High explosives are an important class of energetic materials used in many weapons applications. Even with modern computers, the simulation of the dynamic chemical reactions and energy release is exceedingly challenging. While the scale of the detonation process may be macroscopic, the dynamic bond breaking responsible for the explosive release of energy is fundamentally quantum mechanical. Thus, any method that does not adequately describe bonding is destined to lack predictive capability on some level. Performing quantum mechanics calculations on systems with more than dozens of atoms is a gargantuan task, and severe approximation schemes must be employed in practical calculations. We have developed and tested a divide and conquer (DnC) scheme to obtain total energies, forces, and harmonic frequencies within semi-empirical quantum mechanics. The method is intended as an approximate but faster solution to the full problem and is possible due to the sparsity of the density matrix in many applications. The resulting total energy calculation scales linearly as the number of subsystems, and the method provides a path-forward to quantum mechanical simulations of millions of atoms.
Density Functional Theory (DFT) based Equation of State (EOS) construction is a prominent part of Sandia's capabilities to support engineering sciences. This capability is based on amending experimental data with information gained from computational investigations, in parts of the phase space where experimental data is hard, dangerous, or expensive to obtain. A prominent materials area where such computational investigations are hard to perform today because of limited accuracy is actinide and lanthanide materials. The Science of Extreme Environment Lab Directed Research and Development project described in this Report has had the aim to cure this accuracy problem. We have focused on the two major factors which would allow for accurate computational investigations of actinide and lanthanide materials: (1) The fully relativistic treatment needed for materials containing heavy atoms, and (2) the needed improved performance of DFT exchange-correlation functionals. We have implemented a fully relativistic treatment based on the Dirac Equation into the LANL code RSPt and we have shown that such a treatment is imperative when calculating properties of materials containing actinides and/or lanthanides. The present standard treatment that only includes some of the relativistic terms is not accurate enough and can even give misleading results. Compared to calculations previously considered state of the art, the Dirac treatment gives a substantial change in equilibrium volume predictions for materials with large spin-orbit coupling. For actinide and lanthanide materials, a Dirac treatment is thus a fundamental requirement in any computational investigation, including those for DFT-based EOS construction. For a full capability, a DFT functional capable of describing strongly correlated systems such as actinide materials need to be developed. Using the previously successful subsystem functional scheme developed by Mattsson et.al., we have created such a functional. In this functional the Harmonic Oscillator Gas is providing the necessary reference system for the strong correlation and localization occurring in actinides. Preliminary testing shows that the new Hao-Armiento-Mattsson (HAM) functional gives a trend towards improved results for the crystalline copper oxide test system we have chosen. This test system exhibits the same exchange-correlation physics as the actinide systems do, but without the relativistic effects, giving access to a pure testing ground for functionals. During the work important insights have been gained. An example is that currently available functionals, contrary to common belief, make large errors in so called hybridization regions where electrons from different ions interact and form new states. Together with the new understanding of functional issues, the Dirac implementation into the RSPt code will permit us to gain more fundamental understanding, both quantitatively and qualitatively, of materials of importance for Sandia and the rest of the Nuclear Weapons complex.
This report gives an overview of the work done as part of an Early Career LDRD aimed at modeling flow induced damage of materials involving chemical reactions, deformation of the porous matrix, and complex flow phenomena. The numerical formulation is motivated by a mixture theory or theory of interacting continua type approach to coupling the behavior of the fluid and the porous matrix. Results for the proposed method are presented for several engineering problems of interest including carbon dioxide sequestration, hydraulic fracturing, and energetic materials applications. This work is intended to create a general framework for flow induced damage that can be further developed in each of the particular areas addressed below. The results show both convincing proof of the methodologies potential and the need for further validation of the models developed.
Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.
Software lifecycles are becoming an increasingly important issue for computational science and engineering (CSE) software. The process by which a piece of CSE software begins life as a set of research requirements and then matures into a trusted high-quality capability is both commonplace and extremely challenging. Although an implicit lifecycle is obviously being used in any effort, the challenges of this process - respecting the competing needs of research vs. production - cannot be overstated. Here we describe a proposal for a well-defined software lifecycle process based on modern Lean/Agile software engineering principles. What we propose is appropriate for many CSE software projects that are initially heavily focused on research but also are expected to eventually produce usable high-quality capabilities. The model is related to TriBITS, a build, integration and testing system, which serves as a strong foundation for this lifecycle model, and aspects of this lifecycle model are ingrained in the TriBITS system. Here, we advocate three to four phases or maturity levels that address the appropriate handling of many issues associated with the transition from research to production software. The goals of this lifecycle model are to better communicate maturity levels with customers and to help to identify and promote Software Engineering (SE) practices that will help to improve productivity and produce better software. An important collection of software in this domain is Trilinos, which is used as the motivation and the initial target for this lifecycle model. However, many other related and similar CSE (and non-CSE) software projects can also make good use of this lifecycle model, especially those that use the TriBITS system. Indeed this lifecycle process, if followed, will enable large-scale sustainable integration of many complex CSE software efforts across several institutions.