During the simulation of contact problem model, the time step was always 5.0E-4sec. But the defined Maximum Time Step was 1.0e-2sec. Why the time step doesn't become shorter than 5.0e-4sce?

Q) During the simulation of contact problem model, the time step was always 5.0E-4sec. But the defined Maximum Time Step was 1.0e-2sec. Why the time step doesn't become shorter than 5.0e-4sce?

A)First of all, it(5.0e-4) is Maximum Time Step. And, maybe you set the Maximum Stepsize Factor as 20 in the contact characteristic page. RecurDyn adopted the concept of buffer radius shown below figure. In post-search stage, if no nodes with radius in the hitting body is contacted with the candidate lines in the defense body and some nodes with buffer radius are contacted, the integration step will be decreased. So, in this case, integration step is 1.oe-4 / 20. Therefore, it is 5.0e-4. *Numerical Integration Strategy. The sufficient condition for a successful numerical integration step is to satisfy both accuracy and stability of the state variables for a system without contact. Satisfaction of the accuracy and stability is not sufficient for a system with a contact. Suppose a bullet collides with an object. If the object is thin, the bullet passes through the object without noticing it. If the object is thick and a moderately large step size satisfies both the accuracy and stability, the bullet penetrates too deep at the first step of a contact. Large and sudden contact force due to the large penetration generally introduces a large numerical error in the state variables. The large numerical error often causes the integration step to fail. Therefore, the contact condition must be considered in deciding an integration step. In order to make a system transition from a non-contact status to a contact status smooth as much as possible, time of contact must be predicted accurately. However, the computationally extensive search algorithm must be triggered to predict the exact time of a contact even though two bodies of a contact pair are located in a distance. Easy and practical solution to this problem is to use the method of backtracking.