimes CRASH 3 results are 2 times higher than planar impact mechanics, and sometimes lower. Why like this do you think? Maybe it is because i used general stiffness coefficients, not the individual real values of vehicles?
- How do each analytical technique compare with the full scale tests?
How do your results for CRASH3 compare with the results reported in the literature?
- To be sure your MATLAB implementation is performing properly you should probably try to duplicate the reported results in the literature. For a presentation and discussions of the original CRASH reconstructions of the RICSAC tests, see the Jones report:
"Research Input for Computer Simulation of Automobile Collisions – Volume IV - Staged Collision Reconstructions", Jones, I.S., Baum, A.S., Calspan Report ZQ-6057-V-6, Contract DOT-HS-7-01511, December 1978
Some differences in correlation may be due to the Monk & Guenther “Update of CRASH2 Computer Model Damage Tables”, DOT-HS-806446, March 1983 (note: file is 5 megs)
The problem with the CRASH3 update by Monk & Guenther of the Damage tables was that the authors had problems with the fitting procedure and so they ended up averaging the stiffness tables between the CRASH2 and their ‘update’ and so the tables have some issues. Quoting from our 1986 paper "A Revised Damage Analysis Procedure for the CRASH Computer Program
- “(4) The test data upon which the CRASH3 empirical fits of the Monk & Guenther report Update of CRASH2 Computer Model Damage Tables are based should be carefully re-examined. In the development of those fits, it has been assumed that common crush properties exist within each size category of vehicle, regardless of differences in the basic layouts of components and in overhang dimensions. The total numbers of included vehicles are limited, and substantial adjustments have been made in the results. A fresh look, with the CRASH4 data needs in mind, may define more proper categories on the basis of stiffness and restitution. It may also eliminate any need for adjustment of the results”.
So the original ‘categories’ from CRASH2 may created a better comparisons than those with the CRASH3 tables.
And one would expect that using custom fitted coefficients for the individual vehicles should also help the CRASH results to better correlate with the full scale tests.
One last important note: A couple of things to be sure to include in any comparison of analytical techniques:
- How each individual analytical techniques compares with reality (as in full scale tests results)
A comparison of the input requirements for each technique: Are all directly measurable? Or are some subjective?
If something isn't measurable, how does an analyst objectively determine the input? Many analytical technique comparisons contain bias when the ‘answers are known’ during the comparisons. Subjective inputs can be arbitrarily adjusted for better correlation. The true test of an analytical technique is applying the technique blindly as is the case when used for actual applications in the field. What are the guidelines for a user to estimate the subjective inputs? And what is the range of possible variation of inputs?