Christopher Lange (Department of Mechanical Engineering, HSU)
The project aims at establishing an optimized simulation framework for the atomistic modeling of impact-induced chemical reactions in new weapon materials. In our mechano-chemical research we combine atomic and molecular dynamics simulations. Strain-dependent reaction paths are determined with static ab initio simulations and coupled with impact-induced strains found by molecular dynamics. Together with the experts of hpc.bw we want to increase our research efficiency through better connections of our different simulations, their optimization for the HPC environment, and improved data management.
New weapon systems incorporating Reactive Materials (RMs) pose a serious threat to established armor solutions, as they can release additional amounts of chemical energy, when subjected to sufficient mechanical loads. This effect is used to enhance the damage capabilities of novel projectiles or warheads. To design new protective systems against RMs, a thorough threat assessment and the understanding of their terminal ballistic behavior is necessary.
So far, mostly macroscopic simulations or empirical approaches have been used to model the energy release behavior of RMs. Systematic studies on a wide range of material compounds, and the influence of their respective constituents, have not been conducted yet. Since this is a strenuous and expensive endeavor under experimental conditions, simulations on atomic scales open new possibilities in this area of materials research. An optimized and automated simulation environment, driven by High-Performance Computing (HPC) at its heart, is necessary to handle such amounts of data and huge parameter fields.
In detail, the projected work within hpc.bw includes at first the optimization of the modeling software for the HPC cluster, namely the VASP and LAMMPS codes. This includes varying compilations and benchmarking their runtime for different modeling goals. As the environment will rely heavily on automation, the second step will focus on automating pre-/post-processing of the respective simulation data, its input/output, and its management within databases. For this, a combination of established and self-developed python-based solutions will be used. In the third and concluding step, the simulation data and models are interconnected, and a common user-interface/API is built, using again python-based code and MongoDB.
The so built setup will allow us to investigate relevant materials and their combinations under the influence of a wealth of reaction parameters, while simultaneously reducing user-interaction with the simulations drastically. This will free up researcher’s time to focus on the interpretation of results and their validation with experiments.
The hpc.bw-project at the University of the Federal Armed Forces Hamburg will enable us to investigate materials, their combinations, and their threat potential throughout the whole periodic table in a high-throughput manner. A necessary first step for the design of future protection systems of our armed forces.