Reactive burn models represent a significant leap in high explosive (HE) modeling capability. The first generation of engineering models of HE detonation are called programmed burn models and they are largely based on the distance between a prescribed detonation point and each zone in a simulation. There have been many advancements to programmed burn models over the years and when the assumptions upon which they are based are met, a properly tuned programmed burn model can be highly accurate but if any of their assumptions is not met, as is the case for corner turning or weakly initiated HE burn, they will give the wrong answer. Reactive burn models represent an entirely new way of modeling HE burn. They use the local conditions of a zone – e.g. temperature, pressure or density – as calculated by a hydrocode to determine if and when the zone is going to detonate and if so, how rapidly. This difference opens up an entirely new set of capabilities for HE modeling. It makes it possible to accurately and predictively model phenomena like the effect of confinement and the formation of dead zones. Reactive burn models have seen sustained development effort at LANL for at least the last decade but several recent developments make it timely to transition reactive burn models from a research topic to a production tool. The main goal of this milestone is to facilitate and accelerate the adoption of reactive burn as a commonly available modeling option, with recommendations on the resolution that will be required and uncertainties associated with their modeling choices. To achieve this, we have performed verification, validation, and uncertainty quantification (UQ) assessments of AWSD and SURF/SURFplus in xRage and FLAG on a variety of different problems.

A computational verification and validation study of the Cyclops I experiment [1-7] was conducted using the Los Alamos Eulerian Applications code xRage [8]. The purpose of this study was to validate the Scaled Unified Reactive Front (SURF) plus (SURFplus) model for insensitive high explosives [9-12]. Diagnostics from the experiment included photon doppler velocimetry measurements of the encasing shell for the device and proton radiography photographs of the explosions. This data was compared to the xRage computed data and a convergence study of burn front evolution was conducted. We conclude that the SURFplus high explosive model does an excellent job at predicting the high explosive burn front velocity and shape with results that converge to the experimental data at rates near to or better than first order in most cases. Some companion verification metrics for the solution convergence are also described. These metrics show that the xRage computed solution for the high explosive burn front converges to first order or better, as consistent with the treatment of shock fronts in a higher order Godunov hydrodynamic solver as used in xRage.

We investigate sufficient conditions for thermodynamic consistency for equilibrium mixtures. Such models assume that the mass fraction average of the material component equations of state, when closed by a suitable equilibrium condition, provide a composite equation of state for the mixture. We show that the two common equilibrium models of component pressure/temperature equilibrium and volume/temperature equilibrium (Dalton, 1808) define thermodynamically consistent mixture equations of state and that other equilibrium conditions can be thermodynamically consistent provided appropriate values are used for the mixture specific entropy and pressure.

with the option, within EOSPAC, to invert the table at setup, using a linear or rational interpolator, and using an EOS table cut down to only the region actually sampled in the problem. Air and Deuterium are used as the test materials for the simulations. While using EOS data directly with EOSPAC, the rational interpolator takes about twice as long as the linear one. Additionally, using a windowed EOS table does not show a large increase in performance. An EOS table that has had more energy grid points interpolated and added in by EOSPAC showed more accurate results, suggesting that a more dense EOS table would be more accurate.

with the option, within EOSPAC, to invert the table at setup, using a linear or rational interpolator, and using an EOS table cut down to only the region actually sampled in the problem. Air and Deuterium are used as the test materials for the simulations. While using EOS data directly with EOSPAC, the rational interpolator takes about twice as long as the linear one. Additionally, using a windowed EOS table does not show a large increase in performance. An EOS table that has had more energy grid points interpolated and added in by EOSPAC showed more accurate results, suggesting that a more dense EOS table would be more accurate.

A ghost fluid method for compressible multi-fluid flows is presented in an adaptive mesh refinement (AMR) environment, where the volume of fluid method is used to track the interface. Various numerical examples are presented to compare the proposed method with interface capturing methods using pressure-temperature equilibrium and non-equilibrium temperature mixed cell approaches. It is found both mixing models are unable to generate accurate results for strong shock refractions through high acoustic impedance mismatch interfaces. The proposed method is found to be quite robust and can provide relatively reasonable results across a wide variety of flow regimes. The ghost fluid coupling between the fluid solver and the volume of fluid method is designed to be simple and consistent in any spatial dimension on AMR grid. Published by Elsevier Ltd.

We describe the method to port a sequential 3D interface tracking code to a GPU with CUDA. The interface is represented as a triangular mesh. Interface geometry properties and point propagation are performed on a GPU. Interface mesh adaptation is performed on a CPU. The convergence of the method is assessed from the test problems with given velocity fields. Performance results show overall speedups from 11 to 14 for the test problems under mesh refinement. We also briefly describe our ongoing work to couple the interface tracking method with a hydro solver.

This article describes mathematical models for phase separated mixtures of materials that are in pressure and velocity equilibrium but not necessarily temperature equilibrium. General conditions for constitutive models for such mixtures that exhibit a single mixture sound speed are discussed and specific examples are described.

We investigate the effects ofthermal equilibrium on hydrodynamic flows and describe models for breaking the assumption ofa single temperature for a mixture of components in a cell. A computational study comparing pressure-temperature equilibrium simulations of two dimensional implosions with explicit front tracking is described as well as implementation and J-D calculations for non-equilibrium temperature methods.

The purpose of this paper is to propose a simple (one or two parameter) multiphase flow model, suitable for the description of Rayleigh–Taylor and Richtmyer–Meshkov mixing layers. We justify model closure assumptions in this model by comparison to Rayleigh–Taylor and Richtmyer–Meshkov simulation data. We show that the relative errors related to model closure terms are about 10%, and are about two to four times smaller than related closure models of Abgrall and Saurel.

We outline a program for the study of turbulent mixing of compressible fluids. We emphasize recent progress and steps still to be taken.