Lagrangian approach embed with discrete element method for extreme deformation study in frangible bullet designs fragmentation and penetration on viscoelastic ballistic gel.

Development of a model for analyzing a bullet's impact is important in the military field to design a bullet with desired properties. This study uses a finite element model with a Lagrangian framework and Lagrange-discrete element method (DEM) model by ANSYS Explicit Dynamic to investigate the effect of frangible bullet designs on bullet deformation and penetration in ballistic gel setting. A modeling approach with ballistic gel can analyzed the extreme deformation of bullets much faster compared to the more resource intensive real life ballistic gel test.

Well-conditioned model predictive control.

Model-based predictive control is an advanced control strategy that uses a move suppression factor or constrained optimization methods for achieving satisfactory closed-loop dynamic responses of complex systems. While these approaches are suitable for many processes, they are formulated on the selection of certain parameters that are ambiguous and also computationally demanding which makes them less suited for tight control of fast processes. In this paper, a new dynamic matrix control (DMC) algorithm is proposed that reduces inherent ill-conditioning by allowing the process prediction time step to exceed the control time step.