University of Notre Dame College of Engineering
C-SWARM | Center for Shock Wave-processing of Advanced Reactive Materials

C-SWARM

Center for Shock Wave-processing of Advanced Reactive Materials

We propose a coordinated effort combining multi-resolution Exascale simulations with co-designed experiments to characterize the thermo-mechanical and chemical response of HRMs to dynamical loading and heating.

We will focus on reactive composites produced by High Energy Ball Milling (HEBM), a promising strategy to control the initial degree and character of the inter- mixing between various components and, consequently, tune the resulting material properties. Our primary focus will be to examine intermetallic systems such as nickel-aluminum, Ni-Al. As part of the project, we additionally propose a novel application of shock-induced synthesis to obtain cubic boron nitride (c-BN). Boron nitride (BN) is isoelectronic to a similarly structured carbon lattice. The cubic (sphalerite structure) variety, c-BN, is analogous to diamond. Its hardness is inferior only to diamond, but its thermal and chemical stability are superior.

Computational Physics

The integrated computational approach for predicting the behavior of the demonstration and discovery systems will consist of combining macro- and micro-continuum representations. Our two-fold strategy recognizes that only a relatively small part of the material will generally be instantaneously exposed to shocks and/or undergoing large plastic flow, phase change, and reaction. The rest of the material may be adequately described by macroscopic constitutive models, based on homogenization of the complex but slowly-varying microstructure. However, the shocked and/or reactive regions will generally need a more fundamentally based simulation since no reliable and universal constitutive model exists. We will perform all the computations at the continuum level, since current experimental data does not provide evidence for considering molecular/atomistics scales. Our approach will take advantage of the instantaneous localization knowledge of those regions where full simulations are necessary. In short, we propose to solve phase-averaged macro-continuum equations with constitutive laws provided by results obtained from full simulations of the multi-phase mixture using micro-continuum equations. We will refer to codes that solve macro- and micro-problems as M&m codes.

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Computer Science

The goal of the Exascale Plan is to develop a dynamic resource allocation environment that maintains high levels of performance of the C-SWARM framework in the presence of varying resource demands. In order to accomplish this, clear advances are required in the areas of efficiency, scalability, programmability, power, and resilience. The execution model adopted, and the runtime system reflecting it, not only complements the M&m algorithms well, but exposes and exploits new forms of parallelism for scalability. In addition, a programming interface will be devised and implemented on top of the runtime system to ensure that the M&m algorithms in the C-SWARM framework can be efficiently represented and communicated to the underlying system. A new method of fault tolerance will be developed to continue computation in the presence of errors through graceful system degradation. Lastly, an infrastructure for managing the measurement and control of power consumption correlated with the computational workflow will be devised.

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V&V/UQ and Experimental Physics

The purpose of the V&V/UQ program is to provide a platform for computational model verification, validation, and propagation of uncertainties through the computational framework. Our emphases will be on quantifying the predictive ability of our multiscale simulations through deterministic verification strategies, coupled with stochastic and physically-based statistical techniques, for validation and UQ. The key component in our validation plan is a series of carefully co-designed simulations and experiments (with quantified uncertainties) to enable meaningful and rigorous comparison of simulations with experiments. Our computations will be data-driven, with morphological information and calibration data provided to our micro-continuum model, leading to a straightforward means for statistical validation.

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