The Optimization of a Shaped-Charge Design Using Parallel Computers

Current supercomputers use large parallel arrays of tightly coupled processors to achieve levels of performance far surpassing conventional vector supercomputers. Shock-wave physics codes have been developed for these new supercomputers at Sandia National Laboratories and elsewhere. These parallel codes run fast enough on many simulations to consider using them to study the effects of varying design parameters on the performance of models of conventional munitions and other complex systems. Such studies maybe directed by optimization software to improve the performance of the modeled system. Using a shaped-charge jet design as an archetypal test case and the CTH parallel shock-wave physics code controlled by the Dakota optimization software, we explored the use of automatic optimization tools to optimize the design for conventional munitions. We used a scheme in which a lower resolution computational mesh was used to identify candidate optimal solutions and then these were verified using a higher resolution mesh. We identified three optimal solutions for the model and a region of the design domain where the jet tip speed is nearly optimal, indicating the possibility of a robust design. Based on this study we identified some of the difficulties in using high-fidelity models with optimization software to develop improved designs. These include developing robust algorithms for the objective function and constraints and mitigating the effects of numerical noise in them. We conclude that optimization software running high-fidelity models of physical systems using parallel shock wave physics codes to find improved designs can be a valuable tool for designers. While current state of algorithm and software development does not permit routine, ''black box'' optimization of designs, the effort involved in using the existing tools may well be worth the improvement achieved in designs